September 26, 2023

What are the signs of digital disruption for a company/industry ?

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Read: Digital (R)evolution – Chapter 3 – Idea Incubation

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1.What are the signs of digital disruption for a company/industry ?

2.What is needed for your company/industry immediate survival?

3.Why most of organizations struggle with the innovative transformation?

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Table of ContentsCOVERFOREWORDPREFACEDefinition of Work Is ChangingDo Not Ignore the Emotional ComponentEcosystems of DisruptionHope for the Best, Prepare for the WorstACKNOWLEDGMENTSChapter 1: Drivers of ChangeBrass Ring or Black Hole?Mechanics of TransformationLevels of TransformationOn the Ground and in the TrenchesChapter 2: Focus and DisciplineBrace for Impact

Chapter 3: Idea IncubationOvercoming the Natural Inclination to AvoidRiskYou Can’t Just Wing ItInside the IncubatorThe QRate TemplateLessons from the FieldChapter 4: Operational ExcellenceLearning from DataEarning Trust and Building ConfidenceResponse Time vs. Resolution TimeChapter 5: Customer-Driven ChangeDigital AlchemyAutomated Customer ServicesBasic Principles of TransformationKnow ThyselfReal-World Examples and War StoriesChapter 6: Strategy vs. Execution

A Blend of Science and SentimentSetting StrategyChapter 7: Hire Captains, Not Kings or QueensThe Kid in the CornerThe Man with Blue HairThe ReceptionistNeha and RahulChapter 8: Integrated EcosystemsMaking the Case for CollaborationDon’t Make AssumptionsWhen Life Gives You Lemons…Communities of PracticeSocial and Collaboration ToolsInnovation TargetsKey Success FactorsGreat Execution Eats Strategy for Lunch!Lessons Learned on ExecutionDealing with an Informed and IntelligentAudienceDealing with a Knowledgeable AudienceGlobal Research Use Case

More Lessons Learned: When Business StrategyIs the Only Driver of TransformationUsing Machine Learning to Solve theInformation Overload ChallengeThe Future of CollaborationChapter 9: Digital Proficiency and InnovationHere Come the RobotsA Long and Winding RoadInnovation and the Agility ParadoxChapter 10: Are You “Digitally Determined” or“Digitally Distraught”?Why Digital Transformation Seems ConfusingAgent of ChangeThree Fundamental ObjectivesKey Strategic Elements and Success FactorsForging a Transformation RealityDetermined or Distraught?Tone from the TopNotesChapter 11: Use Case: The Smart City

An Infinite Universe of Moving PartsSafety FirstSix Areas of “Smartness”Four Stages of EvolutionNoteChapter 12: Looking Ahead: Runway or Precipice?Artificial IntelligenceBlockchainRoboticsVirtual RealityBig DataCloudInternet of ThingsMarketing Automation and ProgrammaticAdvertisingDon’t Get Fooled Again…Chapter 13: AI: The Elephant in the RoomWhat Artificial Intelligence Is and Isn’tAdaptive Business Process TransformationDebunking Myths About Artificial IntelligenceFinding Needles in Haystacks

Will AI Replace Your Employees?Is There a Difference Between AI and DataScience?Skills You Need to Become a Data ScientistAI is Part of the Emerging DARQ StackNotesAFTERWORDData about Digital TransformationTools and TechniquesDigital IdentityNoteABOUT THE AUTHORINDEXEND USER LICENSE AGREEMENTList of IllustrationsChapter 2Figure 2.1 Urgent vs. Important matrix.

Figure 2.2 Urgent vs. Important matrix withexamples.Chapter 3Figure 3.1 The QRate Model.Figure 3.2 Actions by audience segmentation.Figure 3.3 Managing adoption rates throughbetter issue resolution.Chapter 4Figure 4.1 Bottom-up approach to servicequality.Chapter 9Figure 9.1 The SMART business and digitaltransformation method.Chapter 10Figure 10.1 Perception and Truth matrix.Figure 10.2

DIGITAL (R)EVOLUTIONStrategies to Accelerate BusinessTransformation YURI AGUIAR

© 2020 by John Wiley & Sons, Inc. All rights reserved.Published by John Wiley & Sons, Inc., Hoboken, New Jersey.Published simultaneously in Canada.No part of this publication may be reproduced, stored in a retrieval system,or transmitted in any form or by any means, electronic, mechanical,photocopying, recording, scanning, or otherwise, except as permitted underSection 107 or 108 of the 1976 United States Copyright Act, without eitherthe prior written permission of the Publisher, or authorization throughpayment of the appropriate per-copy fee to the Copyright Clearance Center,Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750–8400, fax (978)646–8600, or on the Web at www.copyright.com. Requests to the Publisherfor permission should be addressed to the Permissions Department, JohnWiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748–6011,fax (201) 748–6008, or online at www.wiley.com/go/permissions.Limit of Liability/Disclaimer of Warranty: While the publisher and authorhave used their best efforts in preparing this book, they make norepresentations or warranties with respect to the accuracy or completenessof the contents of this book and specifically disclaim any implied warrantiesof merchantability or fitness for a particular purpose. No warranty may becreated or extended by sales representatives or written sales materials. Theadvice and strategies contained herein may not be suitable for yoursituation. You should consult with a professional where appropriate.Neither the publisher nor author shall be liable for any loss of profit or anyother commercial damages, including but not limited to special, incidental,consequential, or other damages.For general information on our other products and services or for technicalsupport, please contact our Customer Care Department within the UnitedStates at (800) 762–2974, outside the United States at (317) 572–3993, orfax (317) 572–4002.

Wiley publishes in a variety of print and electronic formats and by print-on-demand. Some material included with standard print versions of this bookmay not be included in e-books or in print-on-demand. If this book refers tomedia such as a CD or DVD that is not included in the version youpurchased, you may download this material athttp://booksupport.wiley.com. For more information about Wiley products,visit www.wiley.com.Library of Congress Cataloging-in-Publication Data:Names: Aguiar, Yuri, author.Title: Digital (r)evolution : strategies to accelerate business transformation /Yuri B Aguiar.Description: First Edition. | Hoboken : Wiley, 2020. | Includes index.Identifiers: LCCN 2019053582 (print) | LCCN 2019053583 (ebook) | ISBN9781119619734 (hardback) | ISBN 9781119619741 (adobe pdf) | ISBN9781119619789 (epub)Subjects: LCSH: Business enterprises—Technological innovations. |Information technology—Management. | Strategic planning.Classification: LCC HD45 .A4768 2020 (print) | LCC HD45 (ebook) | DDC658.4/06—dc23LC record available at https://lccn.loc.gov/2019053582LC ebook record available at https://lccn.loc.gov/2019053583Cover Design: Wiley/Aaron AguiarCover Image: © imaginima/Getty Images

For Lynn, who taught me resilienceFor Aaron and Brandon, who inspire me every dayFor my parents, who taught me the value of hard workFor my grandmother, my role model growing upFor family and friends who were always there through thegood times and otherwise

FOREWORDWaterwheels transformed agriculture and electricitytransformed manufacturing. Today, digital technologies aretransforming everything.The scope of this transformation is truly astonishing. It’s notsurprising that many companies find the challenges of digitalbusiness transformation overwhelming. That’s why this book isso important. It’s a practical guide for navigating the roughwaters ahead of us.This book is also a potent reminder that genuinetransformation is always about people and about providingtangible opportunities for real growth. Transformation is aprocess, and it moves along a fairly predictable path. This bookwill help you stick to the path and not get distracted.From my perspective, transformation enables and empowerscompanies to utilize both customer data and performance datato create new revenue lines that are both vertically andhorizontally integrated. Transformation sets the stage forcreating new business models and new forms of commerce.Digital transformation is necessary for success and survival intoday’s economy, since every company can be considered a

technology company and a potential competitor. The explosionof digital technology has opened the floodgates for newentrants in every sector of the global economy, putting everyestablished incumbent and legacy organization at risk.The prime example of this phenomenon is Amazon, whosebrilliant use of data analytics completely disrupted the retailindustry. There’s a harsh lesson to be learned from Amazon’srise: if existing companies neglect to embrace digitaltechnology, new entrants will certainly attempt to disrupt theirbusiness models.The rapid success of Amazon and other digital disruptors hasleft many executives in a state of shock. Many organizationsseem overwhelmed by the sheer scale of change they face. Fromthe perspective of a traditional company, the challenges canappear insurmountable.When people feel helpless, they often make rash decisions thatprove untenable over time. In their rush to “do something,”they make mistakes. Aiming for short-term victories, theysacrifice strategic goals. Reading this book will help youovercome whatever natural sense of panic you might be feeling.This book will help you slow down and thoughtfully considerthe logical steps of business transformation.From my perspective, the best approach is setting reasonablemilestones and focusing on incremental gains. Establishmeasurable and specific key performance indicators (KPIs),

benchmarks or milestones that will guide you gradually towardsuccess.Don’t just say, “We want transformation.” Instead, decide whattransformation looks like to you and how you will get there.Develop a plan ahead of time and stick to it—but don’t be afraidto update it as you move along your transformation journey.Cultivate trusted partners to help you execute. Revisit yourtransformation strategy regularly to keep growing far into thefuture.The power of technology is both exciting and compelling.Helping other people recognize what an effective strategy cancreate for them and seeing them getting excited about it—that’sa great feeling.We all love to read and hear about success stories, whereeverything works. This book will help you and yourstakeholders write your own success stories.Some people ask me, “What’s next? What comes aftertransformation?” Frankly, I believe the next big challenge willbe answering the same questions that successful, forward-thinking companies have always been asking:How can we provide further opportunities for ouremployees, our experts, our leaders, and our creativethinkers to grow and develop?

Arup DasCEO, Alphaserve TechnologiesHow can we strengthen the relationship between thecorporation and the people it serves, its employees, andthe larger community?These basic questions haven’t changed—the best companies arealways looking toward the future. What will change, however,are the ways we work toward achieving our goals, using theknowledge and resources available to us through digitalbusiness transformation.This book is an important step toward achieving a betterfuture, and I am confident that you will enjoy reading it.

PREFACEWe’ve all heard and read that digital transformation ischanging our lives. But how precisely are we beingtransformed? Which aspects of our lives are changing and whydoes digital transformation matter? Why should you read thisbook? More specifically, why should you read this book rightnow?Digital transformation and digital disruption are urgentconcerns for all of us, all over the world. Together they havebecome an inexorable force of nature. Even if your organizationis operating smoothly and hitting its numbers today, I canguarantee you will experience transformation and disruption inthe near future.Elon Musk talks about sending people to Mars. On everyimaginable level, the act of colonizing another planet wouldprofoundly transform human culture. Yet we are already deepinto the process of transforming humanity.For the past 100 years, we have been shifting steadily from aculture based primarily on physical labor to a culture basedprimarily on intellectual labor. In recent decades, the shift hasbeen accelerated by the availability of high-speed computingand broadband communications networks, and by the

emergence of data science techniques that have led to thedevelopment of practical artificial intelligence.Soon, the knowledge workers who replaced physical laborerswill be at risk of being replaced by AI bots. With alarmingspeed, we are transitioning from a carbon-based to a silicon-based civilization. This transformation is not a trivial matter.Definition of Work Is ChangingWithin an extremely brief span of time, everything we think ofas “work” will be performed by physical or digital robots(scripts) guided by artificial intelligence. Any kind of repetitivetask that can be automated will be automated. For humanbeings, work will become a blend of complex abstract reasoningand pure creativity. In other words, people will only do workthat machines are incapable of performing.What kind of work will we do? Anything that requirescreativity, imagination, tenderness, affection, empathy, or love.We will be creators, innovators, inventors, entrepreneurs,artists, poets, teachers, athletes, gamers, healers, caregiversand lifelong learners.This is not science fiction or fanciful thinking. We’re no longeron the cusp of a new era. We are experiencing the opening actof a fundamental shift. Some parts of the world will arrive at

this future state sooner than others. But this is our shareddestiny, and we need to prepare for it.That’s the big picture, in broad strokes. The rest of this book isabout the details of getting from our present state to our digitalfuture. This book is neither a roadmap nor a theoreticaltreatise. It falls somewhere in between.I’m perturbed by pundits who make false comparisons betweenthe digital transformation we’re facing today andtransformations of the past. The digital disruption I’m writingabout will shake the foundations of society. It will truly rockour world and change our lives. Most of those changes will befor the better. But many of the changes will leave us feeling lostand confused.Digital transformation will create millions of new jobs. From aglobal perspective, I am optimistic and enthusiastic about ourfuture. Yet I am also a realist, and I know that transformationwill eliminate jobs and disrupt the careers of people in manysectors of the global economy.“A digital tsunami is coming,” says Chetan Dube, a thoughtleader in artificial intelligence and the chief executive officer ofIPsoft. “Overall, it’s a benign tsunami. But it’s like a 100-footwall of water coming toward us. It will sweep away many of theordinary chores and tasks we do at work. It will removedrudgery from our lives, freeing us to become our best andmost creative selves. But we cannot simply sit on the beach and

wait for the tsunami to hit us. We must prepare. We must moveto higher ground.”Do Not Ignore the EmotionalComponentMoving to higher ground requires leaving behind anything thatisn’t required for immediate survival. As leaders oftransformation, it’s our responsibility to help people overcomethe emotional obstacles they will invariably face as they shedtheir old work habits and adopt new methods for achievingtheir goals in the modern workplace.The process of moving from the familiar past into an unknownfuture is difficult, to say the least. Ignoring the emotionalcomponent would be a sign of poor leadership, and a clearinvitation to failure.I had a wonderful conversation with my friend and colleague,Ben Richards. Ben is the worldwide chief strategy officer atOgilvy, and he has vast experience helping major brands thatare grappling with business transformation strategies.Here’s a brief summary of what Ben told me:

There are two ways of doing transformation; one thatsets you up for catastrophe and another that usuallyworks out quite well. The first way is to sit everyonedown and offer them an extraordinarily rationalexplanation of your transformation strategy. Thatapproach almost always paves the road to ruin.The second approach is explaining to people how thestrategy will impact them as individuals. Tell them how itwill affect their income and their career. Explain how thestrategy will help them become more successful, morefulfilled, and more satisfied.Given the choice, Ben says, he would “pick the emotionalargument over the rational argument any day of the week.”He also recommends reaching out to all the stakeholders in theorganization, especially those in the trenches and on the frontlines. Make sure that you understand and address their fearsand concerns. “You need to win the hearts and minds of yourconstituents,” Ben says.The last thing you need during a transformation, he says, is adissatisfied workforce. “If you think that analysts won’t callyour employees and ask them off the record how thetransformation is going, you are mistaken,” he says.Ben advocates in favor of an approach he calls “Platform,Program, Pulse.” In this approach, a transformational strategy

is divided into time horizons:Platform = Long TermProgram = Medium TermPulse = Short TermIt’s not too different from the idea of going for quick victorieswhile you keep your eye on the long-range goal. I also like howthe Platform/Program/Pulse model gives you breathing room.Instead of attempting to do everything all at once, you establisha logical timeline for accomplishing the various parts of yourtransformation strategy.I genuinely admire Ben’s approach, and I urge you to keep it inmind as you move through the stages of your owntransformational efforts.Ecosystems of DisruptionIt’s also imperative to remember that transformation anddisruption do not occur in a vacuum. At the risk of stating theobvious, everything is connected. Instead of thinking abouttransformation and disruption as free-standing events, I urgeyou to envision them as constituent parts of a much larger andcontinually evolving ecosystem of organizations and theirstakeholders.

I found the experience of Goran Kukic, head of IT innovation atNestlé, to be highly instructive. In a wide-ranging conversation,Kukic described how Nestlé built a specific program for dealingwith the startup community, which is a prime source ofdisruptive innovation and transformation.“Dealing with a startup can be exceptionally challenging,”Kukic says. “You can’t send a 40-page contract to a startup.They are simply not traditional companies.”Even when there are clear business reasons for collaborating,cultural mismatches between startups and traditionalcompanies can lead to disastrous relationships. To improve theodds of success, Nestlé created a Silicon Valley InnovationOutpost to scout opportunities for collaboration and buildessential relationships on the ground.“We realized there was so much more to be learned fromstartups,” he says. Today, Nestlé has a team of innovationmanagers in the San Francisco Bay area. They have becomefamiliar faces in the startup community; they are part of thelandscape.From my perspective, Nestlé’s approach is absolutely brilliant.Instead of regarding innovation, disruption, andtransformation as alien or unnatural, the company sees themas natural and integral to continuing success.

Hope for the Best, Prepare for theWorstPart of our general uneasiness about digital disruption,however, arises from our sense that it is occurring quitesuddenly. In fact, it is the tail of a larger transformation that’sbeen going on since the beginning of the twentieth century. Wetend to think of the most recent advances in technology asbeing the most significant and the most influential, but thereality is more nuanced. Each of the previous advances wasessential, and we wouldn’t be where we are today withoutthem.Moreover, the pace of transformation has been logarithmic, notlinear. Each of the five advances in computing can be rightfullyconsidered a paradigm shift, and each advance contributedexponentially to the growth of computing power.I mention this because it’s important to dispel any notions thatdigital transformation is some kind of magical event or suddenbreak with the past. Digital transformation is both a powerfulforce and a natural leap forward in a process that’s been goingon for quite a while.If digital transformation is merely another step in a naturalprocess, why do so many people find it confusing? The answeris simple and somewhat embarrassing: the business technologycommunity has done a less than stellar job of explaining what

digital transformation is and how it will affect the lives ofeveryday people.A world-renowned creative leader who works with technologycompanies on defining their brands puts it eloquently:We talk about digital transformation and we know it’scoming, but nobody really knows what it means, it’s aloose term. Most of us don’t know exactly how digitaltransformation will change our lives and our jobs, so weassume the worst.His comments echo the sentiments of many people weinterviewed for this book. I cannot offer answers to theexistential questions raised about digital transformation. I will,however, provide specific steps and processes for assuring thebest possible outcomes from your business transformationefforts.We do not live in a deterministic universe. I do not believe thefuture is carved in stone. Technology is a tool and we get tochoose how we want to use it. This book lays out some of thechoices. It offers suggestions for moving forward in athoughtful and responsible manner. I hope you find this bookhelpful in your transformation journey.I conclude my introduction with wise words from LaurenCrampsie, president, Ogilvy New York:

Change of any kind, digital or human, is always aboutmanaging expectations, setting goals and defining clearresponsibilities for executing against those objectives.Given the pace of change today, organizations have torespond with a tenacity which often means questioningevery precedent and definitely changing the status quo.

ACKNOWLEDGMENTSThank you to all my colleagues, friends, and advisors forsharing of your precious time and brilliance to this project; thisbody of work would not be the same without your real-lifeexperiences and inputs: Mitra Best, Lauren Crampsie, ChetanDube, Sonia Fernandes, Anna Frazetto, Steve Goldstein, NaliniGuhesh, Carla Hendra, Nikhil Jinghan, Goran Kukic, AdamMorris, Ben Richards, Rajesh Sinha, Atle Skjekkeland, R.Sridhar, Steve Sterin, Jonathan Stern, Tiger Tyagarajan, PhilWiser, and Sigal Zarmi.Special thanks to Arup Das, Vineet Jain, Thornton May, andMeredith Whalen for your extended contribution, counsel, andthe immeasurable amounts of time that you offered to thisendeavor.Special thanks to Mike Barlow for your patience in the writingprocess and helping me keep it real.And thanks to Sheck Cho, who made this project possible.

Chapter 1Drivers of ChangeExecutive Summary: The world is changing rapidly andorganizations need to adapt to survive. Transformation is anessential and inevitable process of business evolution,requiring hard decisions about the allocation of limitedresources. Assembling the right team of people is primary tosuccess; the technology is secondary.Thanks to Clayton Christensen, we’re all familiar with theconcept of disruption. In his classic bestseller, The Innovator’sDilemma, Christensen describes the fate of major companiesthat don’t foresee the impact of disruption on their businessmodels.The disrupted companies were not run by fools. For the mostpart, their executives were intelligent, skilled, and experiencedbusiness leaders. With the luxury of 20-20 hindsight, it’s easyfor us to shake our heads and wonder why they missed thesignals that foretold their demise.We cannot change the past. But we can influence the future. Myadvice to everyone reading this book is to dust off your copy ofThe Innovator’s Dilemma and read it again. This time, askyourself if your organization is a likely target for disruption.

Here’s a quick pass-fail test to determine if your organization isa candidate for disruption:Have you digitized all of your business processes?Are you collecting data from all your businessprocesses?Are you analyzing the data you collect?Are you optimizing your processes based on insightsgenerated by your analysis of the data?If you answered “no” to any of the questions above, you mustconsider your organization a candidate for disruption.Here’s the plain unvarnished truth: if your organization is noton a path to having working digital version of every criticalprocess it performs, your organization will be disrupted and inall likelihood will fail.Today, every business-to-consumer (B2C) organizationunderstands that simple fact. It’s digital or die. That’s why B2Ccompanies are racing to provide their customers with the bestpossible digital experiences.The smarter business-to-business (B2B) firms also understandthis, but you would be surprised how many are lagging. Thebad news for them: the digital laggards will fail or at the veryleast fall behind those who have indeed threaded that needle.

They will be unable to compete in a world in which the majorityof their potential customers want to interact with your websitebefore they talk with anyone from your sales team.“Millennials don’t want to have a conversation with your salesteam, they want to have a conversation with your website,” saysAdam Morris, CEO of Redstage, a strategy and designconsulting firm specializing in B2B ecommerce.It’s easy to pick on millennials, and the demographic ismischaracterized in almost every conversation. I’ve heardcountless complaints about how this demographic doesn’t wantto communicate. That’s unfounded rhetoric. Millennialsdefinitely want to communicate using their medium of theirchoice. They’re constantly communicating via text and socialmedia. They are avid users of collaboration platforms likeSlack, RingCentral Glip, Snapchat, Instagram, Fuze,ChatBlazer, Workplace by Facebook, and Skype.If your organization still relies primarily on phone and email,you’ve missed the boat. Even if the majority of your customersaren’t millennials, it’s fair to say the majority of your customersare influenced by them. According to a Pew Research Centeranalysis of U.S. Census Bureau data, millennials are already thelargest generation in the workforce. Can you really afford towrite off their influence?I have business acquaintances who tell me their best customersare “an older demographic” who don’t text, won’t use a

collaboration platform, and don’t care about their userinterface. They tell me they won’t invest in mobile apps andbetter UIs because “young people” aren’t interested in buyingtheir products and services, so why bother?Complaints of that nature are self-destructive and self-fulfilling. Any organization that ignores the habits andpreferences of an entire generation of potential customers iswriting its own epitaph.In later chapters of this book, I write about the imperative forenabling collaboration and communication across the modernenterprise. A global business in the twenty-first century bearslittle resemblance to businesses of the past. Back in the day,everything was about command and control. Power andinfluence were highly concentrated. Information was shared ona strictly “need-to-know” basis.Today’s business climate favors decentralized and distributedoperations. Nowadays, we understand that information is anasset that grows in value when shared. There is nothing moreuseless than so-called “dark data,” which is a term for data thatis collected and never put to work.Moreover, there is a high probability that a significant portionof your workforce works remotely or outside of traditionalbusiness hours. If you’re not making it easy for them tocommunicate and exchange information, their value to theorganization is greatly reduced.

Brass Ring or Black Hole?After you’ve finished reading The Innovator’s Dilemma, takeup Geoffrey Moore’s book Zone to Win: Organizing toCompete in an Age of Disruption. I’m sure that most of youhave read Moore’s first book, Crossing the Chasm. By now, thebook’s basic message is well known. It feels familiar andcomfortable.Zone to Win will reawaken your sense of urgency. It will makeyou feel uncomfortable again, which is precisely how youshould feel if you want your digital transformation strategy tosucceed.Remember, the majority of transformation projects fail to meetexpectations. A landmark McKinsey survey revealed that only26% of respondents said their transformational efforts were“very or completely” successful. That failure rate represents “a$900 billion hole in enterprise strategy” according to a recentForbes post.My back-of-the-envelope explanation for why mosttransformations fail is simple: the failed projects focused onfuzzy long-term objectives when they should have focused onprecise short- and medium-term objectives. Their visionexceeded their grasp and strategy certainly exceeds their abilityto execute.

The irony is that short-term victories can lead to long-termadvantages, especially in turbulent markets and uncertaineconomic conditions. There’s a good reason for not losing aview of the larger strategic picture while also focusing on thenow; with any luck, it will sustain you long enough to beat backyour fiercest competitors.Digital transformation can be the brass ring that keeps youriding merrily on the carousel. Or it can be a black hole thatdrains your resources and ends your career.In my case, I’ve had the good fortune of transformationinitiatives helping my career. That’s because I approachedevery transformation with a sharp sense of trepidation and adeep reservoir of humility. I’m not embarrassed to admit whenI am skittish about a plan. In many instances, fear can be astrong motivator. Fear reminds us to proceed with care andcaution.I’ve found it beneficial to be a hands-on’ executive. I workclosely with our internal teams. I work directly with our vendorpartners and solution providers. I am familiar with thetechnologies that we develop and deploy in ourtransformational projects. And the buck always stops with me.The amazing success and longevity of Chuck Yeager, one of theworld’s greatest test pilots, is attributed partly to hissuperlative flying skills and partly to his hands-on mechanicalunderstanding of the aircraft he flew. Yeager took the time to

become familiar with the parts and pieces of the airplanes thatcarried him aloft.When something went wrong or didn’t feel quite right, Yeagerknew how to handle it. His deep technical knowledge and keenunderstanding of aviation systems were absolutelyfundamental to his achievements, and he is a role modelpersonally for me and for all of us who labor in the trenches ofdigital transformation.Mechanics of TransformationOne of the lessons we learn from Chuck Yeager’s career is theimportance of understanding the fundamental mechanics of asolution. Gaining this level of understanding requires getting inthe weeds and getting your hands dirty. You cannot manage atransformation from afar. You need to be right there, in closetouch with the teams who are making it happen.Additionally, you must be prepared to answer questions—dozens and perhaps hundreds of questions from internal andexternal stakeholders at every level who are affected by yourtransformation projects. Inevitably, people will ask, “Why arewe doing this? Why are we transforming these processes anddisrupting our traditional ways of operating? Why are wechanging?”

When these types of question arise, this book will help youprovide reasonable answers. It’s written for the purpose ofhelping you navigate through the multiple nuances oftransformation and cope effectively with the shocks andsurprises that will occur as you move forward toward your goal.Here’s something I learned from my experiences as an agent oftransformation: although change is natural, it doesn’t feelnatural. Some people are exhilarated by change, but mostpeople find it upsetting. As a leader, you need to accept thisfact. You have been chosen to lead a transformation initiativebecause you are the outlier – the person who actually enjoyschange! No matter what anyone tells you, they do not shareyour degree of enthusiasm. They are not optimistic. They arefearful.One of your primary responsibilities is managing their fearsand allaying their suspicions that your transformational effortwill make their lives more difficult or result in the eliminationof their jobs.These are not idle worries. They will prey on the minds of thepeople you lead, and you must address these concernsforthrightly and without equivocation. As Franklin DelanoRoosevelt famously said, “The only thing we have to fear is fearitself.”One of the most successful techniques used by NASA toprepare astronauts for the challenges of space missions is

familiarization through continual training and simulation.NASA prepares its astronauts so thoroughly for their missionsthat by the time they go into space, they’ve already practicedthe mission hundreds of time on Earth. NASA takes exquisitecare to make sure that its astronauts are ready for anything thatcould possibly happen.I urge you to adopt similar practices. Prepare your people fortransformation. Walk them slowly and carefully through thesteps. Encourage them to ask questions. Reward them foroffering ideas and suggestions for making the transformationprocess go more smoothly and efficiently.Whenever possible, turn your transformation projects intoteam activities so they feel more like games than work. I’m sureI don’t have to explain to you the importance of gamification. Ifthere’s an aspect of a transformation project that can bygamified, by all means, gamify it!Levels of TransformationReading Zone to Win reminded me that transformation canoccur at three different levels. At the first level, transformationfocuses on upgrading and streamlining foundationaltechnologies and infrastructure. At the second level,transformation improves the efficiency and throughput ofstandard business operations and processes. At the third level,

however, transformation helps the organization create andenable new business models.Some people might argue that newly minted organizations withno legacy infrastructure can safely ignore the first two levels oftransformation, but I would counter by arguing thatinfrastructure and operations will always require closeattention, even when they’re delivered as services in the cloud.Organizations encounter obstacles and frustrations at eachlevel of transformation. Ask any organization with poorfoundational infrastructure how their transformation is goingand you will receive feedback in no uncertain terms. However,the critical challenges fall into two broad categories: people andprocesses.Let’s tackle the “people challenge” first, since it invariablyposes the greatest danger to any transformation initiative.“People are afraid of change,” says Atle Skjekkeland, presidentof the Digital Value Institute. Appealing to their emotionsprobably won’t work, since their fears are likely to overwhelmthe “rational” explanations you offer to prove that change isnecessary.Fortunately, “you don’t need the majority of people to be onyour side, only a handful of key individuals who see the value inyour transformation project,” Skjekkeland says.

The idea of “key individuals” surfaced repeatedly in theinterviews I conducted when researching and writing this book.My own experience has taught me that transformation is not apopularity contest. You don’t require a majority to succeed—you need the support of top executives, key influencers, and ahand-picked team of “transformers” to carry out the project.“We put our best people on the project, and they’re committedfor the duration,” says Steven Sterin, a Fortune 100 CFO andsenior executive with decades of experience. “You want the bestpeople, working full-time on the project.”Processes are the next challenge. Installing new technology ispointless unless it’s accompanied by new processes enablingpeople to use it easily and effectively. Remember, the success orfailure of any transformation project is judged by its adoptionrate. People need methods that will allow them to get the mostout of the new tech investment.Human beings have instinctive abilities to judge value, andthey’ll know immediately if a transformational project hasmade their lives better or worse. If a new method makes theirlives easier, they’ll use it readily. If it makes their lives harder,they’ll find ways to avoid using it. The long tail of anytransformation is adoption by your target audience.It’s also important to remember that transformational projectshave costs. That might seem obvious, but it’s a simple truththat is often forgotten in the heat of battle. In Zone to Win,Moore writes primarily about disruption, yet his basic message

also applies to transformation. He notes that “to disruptsomeone else’s business, you have to add a net new line ofbusiness to your own portfolio.”Since neither your portfolio nor your budget is infinitelyexpandable, you are forced to make hard choices. Do you shiftresources from an existing line of business to fund a new line ofbusiness? How do you explain and rationalize that shift ofresources? Are you willing to sacrifice short-term returns infavor of long-term goals?Transformational leaders face the same questions and areforced to make similarly difficult choices. Let’s say you’replanning to move an application into the cloud andsignificantly reduce your budget. Moving infrastructure intothe cloud isn’t free; whichever cloud provider you choose—whether it’s AWS, Microsoft Azure, Google, IBM, or anothercompany—will charge you a substantial fee for the privilege ofusing their platforms.But that’s only the financial side of the picture. At some pointsoon after making your decision, you’ll need to have thedifficult conversation with your technology staff aboutstructural changes to support the new model.We talk and write frequently about people, process, andtechnology being the essential components of transformation. Iwould add a fourth component: executive leadership. You needmore than just technical acumen to lead a transformation. You

need courage, empathy, foresight, patience, self-discipline, andenthusiasm. Yes, those are “soft skills.” Over the long game,however, they are the critical skills you need to succeed as atransformational leader.“Having driven—and reacted to—many disruptive market shiftsin media in both startups and major media corporations, I havefound that true digital transformation only comes frompersistent and consistent leadership toward a new model ofpeople, product and business drivers. This type oftransformation is not a single big bang project,” says PhilWiser, chief technology officer of the CBS Corporation.On the Ground and in the TrenchesI couldn’t agree more with Mr. Wiser; my experience leads meto believe that digital transformation is only the starting pointfor an extended series of processes. Transformation is a longgame—that is indisputable.Transformation usually begins in the back office, yet its trueimpact is felt across the organization. A genuinely successfultransformation strategy will have ripple effects spreading farbeyond the traditional boundaries of your company. Even smallor highly specialized projects can have global effects.At a recent gathering of design thinkers for a company thatmakes jet engines, I was pleasantly surprised to find that

portions of the engine design were developed throughcrowdsourcing platforms. Design thinking has the potential tocreate entirely new dimensions of innovation. From myperspective, it’s a form of transformation.I foresee enormous transformational power in the emergingDARQ stack. DARQ is the acronym for distributed ledgertechnology (DLT), artificial intelligence (AI), extended reality(XR), and quantum computing (QC). Even if the acronym fadesfrom usage, the underlying technologies will be with us for aquite a while, transforming a wide variety of services inmultiple industries. DARQ will lead to a new generation ofservices in areas such as predictive maintenance, real-timepayments, just-in-time manufacturing, multi-modaltransportation, education, public safety, healthcare andbiotechnology.The Internet of Things (IoT) has similar transformationalpotential, especially in terms of enabling the rapiddevelopment of smart homes, smart schools, smart powergrids, smart roads, smart towns, smart cities, smart regions,and even smart nations.I conclude this chapter with a counterintuitive notionsuggested by my friend Tiger Tyagarajan, the visionary CEO ofGenpact. Tiger is an industry leader who pioneered a newglobal business model and transformed a division of GE(formerly GE Capital International Services) into Genpact, aremarkably successful global professional services firm focused

on delivering digital transformation for its clients. Here is hisobservation:When something is running well, that’s often the best timeto change it. It seems so counterintuitive, but the notion ofalways finding a better way to do something is at the coreof our cultural ethos.NET TAKEAWAYS1. Transformation is not optional; it’s an imperativedriven by factors and conditions beyond your control.Ultimately, transformation brings you to a better place,but the journey is difficult.2. Transformation is not a popularity contest. You don’trequire a majority to succeed—you need the support oftop executives, key influencers, and a hand-pickedteam of your best people to carry out the project.3. Leading a successful transformation requires morethan technical know-how; it requires a blend of “softskills,” including empathy, patience, and self-discipline.4. Transformation isn’t limited by traditional corporateboundaries; there are ripple effects that spread widelyacross multiple industries and economic sectors.

Chapter 2Focus and DisciplineExecutive Summary: In this chapter, we examine theimportance of a focused mindset, thorough training, clarity ofpurpose, and quick responses. We also introduce a helpfultechnique for demystifying leadership decisions and sharingpriorities.All of us, no matter who we are or where we come from, faceadversity in our lives. Adversity can be a great teacher.I was raised in a small fishing village on the outskirts ofMumbai, one of India’s largest and most populated cities. Ourhome was tiny, about 100 square feet. There were seven of us:my parents and grandmother, me, and three siblings. We hadno running water. Every morning at 4:30 a.m., before he wentto work, my father would bring four empty buckets to thecommunity tap, fill them with water, and bring them backhome. Three buckets were for washing, cleaning, cooking, andother daily chores. The fourth bucket was for drinking. Sincewe had no refrigerator, we poured our drinking water into anearthen pot. That’s how we kept it cool during the day.I’m sharing this story because it taught me several valuablelessons. I learned from an early age that resources are precious

and must be managed carefully. I learned that when you havelimited choices, you can devise workarounds and alternativesthat will serve your purposes.I also learned that I did not wish to spend the rest of my life inpoverty. My father worked for a company that printed labels ontubes of toothpaste. As a child, I found the process of printingcolorful labels on shiny metal tubes absolutely fascinating. Byvillage standards, my father had a good job at a solid company.But I had a strong desire to explore opportunities beyond thevillage, to attend a different school or travel to another country—a goal that seemed so elusive at that young age and in thosesurroundings.I often say my first financial advisor was my grandmother.When I was seven, she took me to our local bank and openedan account in my name. She deposited 20 rupees, theequivalent of about 10 cents, into the account. Opening anaccount made me feel very special and I vividly remember theexhilarating feeling of walking into the “big” bank building withmany ceiling fans and glass counters. I didn’t realize that I wasat the beginning of a long journey that would eventually takeme far from home.In addition to being a wise financial counselor, mygrandmother was a great typist. She worked for our localchurch, typing up notes, sermons, and announcements. Shehad a Remington typewriter, a manual machine withmechanical keys and ribbon spools. She was fast and accurate—

80 words per minute, never a mistake. I remember her clackingaway at the keys, slamming the carriage return lever andfeeding fresh sheets of paper into the roller. I marveled at herskill and dexterity.But what I remember most was her discipline. She sat down ather typewriter and stayed there until she completed her task.That’s what really impressed me. She always finished what shestarted. Her focus was unshakeable.I didn’t know it at the time, but my grandmother was teachingme important lessons. Discipline and focus are essential forsuccess. Always finish what you start, whether you’re typing upa newsletter or deploying an enterprise technology platform.Nothing will kill your chances for success faster than quittingbefore the job is done. The subtle lesson from my grandmotherwas: don’t quit. Keep striving until you reach your goals.Brace for ImpactDiscipline and focus are key ingredients of success. But youalso need training, knowledge, and experience to make themost of your opportunities when they arise. In my case, thiswas especially true.In early 2009, I was promoted to my first global leadership roleas a CIO. It was during the depths of the Great Recession. Thestock market had already fallen precipitously and was still

heading down. The world was struggling and there was no lightat the end of the tunnel.I felt particularly beleaguered. There I was, in a new job at amultinational company where I was expected to oversee largeinvestments and implement major changes. Instead, thecollapse of the global economy had pulled the rug out fromunder me. Like many other people at that time, I was uncertainabout the future. Despite the turmoil around us, my superiorshad high hopes and great expectations. But how could I deliveron their expectations in a shrinking economy? From myperspective, the future looked grim.Then a miraculous event occurred. On January 15, 2009, USAirways Flight 1549 struck a flock of geese and lost power inboth engines shortly after takeoff from LaGuardia Airport inNew York City. Minutes after losing power, the plane toucheddown safely in the Hudson River. There were a few injuries, buteveryone on the plane survived. The emergency water landingwas hailed as the most successful ditching of an airplane inaviation history.So much has been written about the “Miracle on the Hudson”that I don’t feel it’s necessary to recount the details. Suffice it tosay the swift and effective responses of pilots Chesley “Sully”Sullenberger and Jeffrey Skiles turned a potential tragedy intoa galvanizing moment.

Unexpectedly, the world experienced a sudden jolt ofoptimism. It was like someone had turned on a light. In a flash,we saw that even our most our difficult problems weremanageable. We felt inspired and reinvigorated.As an aviation enthusiast, I wanted to know how Sully hadsaved the day. After watching the news reports on televisionand reading dozens of articles, I came to believe the miraclecould be encapsulated in three words spoken by Sully to hiscrew: “Brace for impact.”For the crew of Flight 1549, those three simple words lit thefuse. All their years of practice and training kicked into highgear. They knew exactly what they needed to do, and they didit. Moreover, Sully knew the crewmembers would perform theirduties, leaving him free to fly the aircraft to a safe landing inthe river.There are many lessons we can learn from Flight 1549. For me,the main takeaway is that you need a combination of personalskills and a well-trained team supporting you. When you’veproperly trained your team, they know their duties andresponsibilities. You don’t have to micromanage them. Youhave the freedom to focus on what lies ahead. That’s what trueleadership is all about. Leaders guide their teams and theirorganizations into the future.Like many people, I was moved and inspired by the safelanding of Flight 1549. I felt new confidence, and I resolved to

move ahead decisively with my plans for transforming andimproving our global operations. The rest, as they say, ishistory.Our mission was successful. Over the following years, webrought many new technologies into our portfolio anddeployed numerous systems. We executed our duties withtremendous focus, raised the bar with every small success,fulfilled our responsibilities, and created opportunities forgreater success down the road.During this period of time, I developed my own version of thematrix used by President Dwight Eisenhower and later adaptedby Dr Stephen Covey to prioritize decisions. The matrix isinvaluable to IT leaders for two critical reasons:1. It becomes a visual tool for prioritizing projects.2. It clarifies your intentions to the team.The first reason is largely self-explanatory. It’s almost alwayseasier to grasp complex plans when they are displayed visually.That’s a simple fact of human nature.The second reason is more complex. When you are leading adigital transformation, your intentions must be absolutelycrystal clear to everyone on the team. The people you’redepending on to get the job done must know what’s happeningand why. They need to know what’s on your mind. They need toknow where they fit in the larger picture.

The matrix is a useful tool for conveying your priorities at aglance. I’ve found that it’s the key to achieving alignment ofpurpose. All it takes is one quick look at the matrix to knowimmediately where you stand.Figure 2.1 Urgent vs. Important matrix.My version of the matrix is shown in Figure 2.1. Please take amoment to consider how it would apply in your situation.Now let’s drill down into the matrix and look at each of thequadrants. I use some variant of the matrix in all of mypresentations, and I find it resonates with audiences in everypart of the world.

In the example in the figure, the matrix is drawn from theCIO’s perspective. Different executive functions would havedifferent labels on the quadrants, but the basic structure of thematrix would be the same across the C-suite.In the top-right quadrant we have customer and client needs.In all but a few exceptional circumstances, those needs takepriority over everything else. Client engagement teams, withoversight from the CIO, handle activities in the top-rightquadrant.In the top-left quadrant we have the activities related tooperational excellence, such as managing operationaltechnology, networks, cloud computing, finance andaccounting. This quadrant is mainly the domain of operationsmanagers, and quite naturally, they will be happy to explain atlength why it is the most important of all the quadrants.Unquestionably, operational excellence is critical, but it rarelytakes priority over meeting customer needs.In the bottom-right quadrant we have activities related tostrategy development. This is mostly the domain of businessstrategists, but the CIO and other senior leaders will be closelyinvolved. This is where new opportunities are identified andnew techniques for business growth are developed.Finally, in the bottom-left quadrant we have incubation, whichin many ways is the most necessary of all the businessfunctions. But for practical purposes it takes a backseat to the

other quadrants. It would be easy to overlook or downplay theincubation function, but a good leader will make sure it gets theattention it needs. Incubation is where the next great ideascome from. It’s the domain of visionary thinking, continuousimprovement, invention, and innovation that will take theenterprise to the next level. That’s why you cannot ignore therole of incubation.Figure 2.2 Urgent vs. Important matrix with examples.Figure 2.2 is a version of the matrix with the activities of eachquadrant filled in. Remember, this is a hypothetical/genericmatrix. Every organization’s matrix will look slightly different.But the purpose of the matrix remains unchanged, no matter

where it’s applied. Think of it as your North Star, a fixed pointin the sky guiding your journey.The matrix is a useful tool for setting priorities and allocatingresources. But I also see it as a technique for demystifying andclarifying the department’s duties and responsibilities. Itengenders a sense of discipline and makes it easier for yourteam to focus on what’s truly important. The matrix should beincorporated into training processes so the team can respondeffectively and without hesitation when problems oremergencies occur.Hopefully, you won’t ever have to say, “Brace for impact.” But ifyou do find yourself in a perilous situation, you’ll want yourteam to perform like Sully’s crew—quickly and flawlessly.

NET TAKEAWAYS1. Success requires a combination of excellent personalskills and a well-trained team supporting you.2. Use a visual tool such as the urgent/important matrixto clarify and demystify your goals and intentions.3. When your team is properly trained and motivated,you don’t have to micromanage them. You have thefreedom to focus on the path forward. That’s what trueleadership is all about—looking ahead and seeking thenext challenge.

Chapter 3Idea IncubationExecutive Summary: In this chapter, we look at the granulardetails of an incubation process and outline the steps of apractical framework for innovation in the modern enterprise.It is natural for high-performing organizations to focus onoperational excellence. If you can’t manage the basics, no onewill take you seriously.At the same time, maintaining the status quo is never enough.We don’t wake up in the morning and say, “Today, I want to doexactly what I did yesterday.” As social human beings, we knowvariety is the spice of life. We don’t want the same old thing; welong for the excitement of new frontiers and fresh challenges.In today’s hypercompetitive and continually evolving markets,innovation is essential for success. Innovation is more than afrill or a luxury; it’s absolutely imperative. Consumers andusers expect to see new products and services unveiled atfrequent intervals. When they don’t see innovation, theysuspect something is wrong.But here’s the hard truth: when you’re running at full-speedand firing on all cylinders, you don’t have time to be innovative.

Your first and primary concern is getting the job done asquickly and as effectively as possible. That’s the way modernindustry works—your pay is based on your performance andyour performance is typically judged by operationalparameters.Superstars such as Beyoncé, the singer-songwriter-performer,and Jony Ive, the former chief design officer of Apple, arecompensated largely on the basis of their innate creativity.Most of us, however, are paid according to how well weperform our jobs. While the focus on performance is totallyunderstandable from a purely operational perspective, itcreates serious challenges for companies that want to beinnovative.Overcoming the Natural Inclination toAvoid RiskIt is also natural for organizations to strive relentlessly forgreater efficiency and higher productivity, even when it meanssacrificing creativity and originality. In many organizations, thefear of failure outweighs the desire for success. Corporationsare intrinsically risk averse; it goes with the territory.Innovation, however, requires taking risks. Being innovativemeans exploring new ground, going where no one has gonebefore, pushing the envelope, and leaping into the unknown.

“Innovation is like parenting,” says Nikhil Jhingan, a serialinnovator who has developed many new products andsolutions. “A new idea is like a child,” he says. “To the outsideworld, the child might not seem particularly useful. But theparents of the child see its potential. They nurture and protectthe child. With their help, the child blossoms into a magnificenthuman being, accomplishes wonderful things, and changes theworld.”Like children, no two ideas are exactly alike; each must betreated differently. As a result, there is no ironclad procedurefor innovating and no single path to perfection. Each idearequires a unique approach.For example, devising a solution to address a commonlyrecognized problem can be handled by a committee becausethere’s a strong likelihood that everyone is seeking the sameresult. Even if you don’t know exactly what the solution willlook like, there is already agreement over its purpose.However, developing a truly visionary solution to address ahighly complex problem will probably require a strong internalchampion to clear a path and protect the idea in its nascentstages. “When an idea is really visionary, you need anempowered champion at a high level of the organization tomake it happen,” Jhingan says.In any case, innovation rarely proceeds in a straight line. “It’smore of a rollercoaster,” he says. “There are ups and downs. It

can be scary and unnerving. For every success, you experiencemany failures.”You Can’t Just Wing ItBecause there is an inherent conflict between the day-to-dayoperational goals of the organization and the need forinnovation, formal processes are necessary to make certain thatinnovation is encouraged, cultivated, nurtured, and protected.When I speak to smaller groups at professional conferences, Ioften conduct a nonscientific poll by asking members of theaudience to raise their hands if their organizations have formalinnovation processes. At a typical conference, very few peopleraise their hands. I often follow up by asking if they believe thatinnovation processes can be formalized or structured. Again,only a few respond affirmatively.The lack of affirmative responses goes a long way towardexplaining why so many companies struggle with innovation.From my point of view, there are no legitimate reasons for notdeveloping and implementing processes for supporting andpromoting continuous innovation.It is myopic to assume that you cannot put frameworks,guardrails, and guidelines around creativity. Processes arenecessary, even when you’re thinking creatively, because they

don’t affect the idea itself but provide a method to convert theidea into a product or service.For example, the incubator process we developed has becomefundamental to our ability to innovate continuously. Ourincubator methodology is both rigorous and flexible.Why are rigor and flexibility both important? Rigor isnecessary to keep the process on track, moving forward andgenerating practical solutions at a steady pace. Flexibility isrequired to accommodate sudden or unexpected shifts(internally or externally) demanding quick responses. Since theoverarching goal is driving and enabling innovation, theprocesses cannot be overly fixed or rigid—they must beadjustable and adaptable.Inside the IncubatorLet’s take a look at how the incubation process works. This isn’tsomething that was developed overnight—it required years ofexperimentation and many mistakes before we got it right.We knew from the start that our mission would be developingproducts and services that would make a substantive differenceto the enterprise. In addition to being effective and impactful,the timing had to be right. We weren’t looking for pie in thesky; we focused on creating solutions with tangible and timelybenefits. The solutions we created also needed to be easily and

readily scalable, since our firm operated in 168 locationsaround the world. Additionally, we knew that if a solutionproved successful and was adopted widely, we would need toprovide versions in at least seven different languages.Initially, we held two working sessions per year. Each meetinglasted two days. We invited eight to twelve technology leaderswith global or regional responsibilities. Sometimes we invitedmarketing leaders to join the conversation. We had an agendaand predefined topics to cover, based on our perceptions ofwhat kinds of innovation the company would need in the near-term future.We also had three simple rules for the meetings:1. Disconnect from operational world.2. Come with ideas and be ready to speak up.3. All ideas, big and small, are welcome.We purposely created a very fast-paced environment, using awhiteboard to capture ideas as they flowed. Maintaining a highlevel of intensity was important for two reasons. The firstreason was that most of the attendees had just flown in fromdifferent time zones and invariably many were experiencing jetlag. So we had to keep them focused and energized!The second reason was engagement—we discovered thatsetting a quick tempo with rapid-fire dialogue would keep usinvolved and engaged in the process. We strove to keep the

conversations lively, stimulating, and exciting. We wantedeveryone’s synapses firing continously!We also set expectations. We welcomed outlandish ideas—aslong as they were relevant to our business goals and offered thepotential for creating efficiencies or competitive advantages inour markets. In other words, we weren’t looking formoonshots. The ideas had to solve problems that were specificto our business.Even with those guardrails in place, we still had many raucousdebates and constructive arguments. To an outsider, the firstmorning session would have seemed chaotic. There would beopen challenges and counterchallenges before we started tostreamline the debate. Eventually, we would agree on two orthree ideas worth pursuing. Then in the afternoon session, wewould settle down and focus on turning at least one of thoseideas into a practical solution.Any ideas that survived the first-morning session became partof our incubator portfolio. The portfolio served as an “ideabank” we could dip into at any time. Over the years, the ideabank has proven extremely useful, providing us with a virtuallyinexhaustible supply of “seed ideas” we could bring to fruitionwhen the timing was right.The second day was dedicated to moving quickly from ideationto creation. This is when we shifted from right-brain thinkingto left-brain thinking. We allowed our “inner engineers” to

emerge. We worked together as a closely knit team to devise asolution that was viable, sustainable, and scalable.We pressed ahead briskly, racing against our self-imposed 5p.m. deadline. Our breaks were short and the caffeine and pizzawas plentiful. Our diet wasn’t ideal, but our minds were fullyengaged on solving the problem at hand.Over time, the incubator sessions became popular hackathons.Being selected to attend a session was considered a privilege.For a while, we held them on a quarterly basis beforeexpanding to regional centers as well.Most important, however, is that we succeeded in developingand implementing a process for generating a steady stream offresh ideas and new solutions that helped the company achieveits business objectives.The QRate TemplateOur incubation process is supportive and nurturing. Itencourages ideation in a collaborative environment. We wantour teams to know their ideas are both valuable and valued.That said, I would never describe our incubation process aswarm and fuzzy. Projects are not allowed to drag on adinfinitum; there are boundaries and timelines. No proposals

are sacrosanct; each idea must sink or swim based on its ownmerit.There are limits to how much you can brainstorm before youneed to begin testing your assumptions. Setting a cadence,establishing momentum, and generating observable outcomesare critical. Realizing the need for structure, we created atemplate with discrete steps and distinct phases. We call it theQRate Model, and it outlines a process for rating the queue ofideas in our incubator. Figure 3.1 is a diagram of the full model.Now let’s break it down into its component parts and see how itworks in practice.The model incorporates three basic phases:1. Create2. Validate3. BuildEach phase has two subphases:1. Create1. Ideate2. Test concept2. Validate

1. Pilot2. Validate resultsFigure 3.1 The QRate Model.3. Build1. Market viability2. ProductionEach subphase has two or more action steps:IdeateBusiness needTarget audience

Scope of issueTest ConceptViability of productFeedback from sampling target audiencePilotSkills and team assessmentSmall-scale build based on assessmentPivot if necessaryValidate ResultsTest product viability in limited markets andaudiencesTechnological readiness for mainstream useAudit controls if requiredMarket ViabilityConditions and readiness for market adoptionData privacy

Accessibility and performanceLanguage requirementsProductionTraining and support mechanismRedundancyGeographical hosting locationsSuccess measurement criteriaWhen you’re leading or guiding an incubator process, it’simportant to remember that you always have at least twoaudiences.Strategic audience: C-level, board, and senior executivesAnalytic audience: Directors, managers, and developersYou will need to communicate differently with each of thesetwo audiences, since each has its own interests and priorities.The strategic audience doesn’t necessarily need to hear all thedetails, but it needs to see the big picture and understand theoverall financial impact of your project. Its buy-in is essentialfor a variety of reasons, including financial support and dealingwith potential obstacles that could slow down or derail theproject.

The analytic audience, which includes users, needs to know thedetails, since they are the key to adoption once the solution isrolled out. Without their buy-in, it would be hard to achieve theadoption rates necessary for a successful deployment.Figure 3.2 Actions by audience segmentation.Figure 3.2 shows a closer view of audience differentiationsubprocess.The template also includes a “Hypercare” stage to manage thesolution after it’s released (Figure 3.3). Since the ultimategauge of success is adoption, it’s imperative to maintain a closewatch on products after they’re rolled out and to respondquickly when usage issues arise.We’ve used the QRate template to incubate and develop dozensof new solutions over the years. Although every projectpresents its own unique problems and challenges, the templatehas proven flexible enough to handle a wide range of ideas.Having a standard process really makes a difference, and itcontributes meaningfully to our ability as a company toinnovate rapidly and continuously.

The process also serves as a baseline, enabling us to contrastand compare projects over time. Following the template hasbecome a discipline, and it’s taught us many valuable lessons.

Figure 3.3 Managing adoption rates through better issueresolution.

Here are five critical lessons we learned from our incubationprocess:1. Strive for simplicity. The most successful solutions areusually the simplest and most straightforward.2. Test, test, test. And make sure to conduct your tests withreal people, not just with scripts or bots.3. Seek feedback from as many sources as possible. Objective,unemotional feedback is unadulterated rocket fuel for yourinitiative.4. Include project management experts in the process from itsearliest stages. Do not fear the project management office(PMO); work closely with the PMO and leverage itsstrengths and knowledge as you progress through the phasesof the incubation process.5. Make absolutely certain you have a user experience (UX)expert involved at the inception of any softwaredevelopment process. Always remember that adoption is themetric of success; if users don’t see the value in a solution,they won’t use it.Lessons from the FieldThe incubation process wasn’t theoretical—we used it togenerate many practical and usable solutions. Two successfulsolutions that spring to mind are Brandwave and Express. Hereare brief descriptions of each.

Brandwave was a solution for generating deeper levels ofcustomer engagement and learning more about whatcustomers wanted from a brand. We began developing it in theearly 2000s, relying on available technology and systems.Basically, Brandwave enabled customers to snap photos of adsthey saw on billboards or buses, send the photos to a database,and in return, receive coupons for the products in the ads.For example, let’s say you were the parent of newborn infantand you saw an ad for diapers on a passing bus. You would takea photo of the ad with your phone and send it to us in a textmessage. We would then arrange for the ad’s sponsor toincentivize you with a discount coupon.Nowadays, that might not seem like a big deal. But at the time,the cameras in mobile phones had low resolution and therewere relatively few databases capable of handling the type ofdata we needed to collect, store, and analyze to create value forthe sponsor.Nevertheless, we incubated and developed a usable solution. Bymisfortune, another company had been developing a similarsolution and beat us to the patent office. If not for that stroke ofbad luck, I am convinced that Brandwave would have become aglobal standard for raising levels of customer engagement.Express was born from our need to move very large digital filesfor advertising campaigns around the globe, quickly and

efficiently. There were multiple drivers and reasons for creatingExpress, ranging from cost savings to client satisfaction.On the cost side, we were spending millions annually to shipphysical versions of the files by next-day air. We were certainthat it would be much less expensive to send the files digitally,and our assumption was proven correct.There were also problems with shipping highly time-sensitivematerials by air. In many instances, “next-day” delivery cantake three or four days, since shipping is highly dependent ontime zones, weather, and other circumstances beyond yourcontrol. If a package misses its connection, it can sit in anairport until the next scheduled flight.When time-sensitive materials are late, clients becomeunhappy and dissatisfied. Competition in the business isintense, and you always have to meet the client’s deadlines.So we were highly motivated to create a practical digitalalternative that would lower overhead costs and keep ourclients happy. In this case, we realized that we didn’t have theresources or expertise to develop a solution internally. So wepartnered with Accellion, a company with deep experience indeveloping tools for sharing and collaboration. That’s when Imet Nikhil Jhingan, who was Accellion’s co-founder and chieftechnology officer.

Working closely with the Accellion team, we created a robustsolution that met our technical needs, sharply reducedshipping costs, and improved relationships with our clientsaround the world.The path to success, however, was bumpy and filled withunexpected challenges. We quickly discovered that the qualityof Internet service varied greatly as you moved from one regionof the world to another. In some markets, we had to developand deploy additional hardware to make the system workproperly. We also had to create versions of the solution inseven languages. In addition to technical challenges, we raninto cultural obstacles.Eventually, we overcame the challenges and launched Express—only to encounter another unintended consequence. Expressbecame popular more quickly than we had expected, and soonwe had more users than we could accommodate. Initially, westruggled to keep up with usage.After a slow start, the adoption rate was exponential within sixmonths of the launch, which made us both proud and anxious.Fortunately, we were prepared to scale the solution, and wekept up with the high levels of demand.The experience taught us an extremely important lesson: Youcan never just walk away from a new solution after launchingit. You are responsible for the success of a solution even afteryou’ve deployed it. Like the original ideas from the incubator,

the completed solutions you launch are indeed still very muchlike children—they require attention and hand-holding.NET TAKEAWAYS1. Continuous innovation requires formal processes; youcannot simply leave innovation to happenstance, orassume that it will occur naturally withoutencouragement and support.2. Make sure to include the project management office(PMO) and user experience (UX) specialists in yourincubation/innovation processes. Their participation isessential for creating solutions people will use.3. Adoption is the key metric of success. Be prepared tomanage problems and issues after a new solution isdeployed; expect the unexpected and be ready to dealwith unanticipated challenges.

Chapter 4Operational ExcellenceExecutive Summary: In this chapter, we look at thefundamental relationship between operational excellence andcustomer satisfaction. We also introduce a three-tier model fordeveloping solutions and services.Operational Excellence and customer satisfaction are stronglyrelated. Yet many organizations do not perceive the directconnection between the two. Instead, they treat customersatisfaction as an afterthought, something bolted on at the lastminute.The unvarnished truth, however, is that customer satisfactionis built on a solid foundation of operational Excellence. Yousimply cannot have the former without the latter.In today’s hypercompetitive markets, customer satisfaction isessential to long-term success. If you cannot deliver customersatisfaction, your days are numbered. This simple dictumapplies to all organizations, whether they are large or small,global or local.Even if you’re running your business from a garage or a sparebedroom, your customers encompass a wide range of people

and groups. In addition to external customers, you haveemployees, contractors, partners, suppliers, and other thirdparties. Somehow, you must figure out strategies and practicesto keep all of them happy.In a socially connected world, bad news travels withextraordinary speed. Your mistakes will stick to you like glue;make enough mistakes and your reputation may sufferirreparable damage.Learning from DataThe strategic link between operational Excellence andcustomer satisfaction seems obvious, but I became aware of theconnection early in my career almost accidentally while I wasmanaging a project to unify our help desks.Here’s the story: in one of my first global roles, we beganconsolidating our help desks into a single support center. Theconsolidation was a major undertaking since we had help desksoperating in a variety of countries.As we unified the help desks and incorporated theirapplications and data into a central infrastructure, we observedpatterns emerging. Let me take a step back and statecategorically that I’m not the first executive to notice that helpdesk logs contain a lot of useful information. But mostorganizations don’t have rigorous processes for capturing and

analyzing help desk information. If processes are in place, theyare often performed informally or haphazardly.We decided to do it scientifically. Within a short span of time,we began reaping the benefits of our extra efforts. For example,we quickly observed that an enormous portion of calls to oursupport center involved telecom issues. When you’re operatinga global business with offices and clients all over the world,good communications aren’t a luxury—they are absolutelyessential. We also had another factor to consider: creativebusinesses don’t work on a regular schedule so we had toconsider a 24/7 operation in any given major city around theworld.If a fabulous idea for a new video campaign springs into yourmind at 3 a.m., you need a reliable way to share the idea—potentially with visuals and music— with your team ASAP,wherever they are and no matter what time it is. That’s how acreative business operates—the usual rules of “office hours” donot apply when you have a “Eureka” moment.Moreover, we were a business based on significant deadlines.The branding and marketing campaigns we create areexquisitely perishable. If they arrive late, they are worthless.The first lesson you learn in creative business, as with mostmission-critical businesses, is never miss your deadlines!The data we gathered from our support center showedunequivocally that we faced a challenge of truly global

proportions. To put it bluntly, many of our offices lacked themeans for communicating information and exchanging datawith the speed and reliability necessary to compete effectivelyin their markets.Additionally, the cost of making calls or transmitting data whiletraveling was enormous. Remember, this was before the dayswhen everyone had a mobile device. Back then, cellular servicein many parts of the world was very expensive and spotty, atbest. As one traveling executive said to me, “My hotel roomcosts less than what it costs for me to call my team in NewYork.”The support center data also pointed to a root cause. In manyparts of the world, we were hamstrung by substandardtelephone and Internet services. It quickly became apparentthat we would have to devise our own solution to the problem.Using the data from our support center, we made the businesscase for building our own virtual private network (VPN) toensure our ability to communicate with each other and withour clients. A VPN works like a secure tunnel between devices;when you have a VPN, you don’t have to rely on local telephonenetworks to make phone calls or exchange data. And becauseyour communications are encrypted, you don’t have to worryabout unauthorized people listening in on your calls or stealingyour data.

At the time we did this, the idea of a non-telecom companygoing ahead and building a VPN seemed far-fetched. But thedata showed that we genuinely needed a solution to ourcommunications problem, and a VPN was the best choice. Sowith the investment approval and good faith of seniormanagement in our capabilities, we built one of the earlycorporate VPNs over the public Internet.We launched our VPN in 2004, and carefully measured theresults of our work, comparing the initial state with the currentstate. We were pleased, of course, to discover that calls to thesupport center about telecom issues dropped by more than50%. Switching to a VPN eliminated 65,000 help desk tickets.That alone would have been cause for celebration.The next finding, however, had a direct business impact. Thecost of travel communications plunged by 70%. The savingsfrom the initiative more than covered the cost of building theVPN and proved that there is rarely any return without aninvestment.But here’s the kicker: the VPN also allowed us to communicatemore effectively with our clients and with the media outletsthat published the work we created. The improved level ofcommunication became a strategic competitive advantage forour company, enabling us to operate on a truly global networkthat our clients expected. It also helped us with fundamentalsof disaster recovery. Many years after we had forgotten aboutthe initiative, I was pleasantly surprised to hear that during

hurricane Sandy that hit the U.S. East Coast, primarytechnology operations centers were successfully migrated tosecondary centers in Germany in two hours, and over thenetwork we built a decade earlier. The best part was to hearthis from a client who said that a major European brandcampaign was unaffected by the storm, even though it wasdeveloped in the United States and had to be transferred toSpain due to the weather crisis.I love this story because it shows how a relatively simple effortto solve an operational problem at a very basic level can emergeas a strategic competitive advantage providing tangible benefitsacross the whole enterprise and its partner ecosystem.The experience also taught me a valuable lesson andfundamentally changed the way I looked at the relationshipbetween operational Excellence and customer satisfaction. It’seasy to say that operational Excellence is a prerequisite forcustomer satisfaction. In reality, the relationship is a bit morecomplicated.In other words, it’s not a direct line. There are three levels ortiers in the relationship, and they must be approached in theproper order. You have to start at the bottom tier, which is thefoundational technology. Then you work your way up to thesolution, which is the second tier.The third and topmost tier is the service you provide. That’swhere the rubber hits the road. Great service is the key to

customer satisfaction, and you cannot fake great service. Ourtraveling executives didn’t begin using the VPN becausesomeone from headquarters sent them an email telling them touse it—they began using the VPN because it worked far betterand was more cost effective than hotel services at the time.We didn’t solve the problem by starting at the top—we began atthe bottom, at the foundational tier. And to be completelyhonest, the problem we solved was not the problem we set outto solve. Sometimes that’s just the way innovation works.Figure 4.1 is a very high level simplified three-tier model wedeveloped for ensuring customer satisfaction. A quick glance atthe model explains why enterprise-wide digital transformationcannot be purely top-down strategy. Unless you understand thefoundational aspects of a problem, you cannot solve it with anydegree of certainty. Maybe you will get lucky and find asolution, but chances are that you will become lost in a maze ofcomplexity that leads to little progress on the CEO’s changeagenda.

Figure 4.1 Bottom-up approach to service quality.Earning Trust and BuildingConfidenceWorking through the telecommunications problem also gave usthe confidence and experience to tackle other foundationalproblems as they arose. Here’s another example: one of ourclients wasn’t comfortable with the way we hosted its data ondifferent parts of our network. The client insisted that we keepits data in one secure location and gave us one month to figureout a solution.Building on the experience and knowledge we had accumulatedwhile creating the VPN, we devised a plan to build our ownprivate cloud for the client’s data. This was back in 2005, yearsbefore private clouds became commonplace. In fact, we didn’teven call our new project a cloud—we called it our “centralinfrastructure services co-location.”

We built the capability and deployed it successfully. The clientwas happy, and we had a new arrow in our quiver. Wemeasured the results and discovered that our cloud model wasmore secure and easier to maintain than some of our existingsystems. As a result, we moved several of our overseas marketsonto one centralized service, and saved substantially onoperating costs by eliminating infrastructure spending in thosemarkets.As you can see, we weren’t afraid to take a do-it-yourselfapproach in many instances. That said, I am notrecommending a DIY approach for each and every project. Youshould still decide whether to “build or buy” on a case-by-casebasis. In the examples I mentioned, we benefitted from doing itourselves because many of the now common technologies werenonexistent or nascent—we gained knowledge, experience, andconfidence that proved invaluable over time. Additionally, weearned respect and trust.Our internally developed projects also instilled a level offearlessness that made it easier for us to move ahead quicklywhile others might hesitate. Many of the projects we’veundertaken involve taking risks. No matter how many timesyou hear people talking about embracing failure, nobody likesto fail. Time and money are lost; sometimes reputations aredamaged.There’s also the chance that if a project succeeds, it will makesome technical jobs redundant or obsolete. I’m proud to say

that our team never allowed those fears to stand in our way.Once we made the decision to move forward on a project, weacted as a unit, pushing ahead until we achieved our objectives.Response Time vs. Resolution TimeMany companies judge the quality of their customer serviceoperations by measuring how quickly they respond tocomplaints and close tickets. But that’s a bad way to measurethe quality of customer service and it can easily lead to trouble.Any decent help desk can be trained to answer calls on the half-ring. Fast response times can be misleading, however. The timeit takes to respond to a problem is not the same as the time ittakes to resolve a problem. Answering a call and resolving acaller’s problem are not equivalent. In fact, they are verydifferent activities. The wider the gap between the two, themore your reputation for customer service will suffer.I had a painful learning experience with this phenomenonseveral years ago. I was visiting one of our offices in SouthAmerica, and the CEO there was in the midst of pitching amajor engagement to a large beverage company. While I wasthere, the office lost its network connection. The office managercalled the support center. A ticket was opened and fairly soonthe reason for the lost connection was discovered. A serviceteam set to work on fixing the problem and the support center

closed the primary ticket and transferred the issue to adifferent department.Hours passed and the office still had no access to the network.The CEO knew I was in the building and he asked for an urgentmeeting. He closed the door and asked me testily why theconnection hadn’t been restored.I called the support center and was told the problem had beenidentified, and that a fix was underway with a different team.What the support center did not say, however, was thatrestoring the lost connection required a DNS (domain nameserver) reset. If you understand networking, you know thatresetting a DNS can take hours or days in some cases. If you’rethe CEO, however, all you know is the support center said theproblem had been resolved.That unhappy incident taught me a highly valuable lesson:never confuse response time with resolution time. Sometimesthe resolution follows the response swiftly. When it does not,however, you must be prepared to explain the cause for delay.Better still, reexamine how you reward the people working inyour support center. You have to do more than simply rewardthem for picking up the phone, listening to a customer, andclosing a ticket. You need to reward them for resolvingproblems and following up to make sure the customer issatisfied with the resolution.

I included this story in the chapter because it underscores therelationship between operational Excellence and customersatisfaction. In this case, the foundational problem was thesystem of incentives that rewarded people for closing tickets.The solution was reviewing and revamping the incentives. Thenet result was improved customer satisfaction within thecompany, because the support center shifted its focus fromoffering quick responses to providing thorough resolutions.NET TAKEAWAYS1. Customer satisfaction depends on operationalExcellence; operational excellence is a prerequisite forcustomer satisfaction.2. Since customer satisfaction is an imperative in asocially connected world, the relationship betweenoperations and customer service is strategic, nottactical.3. Make sure that incentives are aligned to achievecustomer satisfaction as an outcome.

Chapter 5Customer-Driven ChangeExecutive Summary: Understanding the needs of yourcustomers, whether they are internal or external to yourorganization, is absolutely critical to the success of anytransformational strategy. It’s imperative to remember thatpeople will always be more important to the organization thantechnologies.It took about six months for Alan Turing to crack the Enigmacode during World War II. In the twentieth century he usedelectromechanical technology and arguably made one of thebiggest contributions to the Allies winning the war. Fast-forward 80 years and it takes three to five years to complete atypical digital transformation. Why, despite all of ouradvantages and technological prowess, does it take us such along time to achieve lasting change?There are many stories about amazing people who overcamegreat odds in brief spans of time while under enormous stress.One of the reasons I chose this example is because it revolvesaround code breaking. Another reason, of course, is that Turingis widely acknowledged as a true pioneer of modern computing.

As technology leaders and executives, we often find ourselvesin circumstances that are similar to those encountered byTuring. Time is short, resources are scarce, and the pressure todeliver results can feel overwhelming. We can be inspired byTuring, and we can also learn valuable lessons. Turing and histeam had a clear task. That enabled them to set priorities andto follow through with precision at all levels of their endeavor.So, what’s gone wrong today? Forward-thinking companiestransform to stay ahead of the curve and the needs of theircustomers but most transformations occur in response toexternal stimuli. Reasons for change range from threats to theexisting business model to competitive environment changes,globalization, and disruptive technologies causing automationof the industry, but in almost all cases transformation is areflection of changing customer demands. The importance ofunderstanding the needs of our customers—no matter if thosecustomers are internal or external—is paramount in the successof a transformation agenda. Understanding customer need isthe single most urgent and most important starting point fordriving strategy, setting priorities, and elevating operationalperformance.Customer journey mapping can help establish the true vision ofhow a company wants to position itself to service the needs of acustomer. Some journey mapping outcomes could lead to thecreation of new lines of business, labor arbitrage, or even thetransformation of existing lines of business; whatever theoutcome, the bottom line is managing transformational

complexity that can make or break the future of anorganization.Digital AlchemyThis digital evolution has steadily matured and led to thecreation of online marketplaces, social platforms, and peer-review communities. It has led to the creation of supply chains,automation, and collaboration opportunities without borders.These developments have led to volumes of data gleaned fromevery customer touchpoint and used in everything frommarketing to business decision-making. Collecting data instructured and unstructured forms to provide manageableinformation landscapes is a complex task, usually invisible andextremely technical.This is where data science is indispensable. Quite frankly, ifyour organization does not embrace data science, I see littlehope for long-term survivability or success.We’ve all heard the term “boiling a frog,” which refers to animaginary frog placed in a pot of cold water. I’ve never reallyfound evidence to the facts of this experiment but it makes for agood analogy in transformation. The experiment states that ifthe water is gradually heated to the boiling point, the frogdoesn’t realize the danger until it’s too late.

From my perspective, organizations that are unwilling todisrupt themselves are like the frog in the pot—they realize thedanger too late.For practical examples of this phenomenon, just look into yourwallet and then look at the apps on your smartphone. Almosteverything you cherish in your wallet also exists in digital formon your smartphone. Your credit and debit cards, businesscontacts, membership cards, airline tickets, and even your cash—they’re all converged on your phone, along with a webbrowser, GPS, calculator, camera, stopwatch, and dozens ofother useful apps.I use the term “digital alchemists” to describe organizationsthat understand and take advantage of this convergence. Here’san example of digital alchemy from an unlikely source: theUnited States Postal Service (USPS).The USPS delivered 30 billion fewer pieces of mail in 2018 ascompared to nine years prior. The ten-year trend shows asteady decrease in volume year over year and if not for newerpartnerships and digital innovation, the USPS would not beable to show the $2.6 billion in increased revenue in 2018.Today, the USPS prides itself on continuous innovation. Forexample, the USPS is conducting a pilot for self-driving trucksacross state lines. This kind of experimentation seems a far cryfrom the early days of delivering mail by horseback, but it

reflects the organization’s earliest days, when the idea ofnational postal service was considered truly revolutionary.Customer need also drives innovation in the retail industry,which is under margin pressures and often day trading forcustomers’ attention online. Although early digitaltransformation efforts focused on supply chain optimization,the industry is now throwing its considerable influence intoelevating and perfecting customer experience.I would go so far as to argue that the industry’s fixation onimproving the customer experience has forced suppliers toprovide higher quality goods and services, due primarily to theexistence of online customer reviews.Personally, I don’t know anyone today who does not look atonline customer reviews before buying a product or service.This effect is not limited to consumer goods; B2B technologycompanies such as Adobe have innovated aggressively to raisethe bar, creating end-to-end experiences that are satisfying tousers at every link of the value chain.Smart companies also know they must provide excellent post-sales experiences, since unpleasant or unsatisfactory post-salesexperiences can also generate negative reviews.Automated Customer Services

When you call customer service these days, your initial contactmay be with a chatbot or other form of automation. Chatbotscan be a blessing or a curse, depending on how well theyperform. Companies that devote the time and resources todeploying the best possible automation will reap the rewards;companies that try to skirt costs or rush their automationprocesses will struggle.It’s important to remember that we’re still at a stage in whichcustomer service is a blend of automated and humaninteractions. Again, the companies that take the time andspend the money to develop intelligent processes for escalatingissues from chatbots to human agents will gain competitiveadvantages over the companies that take a slapdash approach.Most of us will always remember a poor experience with acustomer service center and we’ll do almost anything to avoidusing products or services from companies with poor customerservice operations. However, we will happily spend our timeand money with companies that treat us well when we haveissues or questions. On a recent call with American Express, Iwas informed—to my pleasant surprise—that an electronicgadget that I had bought and accidentally damaged wascovered by a warranty that I didn’t even know existed.Imagine my delight at discovering that American Expresswould refund the cost of the repair. To my mind, this is trulyimpressive customer service that makes me a loyal customer. Icannot say the same when trying to resolve a billing issue on

one of my home services. Having been a customer for 11 years Iwas still transferred three times and lost 45 minutes on a callthat did not resolve the issue. Needless to say the outcome ofthat call wasn’t good for the service provider. We’ve all hadthese experiences and make “stay or go” decisions based onthese experiences.Smart organizations leverage digital platforms and improvecustomer service at all touchpoints, before and after the initialsale. But the future is constantly unfolding, with innovativeproducts and services introduced continually. Today, virtuallyevery new offering has the potential to compete in a globalmarket.A new digital environment is unfolding right before our eyes.Small, inexpensive sensors allow us to monitor anything fromanywhere. With this preemptive model, a global equipmentcompany can track the performance of its tractors on farms inMexico, and issue warnings on which parts are most likely tofail, enabling farmers to fix their machines before they break.In our homes, smart thermostats change the temperature whenthey detect the presence of humans (or pets) and smartdoorbells alert us when there is suspicious activity going on inthe neighborhood.We are now experiencing a tidal wave of disruption that is bothlarger and more transformative than we could have imagined.

Basic Principles of TransformationDigital transformation always starts with a well-groundedstrategy. Yet it also requires a real understanding of three basicCs:1. Change Management2. Communication3. Organizational CultureCHANGE MANAGEMENTTransformational journeys are almost always difficult, for thesimple reason that people do not like change. Over time, mostpeople will adapt to change. But in the short term, change isfrightening because it challenges the status quo. Although weenjoy complaining about our daily routines, we becomecomfortable with our routines because they make our liveseasier. That’s just the way it is. Always remember that whenyou ask people to change, you are asking them to make theirlives more difficult for a period of time. There’s just no wayaround this simple fact.This is where many leaders and executives fail. Unless you’vebeen through a transformation journey yourself, it is verydifficult to understand what people are going through whenthey confront change.

Digital transformations are always about more than justtechnology. In most transformations, overcoming thetechnology challenge is the easy part!The really hard part of digital transformation is changing thehearts and minds of everyone who will be affected by thetransformation. Changing hearts and minds is the primaryoverarching challenge. If you don’t get that part right, thetransformation will fail—even if the technology works perfectly.COMMUNICATIONAll change is ultimately personal. Anyone can change a table oforganization on slideware. Changing the organization itselfrequires a deep set of interpersonal skills, beginning withempathy and the ability to communicate.A good communications strategy straddles a fine line betweensaying too much and saying too little. You don’t want tooverwhelm people with more information than they need. Butyou don’t want to keep them in the dark. The last thing youneed during a transformation project is the emergence of arumor mill that spreads false impressions, fuels confusion, andratchets up anxiety levels.I’ve found it’s better to err on the side of too much information,but you need to be careful. Always remember that most peopledon’t care about the technology itself—they care about how thetechnology will impact them.

That means you need to frame your communications in termsthat people can relate to easily and understand at a glance. Oneemail is not enough; ten emails are too many. Ask and answerthe all-important question for the affected community: “What’sin it for me?”I recommend testing your communications strategy on smallfocus groups. If there’s one thing I’ve learned over my career asan executive, it’s that in a time of stress and upheaval, a goodfocus group can be your best friend. If you don’t know how toset up a focus group, ask one of your colleagues in marketing toassist or get professional support. It’s easier than you think,and an excellent investment.I recently spoke with a friend who is a top executive at a largeglobal consulting firm. She reminded me that one of the firm’sstrategic goals is making sure that all employees are “digitallyproficient” to the degree that they can handle virtually anyclient task assigned to them with contextual familiarity andminimum stress.Stating and repeating this goal essentially puts managers onthe alert, because they know they will be held responsible iftheir employees don’t have the skills required for minimumdigital proficiency as described by the firm. As a result,managers make sure their employees receive the additionaltraining they often require to perform effectively.

It would be easy to say, “The company should do a better job ofscreening applicants and making absolutely certain they haveall the skills required to function in a digital workplace,” but inthe real world, it’s extremely difficult to assess someone’sdigital skills with any precision.From my perspective, the firm’s strategic decision tocommunicate its intent clearly and then cascade theresponsibility on managers to make sure employees areproperly trained is the right approach.CULTUREAsk a friend or colleague why they quit their last job and theyprobably won’t say it was because of long hours or money. Themost likely reason people leave jobs is because of poormanagers or company culture. If there’s something wrong witha company’s culture, it will have a difficult time retaining toptalent at every level of the organization.For me, culture is virtually synonymous with motivation. I haveworked on three continents and I have had many managers.Here is what I have discovered: when you have a goodmanager, you can get through the worst day and the deepestcrisis. Somehow, you survive—not because of your own skilland talent, but because you know that someone in the chain ofcommand understands your predicament and is watching yourback.

Companies and organizations with great cultures attract greatmanagers, and great managers tend to stay at companies withgreat cultures. That might not sound very scientific, but it istrue.Know ThyselfAdapting to the changing needs of customers requiresadjusting to new ways of working. Assuming that yourorganization will voluntarily jump into a radical change issimply a misguided belief.As mentioned previously, change is difficult; planning andforethought are requisites. Self-knowledge should be the firststep of any transformation. With the idea of making yourplanning easier, here are four types of corporate cultures.Which one best describes your organization?1. Reactive: Simply responding to a business stimulus thathas already impacted an industry is not necessarily a badthing; however, if an organization is constantly on the backfoot, the chances of growth are certainly less than stellar.Reactive organizations don’t retain great talent and find ithard to create a motivated workforce. Investments usuallyare the minimum required to catch up with the rest ofindustry. Large-scale transformations usually fail at thesekinds of organizations.

2. Adaptive: Some organizations are great at adapting to thechanges in their industry. They stay current without toomuch fuss and usually have an optimistic outlook toinvestment. They tend to be risk averse but are willing totake calculated investment risks. These organizations tendto handle transformation on an even keel but only if neededto sustain their survival.3. Dynamic: Leaders in these organizations set the high barand are focused on discovering big opportunities for growth.They create an atmosphere of innovation and are not afraidto take risks. They attract top talent, treat their employeeswell, and usually have happy shareholders. Theseorganizations tend to be agile in their transformationjourneys and achieve good results quickly.4. Visionary: Leaders at visionary organizations go above andbeyond. Instead of focusing on the doable, they strive forinnovation and disruption. They are comfortable withtransformation and perceive it as a net positive. Theiremployees tend to have heightened states of digitalawareness and thrive in an atmosphere of creativity andcontinuous reinvention.Real-World Examples and WarStoriesI recollect joining a new team working for a CTO who had big,bold, and inspiring ideas. The team behind him, however, was

focused on extremely operational tasks. While the CTO set hissights on the future, his team worried about deadlines,resources, budgets, and the viability of the new technologiesthat fascinated the CTO.The CTO spent a year on the job but made little real progress.Then a set of external business factors hit the organizationhard. The CTO moved on, taking much of his team with him.The new CTO dove right in. Amid the chaos, he sawopportunity. “Never waste a crisis,” he said to me with a smile.He quickly established minimum baselines and staked out arazor-sharp vision for the company’s technology progress. Hisboldness and confidence were refreshing, despite thedifficulties we faced.The CTO’s vision was unmistakably clear and firmly groundedin reality. So we went about our business of delivering on thetargets he set. The bottom line: we hit our targets monthsahead of schedule and the outcomes were better than weexpected.Reflecting on this incident a few years later, I cannot help butthink that we would have been in a very different place andmuch better prepared for the changes in the market if the firstCTO had been a better executive. Although he acted like avisionary, he was in fact a reactive leader. His inability to stayahead of events was unfortunate, to say the least.

Here’s another true story: I recently had the pleasure ofspeaking with a former divisional CIO of a Fortune 50 companyin the industrial sector. She observed that driving change ishard, especially when people have been in their roles for a longtime.One of the challenges, she said, was that her team had beenaccustomed to working in a particular style. Their approach tosolving problems was slow and steady. It produced incrementalimprovements, but it didn’t create the kind of genuineadvantages required to compete successfully in fast-movingmarkets.She decided to shake up the staid culture of the organization bycreating a series of internal competitions. She also looked forpeople who didn’t quite fit the corporate mold—instead ofhiring people who seemed “perfect,” she hired rebels andiconoclasts.Those small changes had large effects. Soon, the companywanted more. The team became more proactive and lessconservative in its approach to solving problems anddeveloping new solutions. New employees were encouraged toshare their ideas more openly; it also created a level of healthycompetition and tension and the team soon became a rolemodel for the rest of the company.I conclude this chapter with a keen observation from my friend,Vineet Jain, the founder and CEO of Egnyte, a secure content

platform built specifically for business.“We are fundamentally in the knowledge industry and ourbiggest asset is our people,” Jain says. “Culture is notsomething you create. It is a collection of personalities,combined with a work ethic. It creates an environment thatpeople would like to be a part of. The core ethos of ourcompany is largely transparency: people knowing how thecompany is doing and what impact am I making or capable ofmaking. Transparency coupled with integrity is critical. Itallows an individual to succeed or fail without the fear ofintimidation.”

NET TAKEAWAYS1. Clear definitions of customer needs are essential forsuccessful transformation projects.2. Complexity in today’s digital environment is a given, soclarity of purpose is more important than ever.3. Change in behavior requires focusing strongly onhuman sentiment; the technology is important, butsecondary.4. Communications should be candid and relevant;include actionable steps whenever possible and keeppeople updated. Nobody likes being in the dark,especially during a transformation project.5. Understanding your organization’s culture will helpyou anticipate and manage challenges as they ariseduring transformational efforts.

Chapter 6Strategy vs. ExecutionExecutive Summary: In this chapter, we unveil the five-stepSPARQ process for planning and following through withstrategic digital transformations. We also look at the executionchallenges posed by matrix reporting structures in the moderndecentralized enterprise.In the movie Groundhog Day, Bill Murray’s character is forcedto repeat the same day over and over. At first, he feels that he iscursed and doomed. Gradually, however, he realizes that hisentrapment is a blessing in disguise, because it gives him thechance to become a far better person than he was before.This brings me to the first rule of strategy: the first 100 daysmust be repeated continuously. Moreover, you mustcontinuously communicate the goals and objectives of yourtransformation strategy. You must communicate at a steadycadence to assure the message is getting through. That’s theonly way to guarantee lasting change in the businessenvironment.As a simple exercise, ask yourself when you last heard yourorganization’s strategy stated or restated. If you haven’t heardit in a while, your organization is drawing its inferences and

deciphering the path for themselves. Lather, rinse, and repeat.Over and over. You simply cannot overstate the value of over-communicating.A Blend of Science and SentimentTransformational change requires a special kind of leadership.Essentially, transformational leadership is a blend of scienceand sentiment.Being a transformational leader isn’t easy, especially if youhaven’t done it before. As with any new role, you willexperience an early stage of apprehension, which is quitenatural. The initial stage will be followed by periods ofenthusiasm, excitement, discovery, ideation, creativity, andproductivity.The hardest aspect of this process is articulating the steps andimagining them as a path, rather than as a series of accidentalevents. This might sound obvious, but it’s amazing how easy itis to surrender control and “just let things happen.” Whenyou’re a transformational leader, simply allowing events tounfold is rarely a good practice.Without being heavy-handed, you will need a structured planlinking actionable steps with tangible results. You will need toprovide guidance and support. Your role in this process is notmicromanagement—it is strategic leadership. You are the

absolutely critical link between the C-suite and the operationalworld. In other words, your job is making transformationhappen.Setting StrategyI find it extremely helpful to have a strong team of capableleaders around the table who will debate the pros and cons ofideas that I think may be good, but can usually be improvedafter a good discussion. These debates and conversations arealso useful for separating operational concerns from strategy.After the strategy has been articulated, it is crucial to establishcheckpoints and test parameters to assess the viability of thestrategy within the proposed business environment. Again, it isimportant to make sure that operational concerns do notinfiltrate or dilute the strategy.Here is a five-step process I use to aid my planning. I call itSPARQ, which stands for Structure, Partnerships,Accountability, Resources, and Quality.STEP 1: STRUCTUREBefore embarking on a transformational strategy, we need todetermine whether we have the structure for achieving thegoals we’ve set for ourselves. While this may seem like a naturalenough starting point, it’s a step that’s often skipped over in the

rush to get going. This is a bit like jumping into a swimmingpool without first checking to see if it’s filled with water.By focusing on structure first, you will quickly discover whichdepartments simply aren’t ready. You might also discover thatsome of your offerings have become overly commoditized, yourteams are not in the right geographical locations to supportcustomer needs, reporting lines are too weak to withstand thestrain of new demand, and too many direct reports in a singleunit are putting undue stress on a good manager.Speaking one-on-one with managers is a good way to begin, butit doesn’t provide a deep insight into team dynamics.Sometimes social settings are more useful than formalmeetings for observing the true dynamics of a situation.Here’s an example: I had recently taken on a new global roleand was observing an afternoon workshop with a regionalteam. They knew I was there watching them, and naturallyenough, everyone was on their best behavior.At a dinner later that evening, I saw the team manager sittingapart from his group. He seemed isolated and distracted. Ididn’t think much of it at the time. But a few months later, aschallenges in the region surfaced, I realized that I had observedan early warning sign. There were communications issues,missed project deadlines, interoffice politicking, and a steadyloss of good talent.

It took a while to resolve the issues and to coach the manager.Eventually, we got the team back on track. I also learned avaluable lesson about the value and importance of teamdynamics.STEP 2: PARTNERSHIPSCompared to transformational efforts in prior years, today’stransformations require much less development by way ofsoftware or tools. Nowadays, most organizations lean towardthe integration and leverage of reliable ecosystems available inthe market.It’s important to remember that technology ecosystems arerarely designed and built in-house from the ground up. Theyare delivered and implemented by technology vendors andspecifically from industry vertical specialists within the vendororganizations.I’m talking here about presales, sales, engineering, customersupport, and other parts of the typical modern technologyvendor enterprise. All of those partners have their own goals,sales cycles, and personal aspirations for growth and success.They eventually become our professional partners; we callupon them regularly to support our own strategies.The right partnerships will mutually inspire teams on bothsides and deliver magical results in well-connected andsupported ecosystems. The right partners will also make you

the first port of call on pipeline innovation and potential jointcustomers.Poor partner relationships can seriously hamper and slowdown your efforts. Transformational leaders who don’t take thetime to develop good partner relationships soon findthemselves at the end of the line, waiting for enhancementsand improvements.Partnerships have to be managed and a good people structureallows for that to be a priority that helps both organizations. Asthe old adage goes, a rising tide lifts all boats.A personal example of relationship building for me happenedquite by accident. As part of a technology transformation, myteam had built an early partnership with a small technologyvendor in Silicon Valley. We seemed to be making decentheadway but not as quickly as I would have liked; then again,they were a small vendor at the time and we didn’t expect themto have the resources we desired.It so happened that their office in Germany were running aconference and a keynote speaker from the United Statesdropped out at the last minute. They reached out indesperation less than a week from the conference and weoffered to have someone there to help them out.Our presentation went off brilliantly, the audience was pleased,we gave our project lead some great exposure, and we saved

their conference agenda. That simple act changed therelationship. From that point on, we were first in line and ourprojects always received top priority.The simple gesture of helping a vendor build more trust and ledto better outcomes for both companies. Based on thatexperience, we went on to create many successful partnershipswith innovative companies around the world.STEP 3: ACCOUNTABILITYA digital transformation can be difficult even when you havethe right people on the team. But a transformation can turninto a nightmare when the lines of accountability are blurred orpoorly defined.Matrix reporting is a case in point. Although matrix reportingis not uncommon in many organizations, it can be disastrouswhen executing a transformation strategy. I stronglyrecommend avoiding matrix reporting if at all possible,especially when you’re tasked with leading a complicateddigital transformation effort.In the event that a matrix structure does exist in yourorganization, it is incumbent on the managers to jointly andclearly define and articulate the goals, stretch goals, andoutcomes for the individuals reporting to two or moremanagers. It’s not just important for the manager, it’s

important for everyone on the team to know where they standin terms of accountability and performance.In other words, people need to know precisely what they areexpected to accomplish and when they are expected toaccomplish it. Otherwise, everything falls apart.Over the course of my career, I’ve worked for largeorganizations with matrix reporting structures. More thanonce, I’ve reported to managers located on different continents.Needless to say, these situations have been far from ideal.However, you can’t remake the world to your own liking andsometimes you just need to go with the flow. Your level ofsuccess as a transformational leader will depend to a certaindegree on which type of matrix is in place at your organization.Daryl Conner has written and co-authored several excellentbooks (Managing at the Speed of Change, Leading at the Edgeof Chaos, and Project Change Management) on this generaltopic, and I find his model (summarized below) extremelyuseful when dealing with the inherent challenges of matrixorganizations. Essentially, Conner describes three scenarios ofaccountability:1. Direct Accountability. In a linear structure where thetransformation leader sits between the business sponsor andthe target group, this accountability model has the highest

chance of success. The target groups are usually directreports and the buck stops with the transformation leader.2. Lateral Accountability. In a triangulated structure wherethe transformation leader and the transformation targetgroup both report to the same business sponsor, theopportunity to succeed is much lower than in the firstscenario.3. Indirect Accountability. In a structure where thetransformation leader reports to one business sponsor andthe target group reports to another business sponsor, thereis an extremely limited chance of success, sinceaccountabilities will vary considerably.As you might suspect, the third scenario is the worst possiblematrix arrangement for enacting any kind of significanttransformation strategy. It will present formidable obstacles,making it difficult to establish common goals and justifyinvestments or spending reductions in areas you don’t directlyoversee.For more insight and far deeper dive into the challenges ofmatrix reporting, I recommend reading Conner’s excellentbooks.STEP 4: RESOURCESThe heart of a successful team is the quality of the people onthe team, the mix of good chemistry, and most definitely the

right talent and skill to get the job done. Too manyorganizations lean toward the talent they know, rather thanlook for a fresh set of eyes outside their teams.I too have been guilty of that. Early in my career, I overlookedmeaningful contributions from a talented group of peoplesimply because I didn’t know them very well. They haddeveloped a good solution and I didn’t see its value. It takes afew hard lessons like that to overcome your apprehension andrespect the diversity of your resource base.Transformation work is not always fun. Sometimes it calls forsignificant patience and it definitely calls for listening skills.This can fray the most battle-hardened teams. But constanttraining, new challenges, a moderately competitive workplace,and a happy atmosphere will keep your people motivated andeager to be around each other.STEP 5: QUALITYIn the final analysis, the success of your efforts depends on thequality of your execution. If the product or output from theteam is subpar or mediocre, nothing else matters.Every aspect of the service you deliver must be measuredagainst the most relevant parameters for your industry. In theservice industry, for example, we typically use customersatisfaction, ease of use, response time, and consistentavailability of services as our common metrics.

Whatever the service or product, you must ensure the rightparameters are considered at the appropriate time. Be awarethat the parameters will not be fixed or constant; they willevolve as the business environment around you changes.Sometimes the changes will come unexpectedly. For example,several years ago we convened a meeting to discuss future techinvestments with a client. In a stroke of bad luck, the Internetcarrier was experiencing intermittent outages. There wasnothing we could do but wait for the carrier to resolve theissues.Our senior account executives, however, were furious. I vividlyrecall one executive asking me to explain how we could possiblyexpect the client to discuss future technology investments withus when basic services were unstable. I understood hisfrustration, and quickly activated fallback plans for workingaround our primary carriers. We then actively measured ourability to recover from even minor disaster scenarios.

NET TAKEAWAYS1. Partnerships are essential; transformations are rarelyaccomplished without significant help and supportfrom outside parties. Your ability to create and nurturedurable partnerships will be a major determiningfactor as you move forward on a transformationaljourney.2. Beware of matrix reporting structures; make sure thatroles and responsibilities are clearly defined.3. People are the engines of successful transformation.Good leaders find the right levels of personalchemistry, training, talent, and motivation to keeptheir teams engaged and productive.4. Measurement criteria must be designed upfront and beiterative throughout the transformation.5. The transformation will only be judged on the qualityof the results it produces.

Chapter 7Hire Captains, Not Kings orQueensExecutive Summary: In previous chapters, we focusedmostly on processes and technologies. In this chapter, we lookat people—specifically, we share stories about finding andhiring people who thrive under pressure, enjoy pushing theenvelope, and aren’t fearful of the future and its uncertainties.It’s common for executives to complain about the difficulties ofhiring top talent for critical roles in the modern enterprise. Iagree completely—hiring talented people is difficult. But it’s notimpossible. David Ogilvy, often referred to as the Father ofAdvertising, the founder of Ogilvy & Mather, stated in nouncertain terms, “If each of us hires people who are smallerthan we are, we shall become a company of dwarfs. But if eachof us hires people who are bigger than we are, we shall becomea company of giants.”When parsing the difference between “difficult” and“impossible,” I invoke the motto of the U.S. Army Corps ofEngineers: “The difficult we do immediately. The impossibletakes a little longer.”

That said, I find it surprising when organizations erectunnecessary barriers that reduce the chances of hiring goodpeople. For a long period of time, you couldn’t get an interviewat a major tech company unless you had attended a top-tieruniversity and graduated with impeccable grades.Some of the big tech firms have relaxed those high standards,but there’s still a heavy dose of bias in the hiring process thateliminates many otherwise fine candidates. The CEO of aventure capital firm told me that he doesn’t mind hiring collegedropouts with passion to learn because education is not theonly sign of a motivated team member. I agree with thatphilosophy because I’ve learned that you can teach skills, butyou can’t teach passion.“Strategic discussions on digital transformation often focus onpeople, process, and technology; however,” there are twoelements about people that have to be addressed in order tomake that statement realistic,” says Sonia Fernandes, chieftalent officer at Mediacom AsiaPac. “First, people are an asset.They need to be nurtured, encouraged, trained, and managed.This cannot be an afterthought, it has to be a concerted effortbecause good talent begets good talent and vice versa.”The second element, she says, is managing employee feedbackin an agile way. Being able to act upon employee sentiment—positive or negative—instills confidence in management.

“At Mediacom, we’ve adopted Amber, an artificial intelligencetool that allows for real-time tracking of employee sentiment.This allows managers to respond rapidly to situations that needattention. Daily dashboards and alerts help us synthesize largevolumes of data and hone in on the most critical of issues withprecision,” Fernandes explains.This chapter offers four real-life stories illustrating situationsin which institutional or unconscious bias could have easilyderailed opportunities for growth and development. It alsodemonstrates the value and importance of “captains”—menand women with the courage, tenacity, and wisdom to serve asleaders and mentors.The Kid in the CornerIt’s the mid-1990s. Eleven team members of a large globalmedia company have been summoned to a meeting in India.The conference room is ornate, with dark wood paneling andfrosted glass windows to ensure privacy.The chairs of the team are arranged in a semicircle. A seniorcorporate executive with a grizzled beard stands inside thesemicircle, describing a new technology that he says willchange the world. He’s talking about the Internet.The team members shift uneasily in their seats. They’re outsidetheir comfort zone and not excited by what they’re hearing.

They don’t want to hear a lecture from an older person who ispotentially unfamiliar with modern technology that couldchange their lives. Some of the team members are visiblydistracted and avoiding eye contact. They’re hoping themeeting will end quickly.In the corner of the conference room, an intern sits, quietlytaking it all in. To the intern, the senior executive’s words arespellbinding. In his mind, the intern sees a future filled withlimitless opportunities.The senior executive unveils a simple plan that willdramatically increase response times to global marketingcampaigns and create enduring competitive advantages for thecompany and its clients. Essentially, he describes a globallyconnected digital economy with high-speed connectivity andthe rapid exchange of information over secure networks—hewas a decade ahead of his time and it was fascinating.He speaks with authority and confidence but not having thedesired impact on the team gathered there. Instead ofembracing the senior executive’s vision, they’re looking at theirwatches and probably thinking about deadlines they had tomeet.The senior executive winds down his talk. He looks over thegroup of executives. He tells them he is looking for a volunteer,someone to help him choose and deploy the right technologiesfor attaining his vision of a digital future.

The group sits silently in their chairs. Realizing that he wasn’tgoing to get any raised hands, he points to the intern sitting inthe corner. “You,” he says, “what do you think of all this?”The intern realizes that he’s on the spot. He hopes that no onenotices his poorly made trousers, inexpensive shoes, andmismatched socks. The intern agrees, with little choice, to helpthe older executive achieve his plan.I was the intern. The senior executive was R. Sridhar, head ofthe company’s direct marketing operations in India. “You aremy guy,” Sridhar told me and went on to be my mentor for thenext five years.Sridhar became my coach, trainer, mentor, and champion. Heshowed me first-hand how to be a captain—the person whomakes a genuine difference, finds the right talent, assembles agreat team, drives the process, and gets the job done properly.From Sridhar I learned how to manage people, run meetings,tell engaging stories, prioritize tasks, and keep projects ontrack. He included me in meetings with clients and seniormanagers. He brought me into regional projects andintroduced me to global executives.He showed me that captains provide inspiration, guidance,attention, and support. They work alongside their colleagues,not above them. He also taught me how to use nontraditionalmanagement methods such as yoga and meditation to manage

stress and maintain focus. Most importantly, he taught me toview my career as a journey, not as a destination.Years later, I asked him why he chose me that day. He smiledand said it wasn’t an accident. He had already done hisresearch and discovered that I was enthusiastic, energetic, andpassionate about my work.Sridhar wanted motivated people on his team. They didn’t haveto be the best or the brightest. He was willing to teach us theskills we needed to learn. We repaid his trust, and many of hisprotégés went on to become highly successful executives andbusiness leaders.We also continue learning from his example. When Sridharrecently asked me to critique an important new strategy he haddeveloped, I realized that I was experiencing “reversementoring,” which is when a senior executive seeks your adviceand counsel. It was a wonderful and humbling moment thattaught me another valuable lesson: captains learn and teachcontinuously. One day you are the teacher; the next day you arethe student. It’s a truly virtuous circle.The Man with Blue HairFast forward to 2006. I was now the company’s global directorof technology operations and we had been interviewingcandidates for a major network security role. We were looking

for someone with passion, curiosity, keen intelligence, andhands-on experience. Only a handful of applicants met ourstandards, and we were becoming anxious about our chancesfor hiring someone with the proper qualifications and the righttemperament.It was a beautiful fall day. My office was on the 15th floor of theWorldwide Plaza building in Manhattan. Looking out thenorth-facing window, I could see the sunlight reflecting off thenewly built Hearst Tower in the distance. A helicopter wasflying low over the Hudson River. Despite our anxiety, I wasfilled with optimism. We had narrowed the field and ournetwork operations director had identified the best candidatefor the job.It is my habit to interview the final candidates for every majorrole in my organization, and I was looking forward to theinterview. But when the network operations director walkedinto my office, he was frowning. Clearly, he was worried. Iasked him to share his concerns with me, and he told me thatall the preliminary interviews were done by phone, but whenthe candidate came in for the penultimate round, he wasconcerned that candidate might not “fit” the workenvironment. I told him that I would interview the candidateanyway.At 3 p.m., the candidate was ushered into my office. For thepurpose of this story, I’m calling him “Rob,” to protect hisidentity. Rob walked in and sat down in front of my desk. He

was wearing a hat, and I politely asked him to remove it whilewe spoke.He refused, politely. “I’ll leave it on if you don’t mind,” was hisverbatim response. I like to think of myself as an easygoingtype of person, but I wasn’t happy with that response.Nevertheless, I wanted to interview him. Every previousinterview with Rob had gone exceedingly well. The people onmy team were impressed with his capabilities and expertise.The hat, however, was irritating me. I wondered what he wastrying to hide. I became distracted thinking about the hat. Aftera couple of minutes, I told him flatly that if he didn’t take offhis hat, I would terminate the interview.Reluctantly, he removed his hat. I couldn’t help but smile. Hishair was bright blue above the hat line. I should explain at thispoint that I used to be a musician and had played in bandssince I was a teenager. Extravagantly dyed hair does not shockme. Blue is just another color.With the hat no longer an issue, we dove into a technicalconversation about network security. It didn’t take long for meto realize that Rob was incredibly well qualified. In fact, he wasthe perfect candidate. I was amazed to discover that he hadbuilt a small server farm in his basement, allowing him toexperiment and explore in his free time.

At one point in our conversation, we began drawing schematicson my whiteboard. He removed his jacket, revealing colorfultattoos on both arms. By then, however, I frankly didn’t carewhat he looked like. The job was his.Looking back on that day, I realize how easy it would have beenfor me to yield to my prejudices. I’m glad that my betterinstincts prevailed. Rob stayed with us for seven years andbecame the leader of our network operations team. Hisknowledge, enthusiasm, and energy made him a wonderfulcolleague and great role model. Today, Rob holds a leadershiprole at a major network solutions company in California.One of my mentors once told me that if you don’t have at leastone rebel on your team, you’re probably out of touch with thelatest developments in your field. I wouldn’t exactlycharacterize Rob as a rebel, but he certainly was a unique andhighly qualified individual who brought an unbiased outsider’sperspective to our group.The ReceptionistThis story takes place about ten years ago. Jonathan, a brilliantentrepreneur, had sold his startup to a large marketing firmbased in New York City. As part of the deal, Jonathan joinedthe firm and became part of its new digital business unit.

For a variety of reasons, the new unit was disbanded andJonathan went looking for something else to do within thefirm. He began pitching in wherever he could, and his talent forsuccessfully managing complex projects was quickly spotted bythe firm’s senior executives. Jonathan was promoted tomanaging director and given a broad portfolio ofresponsibilities.Once established in his new role, he discovered that many ofthe company’s support staff had not fully mastered the use ofbasic office software. Their lack of proficiency and inability tohandle simple requests slowed the pace of work and made itdifficult to meet deadlines.Jonathan knew that without a qualified support staff, he wouldbe overwhelmed with minor tasks and would be unable toperform his duties as a managing director.Then, on a particularly grueling afternoon, he noticed one ofthe receptionists leaving to take a break. Jonathan asked her ifshe had a minute to help him with a quick task, and sheimmediately agreed to pitch in. The receptionist’s name wasLiz. As it turned out, she had initially applied for a role inmarketing, but had been turned down. When she heard therewas an opening on the reception desk, she took the job.Liz was highly competent. She knew how all the office systemsworked and she had a keen appreciation of marketing strategy.But her skills and talent had been overlooked and she wasn’t

able to utilize her marketing talents while working on thereception desk.It didn’t take long for Jonathan to realize that Liz was preciselythe kind of assistant he needed. At his request, Liz wasimmediately transferred to his unit and she quickly became atrusted member of the team. Over the years that followed,Jonathan provided both the support and the challenges Lizneeded to achieve higher levels of success within theorganization. As time passed, she took on larger and morestrategic roles. Eventually, she became a managing directorwithin the company.Today, Liz is a globally respected and highly sought-afterbusiness consultant. She has also become a mentor and rolemodel. Her rise from receptionist to world-class executive istruly inspiring.Her career trajectory also highlights the critical role of captainsin the corporate ecosystem. Jonathan needed help and herecognized her value. He wasn’t afraid to walk into the humanresources office, explain the urgency of the situation, and insistthat Liz be assigned to his team ASAP. That’s how captainschange the world—when action is required, they do nothesitate. I’ve met and worked with both of these very successfulpeople in the course of my career and know exactly whatthey’re capable of.

Neha and RahulThis story returns us to the mid-1990s. Neha was a seniormanager at a large company in Bangalore. The company sheworked for was in the midst of shifting from manual to digitaloperations, and the pressure on Neha’s group was intense. As aresult of the constant pressure, turnover in the company wasquite high and good candidates were hard to find.Neha needed to recruit a new assistant, and she had laid downstringent requirements to ensure that all candidates had thetechnical skills necessary for succeeding in the company’s fast-paced environment.The company also had unwritten rules that made her hiringtask more difficult. Traditionally, assistants within thatcompany were women. Few men applied to become assistants,and on the occasions where they did apply, they were rarelyhired.When Neha reviewed the test scores of the applicants, thecandidate with the best skills was a young man named Rahul.Neha considered herself an open-minded person, but her initialmeeting with Rahul did not go well. She was concerned by hislack of social skills, his extremely quiet manner of speaking,and his obvious discomfort with Western clothing.But his test scores were impressive, and she decided to press onwith his candidacy. Rahul was soft-spoken, almost to the point

where Neha could not understand what he was saying. Theessays he had written for his application exam, however,revealed deep intellectual capabilities and superior writingskills.Neha asked Rahul to explain how he had become such a goodwriter. He told her that his father was an English teacher. At anearly age, Rahul had been encouraged to read and studygrammar. As a result, he had developed an extraordinarycommand of written prose.Neha decide to hire Rahul. Despite his shyness, he became theteam’s go-to guy for writing complex business cases. People inthe office would seek him out and ask him to correct andimprove their writing. He earned the respect and friendship ofhis colleagues, becoming a key player on his team.He also had a natural affinity for computers and he rapidlygrasped the importance of business analytics, developing skillsthat made him even more valuable over time.Soon after hiring Rahul, Neha left the company to start afamily. When she returned a few years later, she found thatRahul had been elevated to a role on the analytics team. Today,he supports the company’s wide-ranging analytics landscape,bringing consistency and rigor to complex processes.When I spoke recently with Neha, she told me the lesson shelearned from Rahul is not to judge a book by its cover. His

introversion and discomfort hid his inner strength andcompetence. Fortunately, Neha was able to see past thesuperficialities. She opened a career path for Rahul, and hesucceeded beyond everyone’s expectations.From my perspective, Neha is a true captain. She is someonewho can look deep into another person’s personality and seethe value there. Rahul wasn’t a rocket scientist or a rock star.But thanks largely to Neha, he was a great hire and he becamean exemplary team player in a highly demanding field.Looking back over the course of my career, it seems clear to menow that captains play critical roles in the success of theirorganizations. Captains play alongside their teams. They showup. They inspire. They win together, they lose together. Theyshare the glory, and they share the pain.Captains accept accountability for the job at hand. They hire orseek out the best people for their team, often people they canlearn from. They look after team members and make decisionsthat help the team move forward. They identify the areas thatneed improvement, providing encouragement and supportalong the way.They have an intuitive ability to seize the moment and takeswift action to achieve their goals. I know from first-handexperience that I would not have been on the wonderfuljourney I’ve had so far without the support and guidance of agreat captain. I’m certain that Rob, Liz, and Rahul have similar

feelings about the captains who played key roles in theirdevelopment and success.I’ll leave you with this question: Are you hiring captains, or areyou hiring kings and queens?NET TAKEAWAYS1. Tests and requirements are okay, but don’t narrow thefield of potential candidates by imposing strict rulesthat might eliminate people with critical skills.2. Look beneath the surface when you interviewcandidates. Make sure the people you hire are trulypassionate and committed to making a positivedifference in the organization.3. Take the time to coach, mentor, and support a varietyof people in your organization. Sometimes the mostvaluable players aren’t the rocket scientists or rockstars.4. Don’t be afraid of reverse mentoring. Even our leastexperienced employees can teach us valuable lessons.5. You can teach skills, but you can’t teach passion.

Chapter 8Integrated EcosystemsExecutive Summary: In this chapter, we dive deeply into thechallenges of real-world social collaboration in a globalenterprise. We also discuss the enduring fundamentalprinciples of collaboration and point to critical future trendsthat will aid your efforts.When people hear the term “digital transformation,” they tendto think of back-office processes such as inventory control,document management, invoice reconciliation, and payroll.Large organizations support thousands of back-officeprocesses. Almost all of those processes are important to theorganization in one way or another, even when they seemtedious and often bureaucratic.But digital transformation involves more than automating orstreamlining back-office operations; it involves the adoption ofmodern technologies that support every aspect of growth andefficiency within an organization. Over the course of my careerone pivotal element stands out in early stages of the journey; Ihave seen first-hand that social collaboration is a prerequisitefor digital transformation. Whether your organization is largeor small, this type of platform absolutely essential to thesuccess of any digital transformation strategy.

Without tackling the social collaboration piece first, yourtransformation efforts are likely to fail. Your plan might lookgood on paper, but it won’t work in the real world unless youfully and completely understand the motivations, desires,needs, and habits of your users. You must understand whatdrives adoption. Without that understanding, your investmentswill not yield the desired outcomes.It is astounding hear about companies spending vast sums ofmoney on digital transformation projects without taking thefirst critical step of making sure that people won’t reject thenew digital tools and systems that are part of thetransformation. If transformation were easy, we wouldn’tspend so much time talking, writing, and worrying about it.That said, we often spend too much time focused on thetechnology of transformation and not nearly enough timefocused on the people who will make it happen. A major aspectof digital transformation is changing the way people thinkabout their work.It’s critical to remember that people don’t like change. Ashuman beings, we prefer the tried and true. We like ourroutines and rituals. We prefer things that are familiar to usand we reject things that appear strange.After all, it is quite natural for people to be suspicious ofanything that is different and new. The aversion to novelty ishardwired into our human brains. It’s a form of bias, and we

need to be aware of it. Once we are aware of it, we can take theappropriate actions to overcome it.Making the Case for CollaborationFrom my perspective, social collaboration is both an enablerand an outcome of digital maturity. You need socialcollaboration to provide a strong foundation for yourtransformation strategy. After the transformation is underwayit will gain credibility and gather momentum through the use ofthis very platform.When a transformation is firmly established, it will provide asturdy platform for productive collaboration across theenterprise. That’s why I see collaboration as both an enablerand an outcome of digital transformation. In a properlyequipped digital enterprise, collaboration creates its ownvirtuous feedback loop, continuously reinforcing andenhancing the value of your transformation strategy.How does it accomplish this seemingly miraculous feat? Hereare some of the ways in which social collaboration acceleratesand reinforces digital transformation:Enabling the sharing and debating of ideas.Today, we work in cross-functional teams spread acrossmultiple geographies. Social collaboration tends toerase boundaries and remove obstacles that impede

workflow. It also makes it easier to share ideas that canlead to the development of new products and services.Collaboration is an essential part of lean and agileprocesses, allowing much faster cycles of prototyping,testing, refinement, and deployment.Finding specialized skills within theorganization. People are constantly and continuouslyupdating and broadening their range of skills. Lookingfor someone who is an expert in retail and speaks Thai?You can probably find someone in your company withthe combination of skills you need—if your companyhas a social collaboration platform.Managing through a crisis. Our world is a turbulentplace. A crisis can arise unexpectedly, anywhere on theglobe. When bad things happen, the social collaborationplatform becomes a place to communicate, reassembleteams, and respond effectively to the crisis.Tracking workflow. Whether you’re buildingprograms and projects for a client or for use within yourorganization, the collaboration platform offers aneffective way for tracking workflow and analytics in realtime, without having to wait for written or oral reports.Disseminating case studies, success stories,lessons learned, and best practices. Our successesand failures generate insight and information that canbe shared internally. We have much to learn from each

other, and the collaboration platform is a unifying forcefor sharing our knowledge and experience.Training new employees in standardprocedures. It’s hard to find your bearings in a neworganization. Even the best training for new hires rarelycovers all the bases. It’s especially important for newemployees to learn the SOPs—standard operatingprocedures. The collaboration platform can providebeneficial information quickly and effectively in aformat that’s informal and easily digestible for newhires.Achieving global/local balance. Every largeenterprise needs a unified strategy, but the componentsof the strategy should be customized for individualmarkets. That means making certain that information isavailable in Western and in non-Western languages(e.g. Mandarin, French, Arabic) and in local dialects(e.g. Brazilian Portuguese, Mexican Spanish), as well asin formats that are accessible across multiple types ofdevices and networks.The bullet points above represent only a fraction of the benefitsthat can be derived from a robust platform. In manycompanies, social collaboration has become the cornerstone ofeffective communications. It has moved from the fringe to thecenter of the modern enterprise.

Here’s a hypothetical scenario illustrating the value of anenterprise social collaboration platform: let’s say you work for amulti-sector technology vendor and you’re meeting with aclient. During the meeting, you uncover an opportunity to sellone of your company’s cloud services.This kind of situation occurs fairly often in the technologyspace. You’re having a high-level conversation and suddenly anopportunity arises that requires specific knowledge andexpertise.This is when a collaboration platform can prove invaluable tothe sales process. Immediately after the meeting, you click onyour collaboration app and start searching for an SME(subject-matter expert) in the area of cloud services thatsparked your client’s interest. Next, you will reach out to atechnical architect who can build a customized demo of thecloud solution that will address the client’s specific need. Youwill also bring a pricing expert onto the team.You will also alert your managers and keep them in the loop. Ifthe opportunity involves a significant amount of money, youalso will bring in an executive sponsor to meet with the client.Apply this scenario to any type of B2B business and all of thoseplayers can be assembled internally through the collaborationplatform. Additionally, the platform will be able to tell youwhich experts are available and where they are located.

Here’s another hypothetical scenario: a client in the MiddleEast alerts you to a potential production issue in a certainsystem. The collaboration platform will help you identify andbring in the best available resources, in the nearest location, todeal with the issue as quickly as possible.It’s not an exaggeration to state that social collaboration hasbecome essential to business everywhere. Collaboration is nolonger a luxury; it is now an absolute necessity. It is also a pathto leverage crowdsourcing opportunities.Without these capabilities, vital information is trapped in silosand loses much of its potential value. Unlike tangible assetssuch as a precious metal or stone, information gains valuewhen it is shared widely. That’s one of the strongest argumentsin favor of social collaboration: it increases the value of yourinformation.Don’t Make AssumptionsSome organizations have an unfortunate tendency to assumethat collaboration is a distinctly millennial trend. This is amistaken assumption.The urge to collaborate is a human characteristic. It’s deeplywoven into our DNA and it is a fundamental part of our lives associal beings. Humans have collaborated and worked together

for millions of years. If there’s a “secret sauce” that explains thesuccess of the human species, that sauce is collaboration.That’s why it’s important not to assume that collaboration issome kind of passing fad associated with a specificdemographic or age cohort. If you build your collaborationstrategy on an erroneous assumption, it will probably fail.When Life Gives You Lemons…I encountered a unique opportunity a few years ago. Acorporate intranet in production was past its heyday and wasn’tespecially popular. With the goal of attracting a larger base ofusers the senior management wanted to revamp the ageingplatform.Technically, the project began as an upgrade. As the projectprogressed, however, the team gathered data from a base ofpotential users and realized that we had an opportunity tocreate something truly special. Eventually, an upgrade wasdeemed useless and a different approach to collaboration wasrequired—one with the capabilities and strengths necessary tosupport a global enterprise. In effect, the new platformlaunched in 2014 was a sea change that brought us firmly andunequivocally into the social age.Before embarking on the project, however, my team partneredwith our corporate communications department to help us

develop a deeper and more granular understanding of ourcommunity of users. The partnership with our communicationsteam proved absolutely essential to the eventual success of ourglobal collaboration platform.The communications team surveyed company personnel inoffices all over the world, conducting in-depth interviews with120 people in all age groups and functional areas of theenterprise. Thanks to the survey, we had hard primary data onwhich to base our collaboration strategy going forward. Thesurvey also gave us the confidence to dismiss our earlierprejudices about who would be mostly likely to use—or not touse—a collaboration platform.Over time, we learned to define our social collaborationconsumers by looking at three factors:1. Geographical limitations of content distribution2. Ease of user generated content submission3. Ability to use personal tech within a secure environmentIt is important to note that none of the three factors haveanything to do with age or demography. Instead, they arecontextual. We could sort users into groups by asking ourselvessimple questions about their circumstances:Does their region have the infrastructure necessary toexchange high volumes of digital content?

Are their networks robust, secure, and available?Can authorized users (employees, consultants, businesspartners, etc.) access and interact easily with theplatform using their personal devices and technology?As you can see, the factors were objective and easy todetermine. They gave us a firm foundation on which to buildwhat became our internal communications platform.Through experimentation and testing, we refined andoptimized the platform, eventually rolling it out to a large baseof corporate users. Based on the insight collected from oursurvey, we divided users into three distinct communities:1. Global2. Regional3. LocalEveryone who logged on to the platform landed on the GlobalAnnouncements and News Page, a page dedicated to worldwidecommunications and geography-based news updates. Analgorithm we created looks up a user’s profile and populatesthe page with relevant information based on their location.Static navigation on the landing page enabled users to use asingle sign-on (SSO) for accessing a host of tools and resources,including external syndicated research available to the

organization, by using a federated system for sharinginformation from third-party sources.Communities of PracticeA mission-critical aspect of the solution was its ability toseparate groups of people into communities based ongeography, customer accounts, and specialized departmentsand interests. Security between groups was of paramountimportance.To accomplish our goals, we divided users into three macrocategories:Category 1: Global Community. This type ofcommunity could share everything with everyonewithin the company (excluding joint ventures (JVs) andaffiliates).Category 2: Limited Community. The names ofthese communities or interest groups are visible to allbut access to this type of community is predefined. Onecould request access based on need, but requests can bedenied based on confidentiality.Category 3: Hidden Communities. Thesecommunities are invisible to everyone by default.Unless a person specifically has access, he/she does not

know if this community exists. And the search enginelimits this access as well.Social and Collaboration ToolsEach business unit had the ability to configure their ownnavigation. This was based on a set of preconfigured guidelinesbut is driven by each independent business model. A givenbusiness unit had the ability to add in specific social tools asbest fit their method of operation.The social and collaboration tools available to each businessunit/group were established through interviews and fell in linewith most of the emerging industry platforms at the time andthe fundamentals still hold true today, depending on theindustry profile. They were as follows:Personal profile—edit and maintain current skills(required).Full form profile and skills search (required).Friend circle and personal wall for managing blog posts,reading lists, etc.Blogs/video blogs with content flagging capabilities.Wikis (how-tos).High-definition video training and archives.

Threaded discussions.Manage team communications and subscriptions.Chat and online presence.Event-based news scheduling.Live Twitter feeds.Virtual drive—shared drive integration withcollaborative editing.Digital publishing of PDFs and presentations sodocuments can be viewed online.Community calendars.Innovation TargetsWe felt we were breaking new ground and innovating inuncharted waters on many fronts as we progressed. But we hadto gravitate away from all norms in three key areas:1. Using social media appropriately within a professionalorganization. We were creating an advanced form ofcollaboration, taking full advantage of social behaviors tobenefit our business, yet social media benefits are muchharder to achieve and business benefits were much harder tomeasure in practical terms.2. The contradiction of using open source to solve anintellectual property challenge. Open source offers a broad

palette of capabilities, but it is very much like a blankcanvas. Every day was a learning experience.3. Collaborating with global resources to create globalcollaboration. Business requirements were gathered byspeaking with 120 end users globally; the technology wassourced from a company in Silicon Valley, California; thearchitecture was done out of New York and North Carolina;the alpha test users were out of the UK; the development,QA, and testing were done out of New York, São Paulo, andMumbai. Language integration and testing were done out ofGermany and China. Creative design was done out ofSingapore and implemented in New York.Key Success FactorsIt’s easy to get excited about the technology; it’s much harder toget users to adopt it and take advantage of what a system has tooffer. We worked with the business units that had the mostcomplex of all the requirements—from the alpha stage throughbeta, pilot, and launch phases.Each of these sets of requirements were driven by the businessCEO or senior-most leaders within the business units. Thisensured that the end product was front-office ready for a globalorganization.

Great Execution Eats Strategy forLunch!Great execution is a mantra we try to practice within our teamseach day, but this project set the bar even higher. After a shakystart, we scrapped the path of an upgrade to pursue a completereplacement of the system. This took some adjusting to interms of resources, planning, project management, design,testing, information architecture, and user experience.It took constant engagement with the business communities.Executing testing of even the alpha version across fourcontinents was a massive undertaking that required skill andexperience.Lessons Learned on ExecutionUnlike B2B applications, collaboration is more of a B2Csolution with a wide range of demographics accessing thesolution and many opinions on what works and what doesn’t.Our lesson was that all organizations on a transformationjourney will be measured by the quality of the execution, notthe shiny slideware at the ideation stages, and this effort wasno exception. Execution implies details, details, and moredetails: staying ahead of the issues as best as the team can,putting rigor into the quality governance process, testing andtesting again, having meeting agendas, having meetingoutcomes that are measurable, knowing what priorities meet

the business goals for the initiative and what is “nice to have.”This last part can be the death of a really good initiative. Tryingfor a perfect solution on Version 1.0 can work in some cases butis exponentially better if you operationalize it for a short periodof time and then attempt to improve it. Voltaire said it best:“The best is the enemy of the good.” And this holds true forscenarios like this.Dealing with an Informed andIntelligent AudienceFrom the start this was a business-driven model withtechnology playing the key role with specialized capabilitiesand researching viable options. Some of the most interestingchallenges out the gate were:The executive sponsorship team was extremely techsavvy and used to managing sophisticated onlinecollaboration.Needs were based on the various online legacycommunities that we had to make provisions for.Each business had diverse business models with lessthan 10% overlap across the six pilot groups.Another technology challenge was cost; the initialdiscussions on costs were during a recessionary periodwhen the market was in a rather precarious position

and we were looking to better manage technology costs.This caused us to settle on an open source technology,which had tremendous potential. However, everybusiness requirement had to be clearly articulated andanalyzed before the software came into play.Being a media company, design aspects were criticaland had to be approved by the CEO and chief creativeofficer, who spent most of their time traveling to clientsor our offices around the world.After months of interviews, requirements documentation andsign-off, systems analysis, front-end design and redesign,information architecture, disaster recovery planning, staging,application fine-tuning, and user acceptance testing we had aglobal social intranet. It was a 360-degree turnaround from thelegacy application it replaced.The difference in philosophy, functionality, behavior, andacceptance is so vastly removed from the older application thatthe brand name, too, had been changed to reflect it.Dealing with a KnowledgeableAudienceIn most cases rapid prototyping helps stakeholders define thefinal outcomes of these types of solutions, but what happenswhen your stakeholders are extremely well informed and know

exactly what they want? We encountered the latter, whichmade the challenge a little more daunting, as conversationsoften veered away from the business cases. Once we were ableto harness that energy by capturing the stakeholders’ needs, wewere able to direct the technology to deliver the desired results.For practical reference, here is how one use case played out.Global Research Use CaseOur company is in the business of brand building. Planningand research play major roles in the outcome of marketingplans and strategy around brand building for our clients andprospective clients.The corporate planning department is spread out across manycompany locations globally, with the head of planning based inNew York City. This team used traditional electroniccommunications within the group every day. Most of thecommunication was related to obtaining the right resource forthe right client or business pitch. Often it was validation ofresults by specialists in the network.The groups use vast amounts of research data and resources tocome up with the fine-tuned results they deliver, and almostevery department in the company uses them in some way. Thesheer volume of communication, time zone complexity, andsearches across these resources was an unsustainable process.

A briefing from the planning head in New York and theresearch lead in London clearly articulated the complexity ofthe global problem and the urgent need to find an all-encompassing system to address it.We arrived at the optimal solution after months of workingwith the team on an extremely bold agenda that included high-definition video streaming, online training, documentbrowsers, research material caches, case studies, referencematerial, suggested reading guides, global and local search,threaded discussion forums, and subsections such as globalstrategy.The planning community was among the first to expose theircapabilities, launching their strategy group from thecollaboration platform in live demos to our global offices. Thelaunch exceeded expectations and created a surge ofenthusiasm, with around 500 planners adopting the platformin over 200 sites worldwide.Here’s what the worldwide head of planning had to say: “Forthe first time we are able to share syndicated research acrossthe company. We can now allow hundreds of planners to createinquires and gather information from the various resourcesposted online. Overnight we have gone from a position whereinformation could only be accessed by a handful of people, tosharing information globally. Large research investmentscentrally can now be leveraged across all markets.”

More Lessons Learned: WhenBusiness Strategy Is the Only Driverof TransformationWe knew that technology was the answer to the problem, butcertainly was not the place to start. We discovered that whentech is used in response to the complex business problem, wederived the most effective value from it. We also learned thatSponsors of the project must really want to solve aproblem and not consider it a handoff to a CIO/CTO.Real feedback from potential customers of the platformrequires “real and unbiased” legwork.Unlike proprietary tools that provide guiderails andcase studies for business cases, open source software isa blank canvas and provides a plethora of options—thefinished product is as good as the vision established atthe start. This can be a blessing or a high-riskundertaking.From those lessons, we realized thatTechnology platforms for social collaboration havecome a long way in the five years since this program andone doesn’t have to build any of its components fromthe ground up anymore. However, the principles ofcollaboration remain the same while the tools change

with technology advancement. To name a few, tools likeSlack, Trello, Egnyte, Workplace by Facebook, and soon integrate seamlessly and also allow for federatedaccess across other proprietary platforms.The fundamentals on any social collaboration platformremain the same. Humans respond to the convenienceof consumer-based technology (with appropriate datasecurity) and these ready solutions achieve greattraction due to a natural familiarity, which requiressmaller changes in their behavior.In modern cloud-based environments, not only can anecosystem of services achieve the same results faster,but they can also help you rapidly adapt to changes inyour environment, by way of languages, scaling up ordown, providing different dimensions of access foracquisitions, audit services, fraud detection, and muchmore.Using Machine Learning to Solve theInformation Overload ChallengeWithin just a few years, collaboration platforms have improvedsignificantly, but the ones that are emerging as the “futurenormal” are the handful that leverage artificial intelligenceintegrated within the DNA of the organization.

While early innovation around collaboration assumed thatusers of these platforms would flock to it and generaterevolutionary ideas and content, we now have the problem inreverse: information overload. Medium- to large-sizedcompanies in particular have this problem in more acute formsthat are immediately apparent. “Search,” which once providedrapid answers to queries, is now seen as an inefficient modelthat provides more information than one can coherentlyassimilate.Consider this example. Even the most well-documented andreligiously followed business processes are nonlinear (this isespecially true for nonregulated industries). This implies thatexceptions are not solved by process alone but by tapping intothe wealth of knowledge collectively possessed by theorganization. But how does one approach the pockets ofintelligence in the age of data and information overload?Enter machine learning, a technique for teaching a system torecognize patterns of predictable behaviors.The company with which I ran an experiment had a simple, yetpowerful mechanism to manage business exceptions orcomplex queries. A simple illustration on the way it worked: auser posted a question to the general population or anindividual. If somebody answered it, they received a ratingrelated to keywords within that question. If they forwarded it toanother person in the network who they believed had the better

answer, that person was rated on whether they answered it orforwarded it on.The answer could then be rated by other users within thenetwork for things like accuracy, number of times the solutionwas successful for them, etc. Based on the number of positiveratings, the person who answered the question was ratedhigher, as related to keywords in the original question. Thesystem gradually sees a pattern forming and starts to sendqueries to the “experts” based on best match.Now consider the collaboration challenge in a multinationalconglomerate with multiple locations and a multilingual anddiverse workforce. The strategy and problem definition isexactly the same as a few years ago, but the approach needs tobe far more responsive. In this case, the self-learning AIplatform is effectively being trained by how the companyresponds to exceptions anyway, and over time, the “trained”system will begin to respond automatically as arecommendation engine. In this scenario, the knowledgesharing is integrated into the way the company behaves and is apowerful expression of AI.There will always be instances where patterns are not wellestablished and will not achieve the desired impact, which iswhy this is a low-risk solution whereby queries can still bedirected to the experts by traditional methods.

The outcome of the experiment showed that over 24,000queries were redirected to less than 5% of the experts in theorganization. This statistic was true of the originalcollaboration tool as well, where the ideation and content wasgenerated by around 5 to 7% of the organization, the keydifference being that efficiency was hindered due to the hugevolumes of information returned by search queries while thenewer method was far more effective and exceededexpectations and response times.The Future of CollaborationArtificial intelligence may stutter a little while making its wayinto mainstream adoption. Also, organizations may be slow torespond to new technology that is not yet fully established, oreven for the fear of the unknown. But in a low-risk use case likethe above experiment, taking the mundane tasks out of theequation and making the organization more efficient is a greatway to start.Another trend that is quickly emerging is that of visual search;Google AI, IBM Watson, and Microsoft AI among otherscontinue to make big strides in this area. A recentdemonstration of Cloud AI capabilities shows significantdevelopment in the areas of machine learning, enabling one tosearch for matching digital images in a browser within just afew seconds. This capability will add tremendous value tokeyless search (i.e. leveraging cameras, not keyboards).

Combined with augmented reality and high-speed 5G networksof the near future, these technology combinations can leveragethe fundamental principles of collaboration to achievelanguage-agnostic secure collaboration at scale without theperformance barriers of just a few years ago.This is the right direction for any industry that generatesvolumes of information that go untapped. It prevents re-creation, manages duplication, and expands your targetaudience while still ensuring governance to a centralizedbusiness strategy.

NET TAKEAWAYS1. Social collaboration is critical to the success of allmodern organizations, since it enables the organizationto leverage the talent, skills, knowledge, and experienceof large numbers of people working together in nearreal time.2. Developing and implementing social collaborationplatforms require special attention to consumers of theplatforms; they are unlike previous generations oflarge-scale software implementations such as ERP.3. A successful social collaboration platform will generate,collect, and distribute enormous volumes ofinformation. Harnessing this information will requirevarious forms of artificial intelligence and machinelearning.4. Modern configurable platforms can help achieve thiscapability without the complexity of internaldevelopment.

Chapter 9Digital Proficiency andInnovationExecutive Summary: Even though advanced technology hasbecome a commodity, organizations still need to develop themindset required for using technology wisely and effectively. Icall this mindset “digital proficiency,” and from my perspectiveit’s more essential to success than technical proficiency.The Apollo 11 spacecraft that took men to the Moon in 1969relied on a guidance computer that could handle eight jobs at atime. Today, an iPhone can theoretically process 6 billiontransactions per second.We’ve come a long way since the days of the Apollo program.Thanks to the spirit of human invention and Moore’s Law,amazing technologies have become commoditized andcommonplace. In our modern techno-savvy culture, virtuallyevery organization can craft a practical business solution withtechnologies that are readily available at a reasonable cost.In other words, technical proficiency has become a given. Whatis not a given, however, is digital proficiency. For most

organizations, the widespread lack of digital proficiencyremains a barrier to transformation.Why is this so? The answer is maddeningly simple: to achievetheir goals and objectives, organizations typically rely on theskills and knowledge of their employees. That makes sense,doesn’t it? After all, that’s the reason you hire people, so youcan leverage their skills and knowledge.But here’s the rub: the typical employee relies on skills andknowledge that he or she learned years ago in school. That’s theproblem! Unlike riding a bike or driving a car, digital skillsrequire continual upgrading. The need for continual learningand development is not some trivial matter. Ignoring the “skillstate” of your workforce can prove disastrous.Today, acquiring new digital skills almost always entails morethan merely learning how to use a new piece of software orsupervise new business processes. Many of the newer solutionsrequire users to adopt a new mindset and a new approach towork. Many newer solutions aren’t merely new—they aredisruptively new, requiring users to become familiar with anewer dictionary and new terminologies.Again, these aren’t trivial problems. And they are compoundedby vast differences in levels of preparedness and experienceacross the modern workforce. In today’s workplace, one sizedefinitely does not fit all. “For the first time in our history we

have four generations working side by side,” says Mitra Best,lead principal of strategic innovation and technology at PwC.Please take a moment to consider her observation. The idea ofa multigenerational workforce isn’t new, but I cannotremember a time when four generations of employees workedtogether. The impact of the multigenerational workplace ispowerful and undeniable.Yet most organizations are constantly operating in beta modewhen it comes to training. A handful of large corporations takelearning and development seriously, but midsize companies arestill way behind the curve. Small companies and startups oftenfocus on hiring people with great technical skills, but fail to hiredigitally proficient talent in critical areas such as sales,marketing, finance, and human resources.What’s the net effect? There are gross imbalances in levels ofproficiency, not just across companies, but across departmentsand teams as well. These imbalances can have direconsequences for transformational strategies in modernorganizations.How often have you heard technologists use the phrase “Buildit and they will come,” but invariably the platform investmentsfall short, or worse still, completely miss the desired objective.Even though technologists form an integral part of atransformation, the keen sense to research solutions withoutadequate definition of the business challenge is a very slippery

slope. While it is imperative to identify the business-orientedcomponents of any transformation prior to identifyingsupporting technologies, most programs repeatedly fall into thesame trap of not doing so with rigor. If you look at the SMARTtransformation approach shown in Figure 9.1, I’ve drawn up asimple method on how to approach this challenge by drawingon commonly used business practices to aid the journey.The acronym identifies the five steps that one can follow whileinterchanging the underpinning steps to suit the challenge.Consider it a prequel or a step in the journey leading to theactual transformation.Survey. The first step in the journey is defined toindicate inclusion of the various stakeholders. In mosttransformational cases there is already a method toachieve the business goals, so before disruptingestablished methods it is crucial to understand what isin place and if it does indeed need to be changed.Map. A simple process within an organization mayhave multiple stakeholders from commercial teams tosupply chain personnel in different geographies. I findthat visually mapping this process brings about thereality of how complex things really are under the hood.This can be one of the most time-consuming processesin the journey as you identify caveats and workarounds.

Figure 9.1 The SMART business and digital transformationmethod.Align. The mapping procedure will act as the basis foralignment with the multiple stakeholders; there is ahigh potential that this cycle of mapping and alignmentwill repeat itself a few times depending on thecomplexity of the challenge.Research. While technologists would have been at thetable throughout this process, this is the point in timewhen the definition of a solution, if technological, issought out through research or pulled from incubators,startups, etc. This is the deciding point as to whetherthe digital enablement will disrupt and truly transformthe process or deliver a mediocre outcome. This is also

the point where the change management would kick infor how a new process might impact the workforce, theP&L, departmental efficiency, a product’s time tomarket, a change in the quality of service, etc.Transform. Once this is fully established, thetransformation journey truly begins. The changemanagement and communication is formulated basedon the culture of the organization.No method will give you a straight-line answer to any businessproblem; it must be adapted for each situation. I’ve outlinedone of these very real situations after the adoption of theSMART process.Here Come the RobotsRobotics offers a good example of the disparities in knowledgethat are typical in the modern workplace. Robotics is amultidisciplinary field and there is no standard “robot.”Robotics includes physical robots, AI chatbots, autonomousdriving systems, and RPA, which is the abbreviation for roboticprocess automation. Despite the variety and diversity ofrobotics itself, the idea of robots inspires two unpleasantthoughts in the minds of many people:1. They are taking over the world.2. They are eliminating my job.

Most people don’t have a clue about what robotics can andcannot do. Why is that a problem? It’s a problem because thechances are very good that your next digital transformationproject will involve some degree of robotic process automation.Simply hearing the word “robotic” will sow seeds of fear andpanic among your workforce, making your role as agent oftransformational change even more difficult.From my perspective, the ability to talk about newertechnologies such as robotics is a critical aspect of digitalproficiency. In other words, digital proficiency isn’t just aboutknowledge and skill—it’s also about explaining why and howthings work in the modern workplace.The CEO of a digital marketing agency recently shared hisfrustration over the inability of a key team to explain the valueproposition of a new technology platform they had developedfor an important client.I found the conversation fascinating. At no point did the CEOmention any problems with the technology involved in theproject. The technology was great, he said. His sole issue wasthe team’s inability to articulate the technology’s valueproposition to the client.A Long and Winding Road

Business requirements and organizational needs drive digitaltransformation. And since every business and everyorganization is different, the term digital transformation hasno strict definition. It varies by industry and by company. Butthere are common threads that can be woven into a coherentstory. Recognizing these threads and weaving them together ispart of digital proficiency.A transformation leader recently told me a story thatunderscores this point. The leader’s company was experiencingpersistent problems with its customer invoicing processes.There were constant delays, inaccuracies, and complaints fromirate customers. Eventually, the problems were traced todeeper issues in a back-office function. Additional trainingdidn’t help, and there were no pragmatic solutions forreorganizing the back office.A deep analysis of the data indicated that about 70% of theback-office work was mostly computational and about 30% wascomplex enough to require human cognition to process. Thisseemed like a natural opportunity for deploying a simplerobotic processing automation solution.But the decision to use RPA was only the beginning of a longerjourney. The leader identified seven distinct stages in thejourney and outlined them for me:Stage 1: Outright Rejection. The back-office unitinitially rejected the idea of automation. Employees in

the unit pushed back hard, saying that automation wasa far-flung idea, not ready for primetime, untested, tootechnical, and would never pass an audit. Theycomplained that it would cost too much, would clashwith existing scripts and automation, and would notwork on older versions of their existing softwareplatform.Stage 2: Fearful Acceptance. Although the analysisindicated that 70% of the work was computational, theemployees thought the figure was inaccurate. They alsofeared for their jobs. The leader responded by assuringthem that they would be retrained and reallocated toanother department if their jobs were eliminated byautomation. Gradually, however, they accepted the ideathat automation was coming.Stage 3: Alignment of Processes. While the back-office unit had well-established processes which shouldhave made the transformation easier, the employeeshad made minor nonconforming changes over time. Asa result, the entire process had to be re-mapped andrealigned before it could be programmed into bots.Stage 4: Buy-In. The leader had expected that shewould get buy-in from the company’s technology group.But her expectations didn’t match up with reality. Thetechnology group wasn’t aligned with the businessstrategy and had its own plans for automating processesacross the company; the back-office RPA project was

not on its roadmap. It took months of negotiating withthe technology group to reach an accommodation thataddressed the back-office issues without underminingthe company’s long-range strategies.Stage 5: Audit Engagement. Before the test launch,the company’s internal audit team had to review thenaming convention used by the unit to designate theRPA bots. This seemed like a simple step until a team ofexternal auditors deemed the process a “materialchange” of the organization’s end-to-end workflow. Ittook weeks to assure the auditors that humans were stillin the loop and overseeing the bots to guarantee theaccuracy of their work.Stage 6: HR Concerns. After clearing many hurdles,another barrier remained: corporate governancerequired adding the bots to the company’s HR database.This might seem humorous, but the HR team wasflummoxed since it had never handled a request likethis before. Again, weeks were lost as new processeswere negotiated and approved. Additionally, since theHR database required human names, exceptions werenecessary to include the bots, which were identified bynumbers rather than names.Stage 7: Determining Employment Status ofBots. Again, it might seem strange to discuss theemployment status of a bot, but the company’sprocurement organization raised the question, leading

to a long and difficult conversation about the nature ofrobotic assistants and other forms of automata.Eventually, a licensing system was devised to getaround the thorny issue of whether bots should betreated as workers or as machines.This story represents only the tip of a much larger iceberg.While the leader felt as though she was in a unique situation,the truth is that scenarios like this will become increasinglycommon as companies integrate automation into their normalworkflows. The questions and issues raised during thetransformation process were far from trivial. Echoing thewords of the auditors, the changes were “material,” and theyneeded to be treated with the utmost gravity.It’s a cop-out to label every business transformation as a digitaltransformation. The real transformation must occur within thehearts and minds of the people involved.Innovation and the Agility ParadoxA lack of digital proficiency in an organization will lead to adrop-off in nontraditional problem solving. The mostsuccessful consulting organizations require a minimum digitalproficiency training that is not just a “talking point” but isformally measured and managed. Organizations thatstreamline these approaches to proficiency tend to lead thepack in forward-thinking and innovation.

NET TAKEAWAYS1. Technical proficiency is not the same as digitalproficiency.2. Make no assumptions as to the level of understandingof departments involved in a digital transformationundertaking.3. Infrastructure is in an advanced and commoditizedstate and should be a peripheral consideration.4. Digital transformation involves more than installingnew technologies; there are social and moral issues toconsider as well.5. Digital proficiency leads to more innovative problemsolving.6. The pace of change tomorrow will be faster than it istoday.

Chapter 10Are You “Digitally Determined”or “Digitally Distraught”?Executive Summary: Digital transformation requires morethan grit, tenacity, and optimism. You need a single strategy toguide the multiple components of transformation in a holisticand coherent manner across the enterprise. A transformationalstrategy must be your North Star across the enterprise;transformations that are limited to lines of business orfunctional areas of the organization are unlikely to deliver thedesired results.A recent memorial honoring the armed forces on the 75thanniversary of D-Day brought to mind the tremendousingenuity of the Allied forces. Their creativity, imagination, andwillingness to innovate changed the course of World War II.They were truly brilliant and fearless in their approach. Manypaid the ultimate price, yet they will be long remembered fortheir struggle to liberate a continent and restore freedom tomillions of people.I visited the WWII museum in New Orleans not too long ago,and reflected on the terrible paradox of war, which brings outthe worst and the best in humanity. Focusing on the best of

outcomes, the war motivated people to innovate in thousandsof ways, both big and small. From their efforts sprang betterantibiotics, advanced forms of surgery, pressurized aircraftcabins, microwave ovens, and practical electronic computers.Their innovation launched an economic revolution thatchanged the world.Seventy-five years later we are seeing a similar drive toinnovation. It is important to note that digital innovation is notnew. The early stages of the digital revolution are sometimesreferred to as the “Third Industrial Revolution” and the currentphase, which includes the rise of practical artificial intelligence,is sometimes called the “Fourth Industrial Revolution.”Whatever you call it, the names are less significant than theeffect.I prefer to think of the current digital revolution as a kind ofrenaissance because the technological maturity we’ve achievedhas now greatly accelerated the speed at which industries areable to innovate.This renaissance is driving massive change in every imaginablecorner of the global economy. Every traditional industry isexperiencing some form of disruption caused by the applicationof newer technologies.Disruption has always been at the heart of progress, but thepace of change today is creating a special problem that I call the“agility paradox.” Here is the paradox in brief: new companies

have little or no legacy system to manage, so they can respondmuch more rapidly to changes in the surrounding environmentthan incumbents, who are burdened by their legacy systems.Newer organizations allow digital technologies to permeate andinfluence every aspect of their working ethos while traditionalorganizations tend to maintain the institutional culture thatbrought them to prominence.For example, I’ve heard top executives at many traditionalorganizations pay lip service to concepts such as designthinking, even when it’s clear they have no idea what designthinking is or how it works.Yet when I speak with startup founders and their teams, it’sclear that they understand the critical importance of designthinking and have woven its basic principles into the fabric oftheir organizational culture.Design thinking has become such an integral part of their livesthat they just do it subconsciously. It’s second nature to them,which explains why they can stay in sync with their customersand users. Design thinking goes a long way toward explainingwhy startups always seem nimbler than incumbents.Traditional organizations excel at running the majoroperational components of their businesses. In fact, that’s theircore competency. Operational expediency is crucial to long-term success; that is inarguable.

Why Digital Transformation SeemsConfusingAsk a group of ten business leaders to define digitaltransformation and you will get 12 different answers—and nonewill be wrong. Here’s why: digital transformation is awraparound term used to signify a process that defies easydescription. It’s an intentionally amorphous term whosemeaning shifts and changes depending on the context in whichit is applied.Although the term itself is abstract and general, each and everyinstance of digital transformation is concrete and specific.Talking or writing about digital transformation does not equaldoing digital transformation. It’s like buying a home or startinga family. It’s one thing to plan a life-changing event; it’s quiteanother thing to actually do it.The overarching purpose of this book is to remove some of theconfusion surrounding digital transformation. My goal isdemystifying and clarifying a process that is inherently denseand complicated. (See Figure 10.1.)Fixating on operational efficiency alone creates a legion ofunseen costs and burdens that can adversely impactprofitability. It’s essential to remember that operationalefficiency isn’t free. Achieving efficiency is expensive, a factwhich is often overlooked or forgotten.

Figure 10.1 Perception and Truth matrix.Agile organizations as a general rule tend to buy services fromspecialized service providers and focus on their core business.This also allows for predictable costs based on growth. Scalingup or down is contractually managed rather than becoming anadministrative overhead. BPO and Software as a Service (SaaS)are varying examples of this.Agent of ChangeEver wonder why the term digital transformation has so manydefinitions and why each definition is slightly different? The

cause of confusion is simple: digital transformation meansdifferent things to different businesses.I spoke at length with Carla Hendra, chief executive of OgilvyConsulting, and chief digital officer of The Ogilvy Group, togain a deeper understanding of the many nuances of digitaltransformation by exploring her point of view as a real-lifepractitioner.The opening gambit of our conversation was a generaldiscussion of the topic. She quite simply stated that allcompanies believe in digital transformation and want toachieve it, but less than 10% of them can articulate what itmeans for their organizations and what it entails. Then sheproceeded to share the best description I’ve heard yet.“We define digital transformation simply as establishing newpathways to growth that take advantage of all the newpossibilities in technology. And even as technology changesevery day and impacts a variety of industries in the B2B or B2C,in all cases the customer journey must map to a new and bettercustomer experience.”Using this simple definition of growth-focused digitaltransformation means leveraging mature technology in theservice of a business. That means digital transformation canserve a wide variety of desirable outcomes, such as expanding aportfolio of competitive products, opening new markets,creating a better planet, or simply improving financial margins.

Merely formulating a digital transformation strategy isn’tenough. You also need to communicate the strategy andtranslate it into a set of actionable plans and measurableoutcomes. From her own experiences, Hendra says thatsuccessful strategies include long-term technologytransformation, digital transformation, and customerexperience transformation. Great organizations, she says, focuson creating customer loyalty and trust.Three Fundamental ObjectivesIn today’s digitally connected world, most organizations strivefor three fundamental objectives:1. Better conversations2. Faster transactions3. Precise informationCompetitive businesses also strive intensely to keep pace withthe rising technology curve. The most successful organizations(e.g. Apple, Amazon, Google, Facebook, and Netflix) anticipatethe rise of new technologies and leverage them to createinnovative products and services that enable them to leap farahead of their nearest competitors. From my perspective, thisis the heart and soul of digital transformation: the ability toanticipate and deploy new technology faster and better thanyour competitors.

Let’s take a brief look at the recent evolution of digitaltransformation. It began with electronic data processing on alimited network. This in turn led to “islands of automation,”which we consolidated and built into data centers.The sprawling infrastructure that followed went through itsown evolutionary period of consolidation and then for the firsttime we stepped away from core infrastructure offerings to arealm that included capabilities such as business processmanagement, total quality management, and business processreengineering. Eventually, the complex and expensiveplatforms built to support those earlier capabilities evolved intoplatforms that were more modular and more affordable, settingthe stage for the era of continuous digital transformation weare experiencing today.It’s true that technology moves at a rapid pace and it seems thatthe principle behind Moore’s law can now be extended to everyaspect of digital transformation, which is why it may seemmonumental when looked at holistically. In many respects,digital transformation is the newest incarnation in the never-ending quest for competitive advantage. That’s why peopleoften use the terms “digital transformation” and “businesstransformation” interchangeably, which only adds to thegeneral sense of confusion.BETTER CONVERSATIONS

In the past, digital evolution relied heavily on prior investmentsand the foundations of coding, infrastructure, and data centers.Today’s incarnation of digital evolution relies very little onlegacy solutions.It’s almost as if there has been a change in our DNA, a shift inour approach to solving business problems. Today, ouremphasis is not on making the LEGO blocks themselves;instead, we’re focused on putting the blocks together to createthe infrastructure we need to deliver value.We’ve gone from building systems to creating digitalexperiences; from constructing data centers to creating on-demand infrastructure; from architecting networks to plugginginto the web; and from setting up firewalls to sophisticatedcybersecurity practices.YesterdayTodayBuilding systems=>Creating digital experiencesConstructing data centers=>Creating on-demand infrastructureArchitecting networks=>Plugging into the InternetConfiguring firewalls=>Zero-trust cybersecurity strategies

Most importantly, we’re enabling the business to move farbeyond traditional sales and marketing strategies. Instead ofhelping the company search for customers, we’re helpingcustomers find us. We’re setting up digital ecosystems,enabling us to meet and interact with our customers wherethey live, work, and relax. Sometimes our customers are inphysical locations and sometimes they’re on web browsers ortheir mobile apps. No matter where they are, digitaltransformation enables you to reach out and interact withthem.FASTER TRANSACTIONSThe output from a digital ecosystem is data, not information.Now that we are creating environments for our customers todigitally interact with us, enabling the fastest possibletransactions, these vast volumes of data need to be able to tell astory, shape the conversation, provide management withindicative trends, improve the supply chain, make decisions oninvestments, and so on.But this poses its own set of challenges; unlike the digitalmarketing world where data volumes are large and complexand the fragmentation from multiple social channels is mindnumbing, for the most part organized digital ecosystems that

companies are now maturing to churn out more structureddata, not information.That’s up to the quality of analytics that we can churn out andis no small feat. Moreover, this information that is culled fromthe data needs to be in near real-time or instantaneousdepending on the business. This calls for a different type ofcompute and certainly more precise information.To consider the future of these complex ecosystems, one case inparticular makes for an interesting example—a smart cityecosystem. IoT sensors will most likely be built into everythingfrom traffic light triggers, to lane keeping mechanisms, e-commerce from a moving connected vehicle, speed trackingbuilt into street lights, pedestrian heat tracking sensors in cars,autonomous vehicles, electric vehicle charging stations, smartkeys, vehicle remote control apps, and various other safetyfeatures.The data output from these various sources needs to cometogether rapidly and often quite simply either to elicit animmediate response from a driver or for guidance to a vehicleto take immediate action. This would be similar to airline anti-collision technology but at a much higher rate of transmissiondue to the volume of vehicles in close proximity.PRECISE INFORMATION

I recently sat down with a lead engineer dealing with complexunstructured data sets from e-commerce channels and thebiggest challenge that team faced was the lack of standardsamong the various sources. The engineers on that team spent70% of their time ensuring that the data sets could be joined upin some meaningful way. Then they spent the rest of the timerunning analytical algorithms on the data. Unfortunately, thischallenge is more common than one would assume. Whilefaster transactions give the aura of high performance andaccuracy, the true value is in deciphering the data at a rapidpace.Here’s where machine learning and pattern matching can behighly useful. Often grouped under the general heading ofartificial intelligence, they are practical methods for using rawcompute power to find data patterns that can deliver macroresults, discover anomalies, and pinpoint hidden issues.Machine learning and pattern matching methods aren’tmagical, however. Both depend on algorithms, which are step-by-step processes written by people and used by computers forprocessing data. Typically, algorithms need time to“understand” the data they’re handling. The more data you feedthem, the more they will learn. After an initial period oflearning, the algorithms can dramatically shorten the span oftime required to arrive at the goal of information precision.The engineering team I mentioned earlier implemented amachine learning layer on top of the unstructured data set and

established data joins in under an hour, an achievement thatwould have been impossible just a few years ago due to thevolume and complexity of the data. The information derivedfrom their efforts helped their client gain new insights andcompete more effectively in a crowded market.Key Strategic Elements and SuccessFactorsAssume nothing. That’s a lesson I’ve learned first-hand over mycareer. For instance, it would be easy to assume that asuccessful transformation strategy depends largely on having agood set of ground rules. While ground rules are important,they are not sufficient to guarantee a positive outcome.While I’ve always known this, my conversation with Hendra,president of Ogilvy Consulting, reemphasized thattransformation involves more than people, process, andtechnology. It also involves culture.Anna Frazetto, the chief digital technology officer andpresident at Nash Tech Global, states that in her experience,company culture drives transformation and technologicaladoption in an organization.“Think about it! It all starts with the top and the vision … Thevision creates the culture. You hire with that in mind andbefore you know it, that is what shapes a company,” she says. “I

feel that the embedded culture is the bloodline of a companyand it will drive success and must be understood beforeembarking on a transformation journey.”Culture is the critical factor in transformational efforts. It isboth the prerequisite and the foundation for success. If youdon’t change the culture, the rest of your efforts will be wasted.Without cultural transformation, the organization will continuefollowing the same path it has followed for years or decades.“People will keep doing things the way they already know,”Hendra says.In the short term, you can force some modest behavioralchanges through the introduction of new technologies, newprocesses, and new employees. You may win some battles—butyou will lose the war.That why we usually refer to transformation as a “strategy.” It’snot a series of steps—it’s a holistic process with thousands ofmoving parts, unfolding over time and space.For example, Hendra and her team recently helped a largemultinational company stay on track over the course of itstransformation, which included designing and building digitalhubs in several countries. Additionally, the company needed totransform elements of its core technology stack, which requiredreplacing systems, retraining managers, and hiring new groupsof workers. The new technologies, processes, and people all had

to fit together and operate smoothly within the company’sculture, which was also adapting and evolving to keep pacewith its customers. Fortunately, the company’s CEOunderstood the complexity of the transformation and remaineda steadfast champion through thick and thin. This sponsorshipaspect of the equation is echoed by Frazetto:Several times what I find is that the challenges are withthe existing management team. The first step is gettingbuy-in and agreement from all the necessaryparticipants. Once we establish that course of action, webreak it down into smaller components ranging from theprocess to the staff and to the technology currently inplace.The transformation referenced by Hendra has produced strongand consistently positive results in all of the company’smarkets, demonstrating the benefits of persevering in the faceof monumental challenges.Forging a Transformation RealityWhen do business leaders first realize they need to dosomething different? Is there a definitive moment when a lightbulb goes off, or is it a gradual process of realization?The simple answer is, “All of the above.” But in truth, mosttransformational strategies are born of fear. Companies talk

and talk about transformation, but what finally gets them offthe dime is having a competitor threatening to disrupt theircore business model. That’s when the talk turns into action.Disruption comes in various sizes, shapes, and flavors.Different industries experience different kinds of disruptionand must therefore develop different types of transformationalstrategies.For example, companies operating in industries such ashospitality, retail, and financial services are generally moresensitive to quarterly results than companies in industries suchas mining, manufacturing, and refining. That sensitivity usuallyinfluences the speed of their transformation. A company thatworries about its quarterly earnings will probably transformitself faster than a company that doesn’t.Each industry has a moment when outside forces compel amajor transformation. It’s almost like a law of nature. In theretail banking industry, for instance, when one bank beganoffering mobile deposits, every other bank quickly followedsuit. They really didn’t have a choice—they had to transform ordie.The proliferation of smart personal devices has generated acontinual race to innovate and win customers by offeringconveniences and capabilities your competitors don’t yet offer.Companies in consumer-facing markets are racing to offer the

best customer service, the best apps, and the best rewardsprograms. This is truly the new face of competition.As Hendra observes, this continual race to outdo thecompetition means that every company must run at top speedjust to stay in place. Innovating in this kind of environmentrequires nerves of steel and supernatural speed, neither ofwhich are easily purchasable commodities.So how do traditional companies remain competitive? Manyrespond to outside pressure by acquiring or merging withcompanies that specialize in rapid innovation. Sometimes theycreate entirely new companies that are spun off but remain inorbit around the parent company.Recruiting, hiring, and retaining top talent is a major issue forcompanies to a far greater degree than ever before. Today,companies don’t merely need talented people—they needsuper-talented people!The talent conversation could not be a more pertinent one atthis moment in time. Frazetto looks introspectively at thetrajectory of change over just a few years: “I think life wassimpler 10 years ago or even 5 years ago in comparison totoday. So, when you marry technological advancements (harderskill required) with transformation and competitive pressuresyou wind up with the skill sets being compounded and gettingmore complex. No one ever looks for just one skill set anymore.”

Determined or Distraught?Meredith Whalen is chief research officer at IDC and a memberof the senior management team. She leads IDC’s worldwideresearch organization, product management, marketing, andclient services functions, setting the direction and agenda forIDC’s worldwide research products. Her international team of1,100 analysts leverage research and advisory services toempower business transformation for the Global 2000, andcounsel technology suppliers on creating effective offerings forthe digital economy.I asked Meredith to help me understand why someorganizations struggle with digital transformation, and shegenerously shared her team’s research. According to theirsurveys, organizations with transformational goals fall into twocategories: the “digitally determined” (46%) and the “digitallydistraught” (54%) (see Figure 10.2).“When we looked at the data, we saw common threads,”Meredith explains. “The ‘digitally determined’ organizationsmake sure they’re really executing on one strategy, one visionfor digitally transforming the organization. They have anintegrated enterprise-wide digital strategy.”By contrast, she notes, the “digitally distraught” organizationshad multiple strategies. In some organizations, it seemed asthough “each line of business or each functional area had its

own digital transformation strategy and its own digitalroadmap.”Figure 10.2Source: IDC Global Leaders Survey North American sample, June 2018.In a recent report, Meredith writes that becoming “digitallydetermined” requires more than grit and tenacity. It requires ablueprint with four essential components:1. Create organizational alignment and culture around digital.2. Employ a single enterprise-wide strategy.3. Demonstrate inherent value of digital.4. Scale digital innovations with an integrated platform.In our conversation, it became clear to me that leadership is acritical differentiator between “determined” and “distraught”organizations. “Transformation requires a top-downapproach,” Meredith says. “You need a CEO who says, ‘I’m1

going to make the hard decisions and there will be changeshere.’ The ‘digitally determined’ are willing to do whatever ittakes, even if it means upsetting the applecart.”Based on their findings, the IDC research team lists five keyfocus areas for “digitally determined” organizations:1. Creating digital KPIs2. Establishing an end-state digital organizational structure3. Constructing a long-term digital roadmap4. Developing the most important digital capabilities5. Building a digital platformI found the IDC analysis to be especially useful, and I amgrateful to Meredith for permitting me to quote from herreports and articles in this book. I also recommend readingMeredith’s blog post, “The Digitally Determined Blueprint,” inwhich she details the steps followed by successful organizationsto achieve their transformational goals.Tone from the TopWhether you end up with the much-desired streamlinedecosystem or poorly integrated islands of automation dependsentirely on the tone from the top. A central strategy andappropriate funding for the right initiatives drives the plannedand predetermined outcome, often exceeding expectations. A23

great strategy, but significant autonomy in downstreamdecision-making within organization P&L’s can be disastrous ina digital transformation. The latter advances individual careersand generates impressive case studies of shiny new techadoption but has a retarding effect on the overalltransformation strategy.More often than not, digital transformation is more impactfulwithin well-run companies where there is a singular North Starand all decisions, investments, and attitudes follow that star.While not every aspect of these organizations works perfectly,they have developed a mindset and strategy that ensuresalignment at almost all steps and back that up with agovernance model that keeps the plan on its flight path. Theoutcomes are reflected in the results of organizations like theseand the pace feels like a jet being catapulted off a carrier deck.The obvious area where transformations typically fall flat iswhen business strategies are disconnected from executionplans, and while these disconnects become apparent early inthe journey, the truly dangerous ones are when the strategy issubtly disconnected from the execution. Here is a brief list ofissues that can derail a transformation project:Lack of process governanceMinimal operational cadenceLack of formalized outcome tracking

Vague predefined benefits identificationWeak or non-dedicated project managementToo many consultants and too few doersLack of specific goals for key staffPoor technology decisionsAny of those issues has the potential to create redundant orunnecessary work for staff, resulting in missed deadlines andsignificant delays. Worse yet, endless rounds of “busy work”can yield the false impression that progress is imminent,despite the absence of measurable achievements.Lack of staff motivation is an underlying and often critical issuethat can engender low morale, lackluster performance, and ageneral sense of aimless confusion. Great leaders don’t ignorethe importance of motivation; they strive to maintain highlevels of engagement, especially during periods of rapidchange.

NET TAKEAWAYS1. Transformation programs must be driven by a singularbusiness strategy but can be broken down into multiplesubprograms.2. Transformation is a business strategy, not a series oftechnological advances.3. Governance across the various activities along withtechnological investments must be centralized to allowfor fewer integration challenges.4. Progress reporting, project benefits measurement, andissue resolution must be tracked with regular anddefined cadence.5. Leverage design thinking for rapid problem solvingwhere possible.6. Seek informal feedback from casual conversations withemployees, managers, and executives to get a feel forwhat’s working and what could be improved.7. Digital transformation is always defined in terms ofbusiness benefit.Notes

1. 1 IDC PERSPECTIVE: A DX Blueprint from the DigitallyDetermined, by Meredith Whalen.2. 2 IDC PERSPECTIVE: How to Break Through the DigitalTransformation Deadlock, by Meredith Whalen.3. 3 https://blogs.idc.com/2018/06/26/the-digitally-determined-blueprint/.

Chapter 11Use Case: The Smart CityExecutive Summary: The impact of digital transformationextends far beyond the boundaries of corporations andbusiness entities. Towns, cities, regions, and nations are alsotransforming themselves in the hope of providing better publicservices with greater efficiency, lower costs, less waste, andreduced carbon emissions.Digital transformation is a truly global trend. Every region anddemographic group is affected by the digitization of productsand services. Within a brief span of time, we have become adigital world, driven by data and moving at the speed ofinformation.Today, our homes and communities are nodes in a worldwidedigital network. The poet John Donne famously wrote that “noman is an island.” Those words, published in 1624, seem eerilydescriptive of our modern culture, in which we’re never morethan a tap away from connecting with friends on social mediaor reaching out to colleagues on a collaboration platform.The impact of digital transformation extends far beyond theboundaries of corporations and business entities. One of the

most compelling use cases for digital transformation is thesmart city.You’ve probably read about smart cities and wondered ifthey’re real or just hype. I would say that smart cities are anemergent phenomenon, which makes them hard to describe.From my perspective, a smart city is a place where thecontinual collection and analysis of data enables theoptimization of a broad portfolio of municipal services. A smartcity provides the best possible experiences for its citizens,workers, and visitors—while simultaneously managing costs,improving efficiencies, and reducing energy consumption.Although my description seems fairly straightforward,becoming a smart city can be complicated. Here’s why: a city isa system of systems. Ideally, those systems should beinteroperable and capable of sharing data. But the vastmajority of cities were built long before the idea of systemsthinking arose.The systems we associate with a typical city—water, gas,electric, buses, subways, trash collection, sewage, streets,sidewalks, and parks—evolved separately, and often at differenttimes, over the course of decades and centuries.Most cities are disorganized tangles of disparate legacysystems. Data collection is haphazard and inconsistent. Somecities have made great strides in digitizing their data, yet manystill keep records on paper and allow city departments to store

their information in silos that are inaccessible to otherdepartments.The harsh truth is that most cities do not have a comprehensivedata governance strategy. Cities without a clear data strategywill find it exceedingly difficult to use their data for analyzingand optimizing services on a consistent basis.Smart cities, however, have strong data governance policies inplace to ensure the accessibility of information acrossdepartments and agencies. Smart cities are all about good datamanagement, and some smart cities have hired data scientiststo oversee and facilitate the use of data in everyday decision-making processes.For example, a smart city might use sensors and cameras tomonitor activity in its parks. When nighttime activity in a parkebbs, the lights in the park could be dimmed to save energy.When people reenter the park, the lights would be brightenedto full intensity. A smart city might also equip its senior citizenswith a smart phone app that would automatically turn on thelights in a park when they enter, providing safer and moreenjoyable experiences for people who might otherwise decideto stay at home.A smart city would also keep track of activity patterns overtime, enabling it to schedule maintenance and cleaning attimes when the park is less crowded. Additionally, a smart city

would monitor usage of its bike and walking trails to predictwhen repairs and maintenance will be necessary.“A smart city will know when you’re sick or injured andautomatically dispatch emergency medics to help you,” writeMike Barlow and Cornelia Lévy-Bencheton, co-authors ofSmart Cities, Smart Future. “A smart city will remind youwhen it’s time renew your driver’s license—and then help yourenew it from your mobile phone. A smart city will help youfind a good rehabilitation center if your mom slips and falls onthe sidewalk.”An Infinite Universe of Moving PartsWhat can corporate executives learn from smart cities? Ibelieve companies and cities encounter similar challengeswhen confronting the need for digital transformation. The firstchallenge is sheer complexity and the second challenge ismanaging risk. Here’s a brief excerpt from Smart Cities, SmartFuture describing the incredible complexity and inherent riskposed by cyber-physical systems in a metropolitanenvironment:

In a smart city, there are no standalone devices,applications or systems. Everything is connected and tosome degree, interdependent.For example, the ticket machines at the train stationmight seem like standalone devices, but they’re connectedto the city’s transit, financial and electrical systems. Sincethe ticket machines accept credit cards in addition tocash, they’re also connected to the privately owned andoperated financial systems that process credit cardpayments.Like the ticket machines, the small sensors in the subwaythat detect the approach of trains are both standalonedevices and nodes in a network. Essentially, every deviceand application plays a dual role. It’s an interestingphenomenon and a fundamental aspect of the Internet ofThings (IoT).Smart cities are subsets of the IoT, which means they arealso subsets of the internet. That’s more than a cleverobservation. It’s a scary fact. The internet has manywonderful qualities, but security isn’t one them.As metaphorical children of the IoT and grandchildren ofthe internet, smart cities possess the strengths andweaknesses of their progenitors. They are broadly usefuland usable. They are painfully difficult to secure. Securityis to smart cities what kryptonite is to Superman.

Just as Superman’s fear of kryptonite doesn’t stop himfrom flying around and doing good deeds, smart citiesmust overcome their fear of cybercrime. We’re notsuggesting that cities should ignore the threat ofcybercrime; we’re saying that cities should acknowledgeit and do everything in their power to fight it.Safety FirstBecause smart cities are cyber-physical systems, any digitaltransformation initiative must also take human safety andphysical risks into account. In the corporate enterprise, weoften use a risk assessment method called “C-I-A,” whichstands for confidentiality, integrity, and availability.But smart cities are a blend of digital and physical assets. Realpeople, made of flesh and blood, live in smart cities, and wemust consider the potential impact of our transformationproject on their safety. For smart city transformation, the riskassessment method is “C-I-A + S,” where the “S” stands forsafety. Here’s another brief excerpt from Smart Cities, SmartFuture:1

Safety throws a wrench into the traditional method ofdetermining how much to spend protecting cyber assets.For years, the rule of thumb was simple: never spendmore to protect an asset than the asset is worth.When safety is added to the equation, the rule of thumbgoes out the window. For example, let’s say the sensor inthe subway car door costs three dollars. Does that meanyou won’t spend more than three dollars protecting it,even when you know that if it fails, a rider might be hurt?If a subway car door closes on a rider’s hand or foot, thecost of the injury will far exceed the cost of the sensor inthe door. If the injured rider decides to sue the city, thecost will be even higher.Smart cities will have to invent new ways of modelingrisk, valuing assets and setting spending priorities. If theemergency braking system in a smart elevator is hackedand the elevator plunges 100 floors before hitting theground, the first thought in everyone’s mind won’t be thecost of the elevator.Six Areas of “Smartness”In their book, Barlow and Lévy-Bencheton list six focus areasthat broadly define the smart city concept:

1. Smart Economy. Multiple economic components from thepublic and private sectors are integrated, coordinated, andorchestrated to speed the flow of resources and materials toprojects and areas of the city where they are most needed.2. Smart Government. Decisions are made and resourcesare allocated based on actual needs of citizens and predictedusage of services, as opposed to guesswork, BAU (businessas usual), or fleeting political sentiment.3. Smart Environment. Smart cities use data analytics totrim energy costs and reduce carbon emissions. They alsofollow “circular economy” principles to ensure the lowestachievable levels of consumption and waste.4. Smart Living. Services and resources are optimized toensure widest possible accessibility, usage, and enjoymentacross all demographic groups and sections of the city. Inother words, the benefits of city living are shared broadly,rather than being limited to small groups of privileged users.5. Smart People. Education, lifelong learning, and continualre-skilling are prioritized and fully funded, fostering andpromoting a culture of intellectual curiosity, innovation, andinvention.6. Smart Mobility. Smart cities have fully integratedmultimodal transit and transportation systems, ensuringeasy travel and commuting across all sections of the city andits surrounding suburbs.

Achieving success in each of the six focus areas depends onstrong marriages of policy and technology. You can no longerhave one without the other; they have become the yin and yangof modern civilization.“The smart city movement is part of a larger digital revolution,”the authors write. “Digital technologies aren’t simplytransforming business and industry—they’re transforming eachand every aspect of our lives, including the places where welive. We are experiencing a genuine shift of paradigms; a newworld is being born.”Four Stages of EvolutionAnother important lesson we can learn from smart cities is theimportance of moving forward in a series of steps. I’m not hugefan of incremental change, but I do appreciate the value ofputting one foot in front of the other. There’s nothing wrongwith treading carefully, especially when large amounts ofmoney are at stake.Many smart cities learned this lesson the hard way, buying intothe notion that technology was the answer to all of theirproblems. Some of the early adopters realized the error of theirways, scaling back their efforts and redefining their objectives.Over time, it became apparent that smart cities aren’t built in aday. Even the “smartest” cities follow an evolutionary path withfour stages:

1. Tech-driven. Cities rely on vendors and consultants toguide choices and invest in technology solutions.2. City led. Local government takes the reins and develops itsown strategies for smart city development.3. Citizen-centric. Citizens become more involved in theprocess, developing grassroots programs for positive changeand pushing back against top-down initiatives.4. Collaborative. In this stage, coalitions of engagedstakeholders work collaboratively to develop practical andsustainable smart city strategies aimed at solving real-worldchallenges such as transportation, public safety,accessibility, inclusion, and economic opportunity.“Sooner or later, most of us will live in smart cities,” theauthors write. “It’s up to us to determine whether those citiesare smart because they’re equipped with the latest technologysolutions or smart because they provide us with the resourceswe need to live happy and fulfilling lives.”The insights drawn by the authors of Smart Cities, SmartFuture can be generalized to cover virtually all forms of digitaltransformation strategy. The primary lesson is that a successfultransformation project always focuses on people first andtechnology last. It’s never just about technology; it’s aboutpeople using technology to make their lives easier, happier, andmore satisfying.

NET TAKEAWAYS1. Leaders of corporate transformation strategies canlearn valuable lessons from smart cities, which facesimilar challenges and problems.2. Smart cities remind us that all successfultransformation efforts depend primarily on changingthe habits and behaviors of people. The technology issecondary.3. Complexity is part of the challenge, for the smart cityand the modern enterprise. Ignoring or downplayingthe complexity of a transformation project willguarantee poor results.Note1. 1 Barlow, M and Levy-Bencheton, C. (2018) Smart Cities,Smart Future (New York: Wiley).

Chapter 12Looking Ahead: Runway orPrecipice?Executive Summary: Many of the new terms bandied abouttoday are essentially buzzwords. But not everything you see orhear is hype. There are serious challenges ahead, and you mustprepare your organization and yourself for handling themeffectively. This chapter is basically a list of newer technologies,with advice and suggestions for avoiding missteps.A Google search for the term “digital transformation” will yieldnearly half a million results in less than a second. A search for“artificial intelligence” will generate even more results in aboutthe same fraction of a second. Searching for terms such as“machine learning,” “virtual reality,” “big data,” “robotics,”“predictive analytics,” “blockchain,” and “quantum computing”will yield generally similar results.If you work in the field of business or technology, you can becertain that people will be asking you for your opinion on theabove mentioned terms. My advice is to be prepared. Havesimple, easy answers ready—because the questions will beasked, I guarantee you!

With that thought in mind, here are some of the responses Itypically give when asked about the latest, greatestdevelopments in tech.Artificial IntelligenceAI still induces a combination of fear and skepticism in mostpeople. From my perspective as a business executive, only ahandful of AI solutions are mature enough to be readilyadopted. In other words, AI is highly promising, but it’s notready for prime time.In summary, AI has a lot of promise and is progressing steadilybut before trying to leverage it within a business the basic rulesstill apply—garbage in/garbage out.If posed with an investment decision, focus the conversationaround the quality of data that will drive intelligent outcomes,not necessarily just the volume. Good business process willlead to better opportunities to leverage artificial intelligence.BlockchainBlockchain is definitely not for everyone. Much has been madeabout this technology because it is the foundational technologyof modern cryptocurrencies. Blockchain itself is notcryptocurrency, but it supports cryptocurrency transactions.

But in layman’s terms let’s boil it down to a simpler context.Imagine that we have a small company with offices in NewYork, London, and Singapore, all working off a single expenserecord book. Here’s the “traditional” scenario:The New York office keeps the record book and theother two offices update the book when they incur anexpense.Only the New York office is aware of all transactionsacross the three offices.In the event of a security breach in any of the threelocations, information could be altered for fraudulentpurposes with relatively little chance of detection.In a “blockchain” scenario, each office is a “node” in a securenetwork and each of the offices would have access to the mostcurrent version of the record book in real time. If, for example,the London office incurred an expense, the record would bevalidated with the other two offices and the encryptedblockchain would be updated.A security breach at one office would not compromise thenetwork; attackers would have to breach all three nodes tosucceed. Attempting to breach all three nodes would require atremendous amount of computing power, which is whyblockchain is considered more secure than traditional methodsof keeping records.

So far, blockchain has proven useful for validating complexsupply chains, moving valuable cargo, cryptocurrency, moneytransfers, land titles, copyrights, and so on with an ever-increasing list. Being in early stages of adoption, there are veryfew examples of its full-blown use. It will be some time beforethere is enough maturity in the market where use cases becomemore frequent.If posed with an investment decision, be aware that blockchainexchanges are starting to become a service provided by the bigcloud providers due to their heavy computing requirements.Just like cloud providers that slowly proliferated thetechnology market, Blockchain-as-a-Service (BaaS) will providemore opportunities for organizations to leverage thistechnology.RoboticsRobots have learned to ride bicycles, assemble cars, defusebombs, and deliver groceries. But don’t hold your breathwaiting for them to take over your office job.From a business perspective, robots (aka “bots”) mostly handleprocess automation tasks. Bots can do the mundane, repetitive,and voluminous tasks that people really don’t enjoy doing. Thiskind of robotics is called robotics process automation (RPA),and is rapidly becoming one of the common types of

automation. It works best when the organization already hasorderly, well-established, and tightly governed processes.RPA was traditionally called scripting and has been aroundfrom the early days of software coding; when developers wouldwrite software modules that did repetitive tasks, these moduleswould then be “summoned” within the context of a largercomputing transaction. The simple difference betweentraditional scripting and modern robotics is that softwarecompanies have made it into platforms that are abstractedfrom software code and can be written by using relativelynatural language terminology.Scripts or bots can be written and integrated to almost anyplatform out there. For example, if you run Oracle, Microsoft,or SAP as a financial accounting software, RPA platforms fromcompanies such as UI Path and Automation Anywhere can runprocess automation independent of that accounting software.They automate processes to mimic what a typical user would dorepetitively.Case studies show that RPA as a technology is very useful butmany organizations are not culturally ready for it and somelevel of digital proficiency would help remove the employeefear factor and leverage the technology for what it is. The largemanagement consulting organizations, financial firms, and lifeinsurance are a few industries that use robotics extensively,effectively, and glean great benefits from it. I have seen otherindustries use RPA to prepare large data sets for analytics,

speed up back-office processes, and help get products quickerto market. Robotics, though often associated with taking overrepetitive human tasks, poses a higher risk for business processoutsourcers (BPOs). Many companies already have their backand middle office work outsourced and leverage some form oflabor arbitrage that very outsourced labor will steadily beautomated and will force the renegotiation of contracts. Somecompanies are taking a proactive stance and offering betterpricing as a result of internal automation.If faced with an internal investment decision, ask questionsaround the business problem it will solve first. Then askquestions around quality and governance of the businessprocesses. Needless to say, it’s easier to understand processautomation when the process is streamlined and much harderwhen the process is fragmented. RPA done right can deliversolutions to complex business challenges and yield efficiencyand cost savings while doing so.Virtual RealityIt was the peak of winter and I was piloting a Boeing 777aircraft into John F. Kennedy airport in New York with over280 passengers on board. I turned on the seatbelt signs asstrong winds buffeted my aircraft and I lined up for runway 4L.That’s when the rain and hail started. Visibility was low and Iwas relying purely on my cockpit instruments; I wasn’t sure I’dbe able to land when the tower cleared me on my final

approach. The landing was too fast and way too hard. Ibounced twice, sped down the runway, brakes screeching,engines in reverse and I still skidded off the end of the runwayto come to a complete stop. Then I sat back in relief and took asip of my coffee while not caring what happened to mypassengers.The coffee was real, the aircraft wasn’t.It was the nearest bad-weather “reality” scenario I couldmuster with the limited knowledge of my favorite hobby, flightsimulation. In virtual reality mode it feels like the real thing!In another similar scenario, the movie Avatar in 3D was awe-inspiring for me as the immersive scenes caused one to movethrough large objects that defied gravity while dragons flewaround.There is a subtle difference between the two scenarios; while a3D movie places you in the magic of the moment, you justwatch and react to thrilling events in the film that can beentirely imaginary. Virtual reality on the other hand createsvisual or interactive spaces with a computer-generated three-dimensional environment based on real-life scenarios, like anaircraft landing while sitting in the pilot’s seat.In order to do this, one needs a couple of simple pieces oftechnology equipment, usually a headset and a controller—theheadset to view the images or specific objects within the 3D

environment, think of it as a mouse pointer, and the controllerto take action. For example, if driving in a virtual car, thecontroller can be a steering wheel and pedals, or for a virtualflight, a flight yoke, and so on. Whatever the application, youare removed from the world around you in a completelyimmersive experience.People often confuse virtual reality with “augmented reality.”The latter actually enables apps on devices to insert objects intolive scenarios. The best example of this was the Pokémon crazea few years ago. By pointing your phone camera at certainareas, for example, street intersections, parks, or other suchlocations, you could see the presence of a Pokémon character atthe location—they were augmenting the reality of yoursurroundings while you were present at the location.Virtual reality has been around for a while but newertechnology and commercialization of headsets and controllershas made it more accessible to consumers.The premise is that VR is so immersive that we will be able torecreate any physical world task or interaction within thevirtual space and train our employees, give customers theclosest experience of really driving the car they want to buy,show customers what the first-class cabin experience reallylooks like, stand at the edge of Niagara Falls, or walk throughMachu Picchu. For the first time gamification of customerexperience and training scenarios do really sound like fun.

Could there be applications for patients who are bedridden toget a few moments of escape or physical therapy landscapesbetter than the sterile environments of a doctor’s office? I couldcite at least 15 different application opportunities to use VR butthe ideas are only as limited as your thinking will allow.If faced with an internal technology investment question,consider your type of business: Is it customer experience-basedor would it be better utilized for internal training purposes?Almost all industries have the potential to benefit from thevirtual reality ecosystem—from content creators to experiencecreators such as digital marketing units to business and retailconsumers. While costs could vary depending on the scale ofthe undertaking, a well-designed memorable experience ispriceless and puts you on the cutting edge of modern tech.Big DataHow big is BIG? I was involved in a project where our datagroup was in an experimental stage with a database technologycompany, a Silicon Valley startup. In order to test theircapability, the group decided to send them a small file. When Iqueried what “small” meant, I found that the database had 65million records!When large trucks pulled up outside our offices to collect boxesof permanent financial records, we never called it “bigpaperwork.” In fact, the old paper-based management of

transactions, be they financial, retail, or business related, hadextremely limited value for mining or analyzing the datawithin. In the environment we live in today, almost everytransaction from sensors in vehicles, factory machinery, onlineretail databases, search engines, points in a supply chain,Internet browsers, game consoles, smart TVs, cell phonetowers, smart watches, voice activated devices, or your car GPSall generate data outputs from a transaction or datatouchpoints from interacting with other devices or people.These volumes of data are undoubtedly large and can yieldvaluable information if mined or analyzed. Given thesevolumes, technologies are now available to segment, dissect,and analyze meaningful patterns and outputs to supportbusiness decisions, wear and tear on equipment, utilization ofmachinery, and many, many more uses.This data due to its voluminous and seemingly ever-growingscale is often referred to as “big data.” The advantages areplenty and even small businesses are able to benefit from thismethod of capturing and analyzing outcomes from data as theytake advantage of affordable and easily accessible cloud-basedtechnology services.If faced with an investment decision, discuss the benefits ofpersonalization, decision support, field maintenance, andcustomer service by using the analyzed data to your businessadvantage. And while benefits may vary, issues related to dataprivacy must be clearly addressed with any scenario. Someorganizations using this data capability may have a relatively

small geographical footprint but even though big data tends tobe anonymized, a good thumb rule is to take the most stringentglobal privacy rules and apply them to your environment. Thiscan be a confusing and complicated area and if a “data privacyofficer” is not a designated role in your organization,professional legal advice should be sought.Cloud“Islands of automation” was a term coined in the early days ofnetwork computing to indicate limitations of interconnectivitybetween computer systems. Companies often maintained localcomputing centers in each of their locations, called datacenters. Later in the evolution of networking, wide areanetworks (WANs) started creating better interconnectedsystems with less duplication of servers and applications. Withthe proliferation of network connectivity, centralization ofthese data centers was the next stage of consolidation but thesecenters were still extremely expensive to run; they had to haveback-up data centers for disaster recovery; they had tomaintain efficient cooling systems to handle the heat generatedby the computer equipment; often they occupied expensive realestate; and they had to be monitored 24 hours a day, 7 days aweek, 365 days a year. But most importantly, they were neverfully utilized. For the most part, systems ran at peak duringbusiness hours and sat idle in off hours; even round-the-clockoperations could not efficiently utilize all the availablecomputing power of servers.

Over time, this morphed into a solution where the hardwareand network was built up by service providers and madeavailable to buyers in bite-sized chunks—this came to be knownas cloud computing. By way of a simple analogy, cloudcomputing is similar to a hotel. You go in and rent some spacewith all the amenities of heating, cooling, plumbing, secureaccess, etc. You can upgrade if you wish, or take the bargainrate, and you can also buy more space and stay for longer orcheckout when you’re done, but you would never have to buildor buy your own hotel. Cloud computing works on a similarconcept. You buy the computing power, network, and storagefor the capacity you need for a fully functioning data center.This capability has widened to a broader ecosystem of“managed services” or cloud-based applications where thevendor or supplier provides an end-to-end method of a givenservice, for example, Gmail or Office365, where all you need isa contract and a browser to make it work. This does not implythat you don’t need some of those technology skills internally;in almost all cases integration to other systems, includingsecurity and access to these systems, is handled internally.If faced with an investment decision, it is crucial to get yourinternal technology architects involved early. Cloud contractsrelated to data retention and transfer can also be complex.While most cloud vendors have figured out the best ways toresolve this, “vendor lock-in” can be a serious problem if youdecide to change providers in the next few years. Also questionwhere your data resides; if in another country, what laws apply.

What failover options they have for disaster recovery andunderstanding their integration capabilities for today, as wellas a roadmap of the future, are crucial. There is also theconcept of private cloud, public cloud, and hybrid cloud—butleave that to your architects to decide the right approach foryour business.Internet of ThingsYou’ve probably received notification emails for when yourcredit card payment is due or your online order has shipped.But that casual method of notification is relatively passécompared to the sensor in your car telling you the inflationlevel in your tires in real time, or your dishwasher telling yourmaintenance company of a potential issue, or the motionsensor in your thermostat adjusting the room temperaturebased on activity in that area.Sensors are now being built into everything and are connectedto deliver their bits of information to other sensors that triggera reaction or send information to relevant recipients to takeaction very rapidly, not like the old methods of asynchronousemail.Industrial use of sensors have been around for a while; over adecade ago a large microchip manufacturer was able to tell theage of fresh produce being transported by attaching a smallRFID chip to the inside of a shipping container. Wearable

technologies help workers build planes while reducingexhaustion from carrying heavy equipment. Sensors in tractorsin fields thousands of miles away can inform a monitoringcenter of a breakdown or even help prevent one.However, in today’s scenario, sensors are now placed intoeverything we touch and create ecosystems that presumablysupport our every human convenience. If you want to checkyour heart rate while at the gym, just glance at your watch. Ifyou want to see who rang your doorbell while you’re in anothercity, just glance at your phone. You can even open doorsremotely for your kids by hitting that smartlock app—and thelist goes on.This is the hyperconnected world we live in and refer to as the“Internet of Things” (IoT). IoT is here to stay and enables aworld where these connected sensors provide invaluableconveniences and save time and money for a generation gluedto interactive handheld devices. Many industries havecapitalized on this and continue to invest in IoT in innovativeways as seen here.If faced with an investment decision, the technology isconstantly evolving and there are companies that can assistwith every aspect of your business needs if you choose to gowith IoT. The important questions would be more around userexperience (also known as UX), what data will you collect, whatinformation would you glean from data sensors in yourproduct, and how you will respond to that information. Will

you improve service, will it be used to improve the productitself, will you use it to cross-sell, would the data help driveacquisition strategy to fill strategic needs gaps? Theopportunities are tremendous.Marketing Automation andProgrammatic AdvertisingYou search online for an airline ticket and you coincidentallystart receiving emails with destination guides, discount tours,airline perks and benefits, maybe even a credit card tied tospecific airlines. Congratulations, you are most likely thesuccessful target of a marketing automation program. This isnot bad news as you will get information relevant to that initialsearch and it also means that marketers have data on yourpersona and can connect with you through multiple channels.Typically within the business landscape that persona ismanaged by a customer relationship management (CRM)platform where various pieces of information about a customerare stored, including last contact, nature of contact, andpotential for a sale or contract, etc. This in turn allows fortargeted marketing campaigns with focused information. Theprocess of being able to serve up an offer to a buyer in anautomated way through multiple digital touchpoints is oftenreferred to as marketing automation.

But what happens when great CRM platforms are notavailable?One nuance of marketing automation in the digital space iscalled programmatic advertising. A simple form of how thisworks is outlined below. For example:A user browses the Internet; data managementplatforms (DMPs) constantly collect and analyzecookies off the user’s browser. This analysis creates atarget audience profile and a better view of thecustomer’s online profile through search, and so on.In order to make good use of these profiles and postthem on various online properties, the intermediarybetween the data platform and the supplier is thedemand-side platform (DSP). This platform evaluatesthe impression based on certain data points andsubmits a bid to the supplier.Publishers manage their online inventory on supplier-side platforms that keep track of the unsold inventory;they also pick from the highest bidder for availableinventory.The end result of the above three steps is that an ad isserved to a user online.There are different reasons for bids to be higher or lower, as anexample:

One of them may be brand awareness, and position on awebpage may not be as important as long as it appearsfrequently on as many web pages as possible.Another reason may be that the brand wants a distinctcall to action and wants the user to click for moreinformation or to buy a product. These would be placedstrategically on the webpage and are often referred to as“above the fold,” as in a folded newspaper, where yousee the headline first.Programmatic advertising is advancing as a result of thetechnologies mentioned above, such as AI, big data, androbotics, and has increasingly matured for television as well asconnected TVs, to become part of the Internet ecosystem.Opportunities to assign ads based on television content ortarget audience increase as the inclination of consumers to usevideo on demand and other streaming methods, also referredto as “nonlinear TV,” increases. The method by which youcannot pause or forward ads is referred to as “linear TV.”If faced with an investment decision, consider engagingspecialized digital agencies to run this for you, especially if youare a small to medium-sized business.Large companies often make the investment in the overallplatform and engage digital agencies to support parts of it dueto its various specializations. This is an involved, always-ontype of ecosystem and needs skills that can handle managing

branding, brand awareness, customer engagement, andcustomer conversion through e-commerce platforms.Even though attribution for the quote “Data is the new oil” isnot clear, it has some relevance here. If you’ve worked with oil,you know it’s messy and needs to go through a process before itis usable in an internal combustion engine.Similarly, marketing automation also has a significant dataplay and analysts and data scientists work behind the scenes tocleanse data and manage these complex platforms before thedata is in a usable format, which makes internalizing andsupporting this platform a serious consideration.Don’t Get Fooled Again…Have you ever seen an ad for a great product in a glossymagazine, only to order it and receive a piece of cheap moldedplastic? It happens less often with the onset of Internet reviews,but it does happen.Applications work pretty much the same way. While mostmodern applications have all the makings of a solid foundation,some applications just have glossy exteriors. These apps areeasy to create with tools readily available to a 12-year-old withan interest in building them. However, we see more often thannot that senior executives succumb to the “look and feel” of anapplication or platform rather than its underlying framework.

Think of a sleek Formula One car body with a motorcycleengine. Similarly, application architecture can be complex andshould not be decided on based on just its look and feel.From the early 1980s, the Open Systems Interconnection (OSI)model has helped create a logical breakdown forinterconnected networks and application protocols. While a lotof the methods are used to create apps, the fundamental waythey interact with the network remains the same. Even within acloud environment the basic logic of the OSI model is stillapplicable.The OSI model contains seven layers and is a good teachingtool, as annotated below:1. 7. Application2. 6. Presentation3. 5. Session4. 4. Transport5. 3. Network6. 2. Data7. 1. PhysicalThis is not meant to be a technical explanation of each layer butI’ve often used this analogy with executives to show them justone dimension of the complexity that sits under the glossy

exterior of the application or Layer 7 that they might be lookingat. Applications have their own sets of integration options withterms like application programing interfaces (APIs), service-oriented architectures (SOAs) and other gnarly expressionsonly suitable for use by integration gurus.If faced with an investment decision, bring in your technologyarchitects early—then trust their evaluation. No matter howgreat an app looks, if your architect says it is a riskyproposition, it most likely is.Newer technological advancements are more complex thanever before. New terminology and acronyms already proliferateour conversations and it’s hard to keep up with anunderstanding of each and every one of them.Digital transformation leaders need to be skilled in the art ofstorytelling. They have to break down these complextechnological advancements into relatable experiences for theiraudiences in the boardroom and the back office. Furthermore,they have to leverage their digital proficiency skills in order tomake the right transformative decisions while maintaining aninnovative edge at all times.

NET TAKEAWAYS1. New technologies and their acronyms will come andgo; always focus your investment decision on the corebusiness purpose.2. Involve professionals to objectively evaluate theunderpinnings of modern data services or technologyofferings that you want to acquire.3. Familiarize yourself with the fundamental aspects ofthe new technology and explain them to your audienceswith practical analogies.

Chapter 13AI: The Elephant in the RoomMike Barlow1Whether you are a C-suite executive, line of business (LOB)manager, or a learning and development (L&D) strategist in thehuman resources department, you are probably dealing withquestions and concerns about the looming impact of artificialintelligence (AI) on the workplace.For senior executives, AI will raise difficult questions about:Remaining relevant in rapidly evolving markets.Competing effectively against faster-moving opponents.Existential risks and long-term business strategies.For LOB managers, AI will raise concerns about:Keeping pace with new technologies.Reskilling and upskilling employees.Adapting to change, both internally and externally.For L&D leaders, concerns will include:Meeting the needs of business units.Developing skills and talent within the organization.Evaluating quality and content of learning tools and solutions.If you are uncertain and unsure about AI, don’t worry—you’re in goodcompany. Some of the world’s most experienced data scientists sayit’s difficult to separate truth from fantasy in conversations about AI.“There’s always been a lot of hype surrounding AI. One of the earlydefinitions was ‘AI is all the stuff that doesn’t work yet,’ and there’s afair bit of truth in that,” says Ted Dunning, a seminal figure in the datascience community and early pioneer of big data applications.

AI covers a broad swath of territory from machine learning (ML) toneural networks to logistic regression. Natural language processing(NLP) and robotic process automation (RPA) are commonly tossedinto discussions about AI, along with terms like deep learning (DL),reinforcement learning (RL), and convolutional networks.“People use grandiose terms when they talk about AI, but what’simportant to remember is that we’re trying to solve serious problemsand do something useful,” says Dunning, who serves as chiefapplication architect for MapR, a data platform for AI and analytics. “Idon’t care whether the solution looks intelligent or not. If it solves acomplex problem we couldn’t solve before, that’s all that reallymatters.”What Artificial Intelligence Is and Isn’t“Think of AI as an airplane,” says Lynda Chin, a medical doctor andformer department chair and professor of genomic medicine atthe University of Texas MD Anderson Cancer Center, as well asscientific director of the MD Anderson Institute for Applied CancerScience. “An airplane will get you from Point A to Point B, but youhave to know where you are going and how to fly an airplane.”Like flying an airplane, using AI effectively requires prodigiousamounts of training and practice. “When a new surgical tool isinvented, surgeons cannot simply begin using it on patients,” saysDr. Chin. “They need to train and practice first. It’s the same with AI.”Modern technologies such as airplanes and advanced surgicaldevices have changed our lives dramatically. Yet they haven’teliminated the basic needs they were created to address. People stillneed to travel and when they get sick or injured, they want to getbetter.AI is a relatively new invention. It is not, however, a philosopher’sstone that will magically turn lead into gold. Like most inventions ofthe human mind, AI will make our lives more convenient, but notnecessarily easier or less complicated.

“AI is a very powerful tool that can help human beings in routinephysical and intellectual tasks,” says Vijay Tallapragada of theNational Oceanic and Atmospheric Administration (NOAA), whichprovides weather forecasts, storm warnings, navigationalinformation, and scientific data to public, private, and academicorganizations.Tallapragada heads the Modeling and Data Assimilation Branch atNOAA’s Environmental Modeling Center in College Park, Maryland.He’s also acting chief of NOAA’s Coupling and Dynamics Group. Asa practicing data scientist, he watches developments in AI veryclosely.“With AI, you can quickly scan a large database of images orrecords, rapidly classify multiple objects of various kinds, anduncover hidden relationships in vast amounts of data,” he says. “Butit’s not a universal key that can open any door.”AI at a GlanceWhat it can do …What it cannot do …Scan quickly through big data and find records or images that meet prespecified conditionsSmoothly manage challenges posed by “large problem spaces” such as autonomous driving and complex robotic manufacturing scenariosReveal hidden patterns and subtle relationships in large quantities of dataReplace high-skill workers, team leaders, and executivesProvide scientists and marketers with fresh insights and ideasThink for itselfAdaptive Business Process TransformationFrom an organizational perspective, AI is ushering in a new wave ofbusiness transformation. In Human + Machine: Reimagining Work inthe Age of AI, coauthors Paul R. Daugherty and H. James Wilson listthree waves of transformation:

Standardized. Assembly lines for mass manufacturing of productsfor global markets. Automated. Business process reengineering and digitalization tocreate new business models and new industries. Adaptive. Innovative, ongoing partnerships between human andmachine intelligence to create continually evolving products andservices for digitally connected markets.We’re entering the third wave now, in which the relationshipsbetween people and machines will evolve continuously for decades.In other words, the nature of work will evolve to match the pace oftechnology development.“The third wave has created a huge, dynamic, and diverse space inwhich humans and machines collaborate to attain orders-of-magnitude increases in business performance,” write Daugherty andWilson.For many, the idea of keeping up with artificial intelligence and otheradvanced technologies will seem frightening. But the greater risk isignoring them or misunderstanding their potential value. Like it ornot, we are developing symbiotic relationships with our machines.The quality of those relationships will depend heavily on our ability tounderstand the potential—and the limitations—of machineintelligence.Debunking Myths About Artificial IntelligenceEven before the term artificial intelligence was coined by computerscientist John McCarthy in 1956, people have been fascinated by theidea of “thinking machines” and “electronic brains.” Smart robots,whether good or evil, have become stock characters in sciencefiction; AI itself has become a virtually inexhaustible source of legendand lore.The dense thicket of mythology that has sprung up around AI is notparticularly helpful to practitioners in the real world, says JoshPatterson, an experienced data scientist who consults on big data

applications and applied machine learning. AI is neither alive norself-aware, Patterson says.“AI today in real terms is applied machine learning,” he says. “Folkswho over-market machine learning to be ‘general artificialintelligence’ do the entire computer science industry a disservice.Machine learning is classification and regression, and in no waymatches up to ephemeral aspirations of an all-knowing, self-awaresystem.”If AI isn’t what everyone seems to think it is, then why all the hoopla?What set the stage for the sudden popularity of AI?“What changed was the exponential increase in computing power,coupled with a fall in costs, and the mass proliferation of data inrecent years. This enabled data science to alter the paradigm of AIresearch, supplanting a field that was once logic-based with one thatsimulates learning through statistical models—we call this machinelearning,” explains Daryl Kang, a data scientist at Forbes and agraduate of Columbia University’s Data Science Institute.Machine learning, which essentially enables software to “learn” fromdata, is not a novel technique. “I do not make as strong a distinctionbetween AI and machine learning as some people do,” says EllenFriedman, principal technologist at MapR. “I see AI as a trendierterm and maybe a subset of machine learning.”Both terms and the processes they represent, she notes, “have beenaround for a long time—some of the hype, especially around AI, isnew, but artificial intelligence and machine learning are not new.”Still, a lot has changed recently, she adds, including:Much larger scale and wider variety of data to inform machine-madedecisions;Better and more practical technology and architectures to deliver thedata and models;Better algorithms and, in some cases, pre-built models that can becustomized, leading to dramatically better results on some classically

difficult problems such as vision or speech recognition andtranslations;A much broader recognition of the value and feasibility of AI andmachine learning; andAs a consequence of these changes, AI has been democratized andis more widely used than ever before.For LOB managers, the rise of AI ramps up expectations and fuelsdreams of continuous improvement in almost every area. Don’t besurprised when the C-suite peppers you with questions about howyour teams are deploying AI and advanced analytics to createcompetitive advantages and efficiencies for the company.Remember, AI is no longer considered pie in the sky. It’s not “overthe horizon” or “around the next bend in the road.” AI has left thelaboratory and is already proving its value in areas such ashealthcare, education, transportation, public safety, retailing,marketing, telecommunications, entertainment, manufacturing,construction, energy, pharmaceuticals, supply chain management,and predictive maintenance. All of us have a stake in making surethat our organizations make the most of it.Finding Needles in HaystacksAI’s ability to find unseen patterns in huge mountains of data makesit especially valuable to scientific researchers and commercialmarketers. For researchers, AI promises to deliver a new generationof tailor-made drugs and medical therapies. For marketers, AI offersa bottomless treasure chest of golden opportunities for selling, cross-selling, and upselling.Applying AI to retail transaction data sets, for example, can revealprecisely which combinations of products shoppers buy when theygo to a supermarket or home furnishings store. AI-generated insightsenable retailers to stock products when and where shoppers aremost likely to buy them. AI also allows retailers to offer discounts andschedule special sales events without having to guess about thebuying habits of their customers.

AI has the potential to transform many aspects of our lives. But it stilltakes human judgment to recognize the value of the insights AI canreveal. In other words, AI can find patterns in data that are invisibleto human eyes, but not every pattern discovered by AI is inherentlyvaluable. An AI itself has no clue whether the patterns it discoversare important or relevant. To an AI, all patterns are purelymathematical.“Maybe the simplest view of AI is that it is machine-assisted decisionmaking,” says Friedman. “AI is not magic. It requires good-qualityand appropriate data, an understanding of that data, a well-formedquestion or basis for analysis, the right algorithm or algorithms, a tonof efficient logistics for data and model management, and a way totake practical action on the output of the AI process.”Areas of rapid AI growth and adoptionHealthcareEducationTransportationPublic SafetyRetailingManufacturingMarketingEntertainmentEnergyPharmaceuticalsTelecommunicationsSupply Chain Management and LogisticsPredictive MaintenanceWill AI Replace Your Employees?

The rise of AI has also led to fears of massive unemployment andeconomic dislocation. Undoubtedly, AI will have a major impact onthe job market. Some areas of work will be affected more quicklythan others.At call centers and help desks, the changes will be drastic. Manyjobs will disappear and the remaining jobs will be transformed.Accountants, paralegals, cashiers, and welders may largely vanishfrom the workforce. The changes will also affect people withadvanced degrees and certificates, such as radiologists, insurancebrokers, and financial planners.The bottom line is that AI will take over thousands of routine orrepetitive tasks now performed by humans. If your job can beautomated, it will be automated. Wholesale automation of customerservice operations will likely wreak economic havoc in countries suchas India, the Philippines, and Poland, which have invested heavily incall centers.Automation will affect people at every strata of the workforce. For themoment, robotic process automation (RPA) focuses mainly on highlyrepetitive tasks. But when AI is fully baked into process automation,all knowledge workers will feel the pain.The good news is that shiny metal robots with glowing red eyeswon’t be taking our jobs. The bad news is that AI chatbots, whichseem cute and harmless, are likely to eliminate or displace manyroles in the modern workplace.For example, it seems unlikely that the role of administrativeassistant will survive the next wave of chatbot development. “Soonwe’ll be saying, ‘Tell your bot to call my bot,’ when we need toschedule a meeting or set up a video conference,” says a leadingtechnology executive.New areas of bot specialization are already emerging within the fieldof data science. In an excellent column on the impact of AI on labormarkets in the U.S. and India, Pulitzer Prize–winning columnistThomas Friedman writes of new jobs such as “digital conversationdesigners” and “voice conversation designers.”2

For data scientists specializing in AI chatbot design, the goal iscreating bots that can accurately gauge a customer’s intent beforehanding the interaction off to a human. Chatbot designers measurethe amount of time it takes before a human agent must interveneand create a score that serves as their “AI batting average,”Friedman writes.From a cost-benefit perspective, it makes sense to automate rolesthat don’t require years of experience. But eliminating those rolescan send dangerous ripples through organizations and cultures,since many people begin their careers in entry-level jobs. AI-powered automation might be a logical choice for manyorganizations, but there will be legions of unintended and unforeseenconsequences for future generations of workers.Is There a Difference Between AI and DataScience?Which came first, data science or AI? Unlike the chicken–eggconundrum, this one’s easy to answer. Data science has beenaround in one form or another for centuries, while AI dates back tothe 1950s. Data science is foundational to AI; without data science,there would be no AI.But there are critical differences. “Data science is the study ofextracting value from data while AI is the ability of machines toperceive and to adapt to changes in their environment throughactions that optimize their objectives,” Kang says.Here’s a rough visualization: imagine a pyramid with statistics at thebase, data science in the middle, and AI at the top. If you want to getfancy, add a layer of machine learning in between data science andAI.“Data science guides everything that sets up the machine learning,”says Sandy Silk, director of IT Security Education and Consulting atHarvard University. “We need the data scientists to figure out theappropriate algorithms and data models to use, validate that theunderlying data sets are large enough and diverse enough to

accurately reflect the population they’re intended to serve, and toverify that the produced results are accurate and not biased.”For example, let’s say you apply for a home mortgage loan from abank. If the bank’s machine-learning model recommends againstapproving your application, it should be required to explain why.“There needs to be clarity about the data elements that led to theresult,” Silk says. “The model can’t be a black box of mystery.”In Weapons of Math Destruction, mathematician Cathy O’Neil tellsthe story of a school district that hired a data science company toanalyze the performance of teachers. Based on the company’sanalysis, the district fired some of its best teachers. How did thathappen?It turned out the company’s algorithms weren’t up to the task ofevaluating teachers in real-life classrooms. But when the firedteachers protested, the district sided with the algorithms.Algorithms are basically sequences of instructions for computers tofollow. As O’Neil points out, you cannot appeal to an algorithm.“They do not listen. They do not bend. They’re deaf, not only tocharm, threats, and cajoling but also to logic—even when there isgood reason to question the data that feeds their conclusions,” shewrites. Human victims of bad algorithms “are held to a far higherstandard of evidence than the algorithms themselves.”But wait, it gets worse. Algorithms can reflect the biases andprejudices of the people who write them. A biased algorithm has noway of knowing that it’s biased, which can lead to all kinds ofunpleasant outcomes for people applying for everything from carloans to parole from prison.Skills You Need to Become a Data ScientistDespite the aura of uncertainty surrounding AI, we are clearlyentering an era in which machines are getting smarter and datascientists are rapidly becoming indispensable. If you have datascience skills, your prospects look very good.

In 2012, the Harvard Business Review published an article with theprovocative title, “Data Scientist: Sexiest Job of the 21st Century.”The article was widely circulated and cited, setting off a chainreaction of chatter that has yet to fully subside. Follow-up articles inother publications described data scientists as mysterious, powerful,and all-knowing beings who would change the face of business andindustry.What are the skills you need to become a data scientist? The answerdepends on whom you ask.A good data scientist should be familiar with basic statisticalprinciples, advanced statistics, and various types of data, includingbig data, says Tallapragada. “Data science is still partly art, so youneed to develop some intuition, which only comes from experience,”he adds.Drew Conway is the head of data and strategy at Augury, a companythat predicts the visual appeal of websites across demographicgroups. Way back in 2010, Conway created a Venn diagramdepicting the “basic” skills required of a data scientist.His diagram indicates that math and statistics are important, butthey’re not the only skills you need to succeed. Thinking creativelyand understanding the impact of your work on the outside world arealso essential skills for a data scientist.“Data science is a team sport,” says Tian Zheng, a professor ofstatistics at Columbia University and associate director for educationat Columbia’s Data Science Institute. “There is a lot of collaborationbetween data scientists, data engineers, and domain experts. Datascientists bring creativity and insights to such a collaboration,translating a domain question to a data question, exploring andnavigating multiple data sources, interpreting trends and patternsfound by machine learning algorithms, identifying and addressinglimitation of observed data, and decomposing and scoping a data-driven solution for a business/real-world problem into a data scienceworkflow.”

From Zheng’s perspective, each data science workflow is asequence of decisions on data sources, feature-engineeringprocedures, computational infrastructure, algorithms, models, andtools for delivering products. Data scientists are the “humans in theloop” who make these decisions, she says.It’s unlikely the role of data scientist will be automated out ofexistence anytime soon. That said, the duties and responsibilities ofdata scientists inevitably will change and evolve over time.“Currently, data scientists still spend a lot of time and effort onscripting their own machine learning codes and building their ownvisualizations, often from scratch,” Zheng says. “As computationaltechnology develops more data science modules that can streamlinesome of the most common data science operations, data scientistswill become more like designers of pipelines for solving problems.”For the foreseeable future, data scientists will remain the “humans inthe loop,” she predicts.

AI is Part of the Emerging DARQ StackWithout overstressing the point, it’s clear that data science and AIare transforming many aspects of our lives. But they aren’t the onlyfactors in a tsunami of change that’s sweeping over global markets.For the past four or five years, technology journalists like me havebeen writing about the SMAC stack, which stands for social, mobile,analytics, and cloud. Today, we’re writing about the DARQ stack,which stands for distributed ledger (DL), artificial intelligence (AI),extended reality (XR), and quantum computing (QC).Undoubtedly, you will be reading and hearing a lot about the DARQstack in the years ahead, until it’s replaced by a new set of essentialtechnologies. For data scientists, the emergence of the DARQ stackis good news, since it marks the acceptance of AI as a fundamentaltechnology layer that cannot be overlooked or ignored.The transition of AI from the margins of technology to themainstream of society is not a trivial occurrence, and all of us haveringside seats at what promises to be a truly game-changingmoment in human history.Yet the DARQ stack is merely the tip of an iceberg. If you really needsomething to worry about, consider how the next generation ofproducts and services built on the DARQ stack will completely alterour traditional perceptions of reality.A decade from now, give or take a few years, we’ll be using DARQtech to simulate or fake anything we can imagine. Fake news will bethe least of our problems. We’ll have fake identities, fake pets, fakefaces, fake homes, and fake lives. In a world in which our basicnotions of reality can be easily manipulated by technology,understanding data science might be the key to sanity and survival.Meantime, leaders at every level of the organization must becomeincreasingly knowledgeable about tools and solutions for continuallearning and development. Today’s workforce expects employers toprovide opportunities for growth and career development, especiallyin “hot” fields such as data science and AI.

But you don’t have to be a data scientist or an AI savant to see thebig picture: organizations that don’t provide employees with the toolsand capabilities they need to advance their skills continually will beunable to compete successfully in tomorrow’s economy.AI is now inextricably woven into the digital transformation process,and it should be treated as a primary component of everytransformational strategy.Notes1 Mike Barlow is an award-winning journalist, prolific author, andbusiness strategy consultant. He is the author of Learning to LoveData Science and coauthor of Smart Cities, Smart Future. He isalso the author of many articles, reports, and papers on topicssuch as artificial intelligence, machine learning, digitaltransformation, and IT architecture.2 “A.I. Still Needs H.I. (Human Intelligence), for Now,” by ThomasFriedman, Opinion, The New York Times, Feb. 26, 2019.

AFTERWORDAs a futurist, I spend most of my time listening to people describewhat they are most excited about; what they are most apprehensiveabout; and how they are thinking and/or preparing for what comesafter what comes next.The work of nonfiction you have in your hands will provide you withmost of the information you need to successfully guide yourself andyour organization through the many pitfalls associated with businesstransformation.Historians, anthropologists, and paleo-sociologists will tell you thatthere are two traits that differentiate Homo sapiens from the rest ofthe biomass:Trait #1: the ability to contemplate multiple futures, over varying timeframes.Trait #2: the ability to collaborate/cooperate at scale (i.e. shareknowledge between tribes and across generations).The author of this book has one of the most interesting stories and isone of the most gifted storytellers I have met in the last 25 years. Arespected thought leader, bordering-on-prescient technologist, andsuccessful senior executive at one of the iconic companies of theday, Yuri Aguiar has distilled thousands of hours of research withcompanies doing digital transformation right, wrong, and uniquelyinto an accessible compendium of stories, frameworks, tools, andtechniques you can apply to your personal circumstance. To choosenot to take advantage of this treasure trove of knowledge borders onmalfeasance.Aristotle—essentially the birth-father of knowledge in the Westerncanon—always started his path of knowledge creation in a particularfield by inventorying and then summarizing a range of endoxa, “theviews of fairly reflective people after some reflection.” Yuri has

interviewed some of the most interesting and noteworthy actors onthe global economic stage.The Chinese have an aphorism, “To know the road ahead, ask thosecoming back.” Yuri has camped out on the road back fromsuccessful digital transformation and interviewed most of thesurvivors.Yuri is a transformation artist turned scientist. He was an earlypioneer in transformation, beginning initiatives before the topic was“discovered” by consultants, academics, journalists, and researchanalysts. Having extensive hands-on, in-the-trenches, “This-has-to-work-or-there-will-be-career-con- sequences” digital transformationexperience, he is uniquely qualified to synthesize the abundant datanow available. He is probably one of the leading thinkers onpragmatic digital transformation.Data about Digital TransformationEvery organization, every executive, every individual, and everyobject is on a digital journey. Sadly, most have no map, no compass,and bad shoes (i.e. there is no explicitly stated digital endpoint; thereare no metrics to assess how the journey is going; and the gear,skills, competencies, and mindsets required to make the journey aresorely lacking).Not digitally transforming is simply not an option. Data collected atthe Digital Value Institute (tDVI) indicates that less than 10% ofcompanies in the global 2000 believe their current business modelwill remain economically viable over the next 10 years. Everybusiness leader has to become a digital leader, creating andcommunicating a vision for one’s enterprise.Boards of directors are pressuring CEOs to “get busy” with digitaltransformation. Money—big money—is being spent on digitaltransformation. In the early stages of GE’s digital transformation, myfraternity brother at Dartmouth College, CEO Jeffrey Immelt,invested over $200 billion in digital initiatives. In 2019 global

investment in digital transformation initiatives is expected to reach$2.2 trillion (∼$1.3 trillion was spent in 2018).There are big benefits to successfully digitally transforming yourenterprise. Subscription research firms forecast that digitaltransformation will generate $18 trillion in added business value(IDC) and generate 36% of overall revenue by 2020 (Gartner).Digital transformation initiatives have stock price impact. DigitalValue Institute research indicates that a subset of the 3% of thepublicly traded general business population who successfullytransformed achieved a 300% stock price increase.Truth be told, CEOs don’t really care about the particulartechnologies that enable digital transformation (i.e. analytics, artificialintelligence, augmented/virtual reality, big data, blockchain, cloud,machine learning, Internet of Things/IoT, robotics, search engineoptimization/SEO, 3D/4D printing, voice-friendly apps, and/orwearables). They care about the benefits (e.g. stock price increase,market share expansion, cost structure reduction, riskminimization/improved risk management) digital transformationenables.Few companies are achieving the results envisioned. Surveys andinterviews indicate that only 14% of the companies attempting todigitally transform have been able to generate “substantiveimprovements in business results.” Many organizations arefrustrated with the lack of results and pace of digital transformationthey are experiencing. The consensus of analysts is that a third oforganizations attempting digital transformation will fail at it.Catastrophic failure to achieve digital transformation can result inorganizations becoming symbols/icons of ineptitude:“Kodak-ed” (i.e. failing to jump to the next technological wave);“Netflix-ed” (i.e. failing to adapt to changing customer buyingpatterns);“Amazon-ed” (i.e. having digital competitors render product/servicesirrelevant);

“Tesla-ed” (i.e. having charismatic outsiders co-opt criticaldestination points on digital horizon);“Uber-ed” (i.e. offering subpar customer experiences); and mostrecently,“AI-ed” (i.e. having algorithmic competitors outsmart incumbentofferings).Everything possible today was at one time impossible. Everythingimpossible today may at some time in the future be possible. Thefuture is not something that just happens to us.The future is something we create. Digital transformation is how wecreate the future.Digital competence/digital maturity level is being measured. TheFletcher School at Tufts has created—on a nation-state level—ametric for measuring a political entity’s digital maturity (The DigitalEvolution Index or DEI). The metric parses nation-states into fourdigital categories: Stall Out: countries which are losing momentum and falling behind. Stand Out: countries showing high levels of digital development. Watch Out: countries facing both significant opportunities andchallenges. Break Out: countries having the potential to develop strong digitaleconomies.Most digital transformations are inwardly focused on improvingexisting business processes—not on launching new products orservices or interacting with external partners through digitalchannels. Domino’s Pizza Inc. has embraced digital, emphasizing allthe ways you can order pizza with minimal human and maximaldigital contact. It’s introduced myriad ordering modalities—Facebook, Twitter, Twitter with emojis, Apple Watch, voice-activated,and “zero click.”

Customers can track their pizzas online, starting from as they’rebeing made all the way to delivery. Digital has been good forDomino’s. Since the end of 2008, its share price has increasedsixtyfold. Domino’s went from having a 9% share of the pizzarestaurant market in 2009 to 15% in 2016.1 They deliver over amillion pizzas a day. Four-fifths of Domino’s sales come throughdigital channels.The time to perform a digital transformation is now. Ninety percent ofthe global 10,000 have embarked on at least one “digitalexperiment.” Eight-five percent of enterprise decision-makers believethey have two years to integrate digital initiatives before fallingbehind their competitors. Fifty-five percent of companies think theyonly have one year. Organizations need to realize while they muststart now, the transformation journey is a lengthy one (a marathon,not a sprint). Four out of five executives say their organization will bea digital business within three years.Every successful digital transformation made information moreavailable inside and outside the organization. Finland has gone sofar as to pass a law stating that Internet access is a birthright.Many digital transformations gave the customer significant voice inproduct and service design.Every successful digital transformation created and managed a clearchange narrative (description of, case for, and feedback regardingthe changes being made). In many instances, these narrativesincluded compelling “anchor visuals” (pictures that helped explainthings). Cognitive scientists tell us that visuals communicateinformation to the brain 60,000 times faster than text.IT can become an obstacle to digital transformation. Legacy systemsdo not support—were not initially designed for—the nearly instant,free, and precise ability to connect people, devices, and physicalobjects anywhere. Without optimizing how IT itself operates within acompany, efforts to improve internal and external systems andprocesses with cloud computing, artificial intelligence, automation,and other capabilities risk hitting a bottleneck that leaves the entire

business lagging behind competitors. Less than 20% of businessleaders feel like they have the right technology in place.Digital transformation requires executives outside of technologybecoming comfortable with technology. A survey conducted by theMIT Center for Information Systems Research showed that out of1,233 publicly traded companies with revenues over $1 billion only24% had board members who were classified as technology experts.A 2018 HBR survey asked 5,000 board members around the worldwhat activities they thought their boards were good at. Technologyand innovation ranked 17th and 18th. A variety of comfort-expandingmethods including technology petting zoos and curated boardmember roadtrips to technology conferences have beenexperimented with.Traditional processes of direction setting, resource allocation, andsystems/capabilities building are no longer sufficient. Theconventional, linear, and time-consuming “wait-and-respond”approach to strategy—where plans are created and finalized in astaff portion of the enterprise, subsequently distributed for commentto the IT department, and then pushed through an industrial-ageprocurement process—are out-of-step with the pace of modernbusiness.During a digital transformation, incumbent companies may need toupgrade the digital skills of the enterprise. A variety of techniqueshave been deployed:Reverse mentoring (younger, digitally savvy employees coach moreseasoned executives).Company-wide training programs (with bespoke uplift curricula).Digital certification programs.Tools and TechniquesHonest Assessment

What is being measured? Where is money really being spent—running the business (activities necessary to compete in currentmarkets), growing the business, or transforming the business(changing how we operate/changing how the industry operates)?Percentage of budget being spent maintaining systems of record.Percentage of budget being spent maintaining systems ofengagement.Percentage of resources and budget allocated to identifying, testing,and validating new technologies.Percentage of resources and budget allocated to new businesses oracquisitions.Inventory of skills and capabilities (gap analysis—what you have andwhat you need).Percentage of revenue generated by digital products/services.Number of innovation ideas generated.Number of innovation ideas that resulted in new products/services.Time to move from ideas to prototype to market.Competence in four foundational digital areas: Data analytics Privacy and security management Digital roadmapping Results trackingA big mistake made by many organizations during a digitaltransformation is to measure activities, not outcomes. For example,call centers should measure the percentage of customer problemssolved, not how quickly they ended the call. A robust and rapidlyevolving set of metrics are available to guide transformation efforts:KPIs (Key Performance Indicators)OKRs (Objectives and Key Results)

ROIs (Returns on Investment)NPSs (Net Promoter Score—management tool used to gauge theloyalty of a firm’s customer relationships)Industrial-age macro-measurements are probably not giving us theright big-picture view of the transformation landscape. How do youmeasure the value of the increasing amount of free goods availableonline, including Wikipedia articles, Google maps, Facebookinteractions, smartphone apps, and YouTube videos?Shared VisionDigital transformation requires a shared vision. Fumbledtransformation efforts can seem like the Indian parable of the fiveblind men and the elephant (where each tribe in the organizationfeels a different part of the animal and comes away with a totallydifferent picture of the beast). You can’t ask the IT guy, “What isdigital transformation?” and have him/her geek out about the latest inmachine learning and cloud portability. Neither can you have theoperations person perceive digital transformation as just being abouta 1-click customer experience. If the line-of-business person onlythinks in terms of business model change (e.g. moving from productsale to services), you will have problems.The economist John Maynard Keynes reminds us, “The real difficultyin changing any enterprise lies not in developing new ideas, but inescaping from the old ones.” As a coxswain at Dartmouth I learnedthat it is much easier to have everyone row harder when there is ashared vision of where the finish line is.A Managed Transformation ProcessThere are many aspects to a digital transformation (e.g.knowledge/vision, persuasion, decision, implementation/informationsecurity and confirmation/communication). Each has to be measuredand managed.Having a few digital initiatives underway does not constitute a digitalstrategy. Yuri has created a simple five-step process called “SMART

Transformation Process”:S StrategyM MappingA AlignmentR ResearchT TransformCustomer ExperienceOrganizations need to map out the exact steps customers gothrough when engaging with your business. With this customerjourney map completed, one can launch a discovery process aimedat identifying which emerging technologies will enhance keytouchpoints in their journey.Many organizations have stalled at what I call the “simple digital”phase of digital transformation. They have used the rich set oftechnologies available to improve how the organization interacts withcustomers. This is great, but this is not the endpoint of digitaltransformation.Organizational messages have to be personalized. The term of artcurrently being bandied about is hyperpersonalized. This is not aboutthe company. It has to be about the customer. Consumersincreasingly expect their world to be “smart” and seamlessly adapt totheir taste and habits.Consumers at the front-edge are evolving—while digital natives askwhat they can do with technology, data natives are more concernedabout what technology can autonomously do for them. Digital nativesuse the Starbucks mobile app. Data natives want the app to knowtheir favorite drinks—and when to suggest a new one.We are migrating beyond our current parent-to-child relationship withtechnology where we need to tell it what to do very specifically andcorrect often.

Employee ExperienceThe objective is to ensure that employees willingly and effectivelyembrace relevant, high-impact technology, rather than feelthreatened by it. One has to authentically deal with concern/fearregarding job loss associated with digital transformation initiatives.Data about DataMichael Porter, an economist and researcher who teaches atHarvard Business School, observes that most workers today aresimply overwhelmed by data: “The machines are smart andconnected, but the people are just sitting out there wondering what’sgoing on.” Is there someone in the enterprise thinking about how keyconstituencies (both internal and external to the enterprise) thinkabout data?Everything generates data. The question is—are you getting fullvalue from that data stream? GE CEO Immelt once observed, “Alocomotive today is a rolling data center.” Data boffins lament that in2018 only 1% of the data generated was effectively utilized. Theyexpect this to rise to 3–4% by 2020. Thirty percent of largeenterprises are expected to commence generating Data-as-a-Service revenue by 2020.To enable future experiences that exceed customer expectations willrequire being able to digitally identify the customer, and allow thecustomer to own, understand, consent to, and share their data.Some organizations have gone so far as to encourage/enablecustomers to create and manage their own data sets regarding therelationship with the enterprise.Data within the enterprise has to be cleansed, de-siloed, and shared.Structural AccommodationsMany organizations (∼60%) have created new business units/newexecutive positions specifically dedicated to digital. Spanish bankBanco Bilbao Vizcaya Argentaria SA established a separate legalentity several years ago dedicated to data science.

Some organizations have created new digital roles (e.g. chief digitalofficer). Less than 25% of large global enterprises have appointedchief digital officers, chief data officers, or digital ambassadors—Barclays has created a “Digital Eagles” designation fortransformation evangelists.Digital IdentityIn a simpler time (the eighteenth, nineteenth, and twentiethcenturies) food was a universal identifier. Jean Anthelme Brillat-Savarin summed this up with, Si tu me dis ce que tu manges, jepeux te dire qui tu es (“If you tell me what you eat, I can tell you whoyou are”).Today how you interact with information (e.g. the technologies youuse, how and to what purposes you use them) defines who you are.Sheryl Connelly, a friend who is a futurist at Ford Motor Company,believes, “Since the Great Recession, status is not found in stuff.Status is having information.”In 1993 Peter Steiner created a cartoon with the caption “On theInternet nobody knows you’re a dog.” In 2020 and beyond, suchanonymity is impossible. Today we all live in a digital glass house. Afellow futurist interpreted this as implying, “Since we are all naked,we might as well be buff.” I think what he means by this is thatbecause how we interact with information is so transparent andessentially defines us, we might as well be aware of and proud of ourdigital behaviors.My former boss, ur-Futurist Alvin Toffler, forecast: “The illiterate ofthe 21st century will not be those who cannot read and write, butthose who cannot learn, unlearn, and relearn.” Reading this book willaccelerate you and your organization down the digital transformationlearning curve.Thornton MayFuturist, author of The New Know:Innovation Powered by Analytics

Note1 https://www.bloomberg.com/opinion/articles/2016-12-27/domino-s-delivery-tech-goes-from-dial-up-to-drones.

ABOUT THE AUTHORYuri Aguiar is the chief innovation and transformation officer at theOgilvy Group. Prior to that he was the strategic portfolio director atthe global technology unit supporting companies within the WPPGroup.He has been a CIO, CTO, and director of worldwide technologyoperations over his career as a global leader in business technology.He prides himself in leading small efficient teams of independentthinkers who challenge the status quo.Yuri recently completed his Masters in Digital Marketing to betterunderstand challenges around consumer data. His thesis, TheEvolution of Consumer and Marketer Responses to TechnologyEnabled Marketing, studied consumer habits across multiple socialmedia channels, geographies, and demographics. His most recentundertaking has been the design and testing of the SMART DigitalTransformation© process in order to create a simple narrativebetween digital proficiency and technical proficiency. He is currentlypursuing interests in the data science area with experiments inadvanced content intelligence while working on a patent aroundaugmented reality.He also pursues inspiration through hobbies that find expressionoutside of work. An avid music and aviation fan, he loves spendingdowntime on a flight simulator. Yuri has partnered with colleagues toorganize charity concerts for Breast Cancer, U.S. Veterans, and forvictims of the tsunami in Japan—often performing with the band.A hands-on leader with experience working across three countriesand interacting with countries on every continent, Yuri has writtenthis book with the intent of sharing his own work experiences andlessons learned from very intelligent people along the course of hiscareer thus far. And a testament, he hopes, for his own businessmotto: “Good execution is the key to a great strategy.”

INDEX Accountability, 75, 79–81, 98Accounting, management, 24Adaptive business process transformation, 193–194Adaptive corporate culture, 68Adaptive transformation wave, 194Adoption rates, 40f, 44Affirmative responses, absence, 30Agile organizations, services purchase, 141Agility paradox, 135–136, 139Algorithms, 148, 196, 202, 203Align (process), 130Analytic audience, 38Analytics, 97, 146Anchor visuals, 215Application (OSI model layer), 187Application programming interfaces (APIs), 187Applications, duplication/protocols, 179, 186Artificial intelligence (AI), 13, 170, 185, 190–207chatbots, 131, 200–201expression, 122problem, 122–123, 189tool (Amber), adoption, 87

Audiences, 38, 39f, 115–117Audit engagement (RPA stage), 134Augmented reality, virtual reality (confusion), 176Authority, usage, 88–89Automated customer services, 61–63Automated transformation wave, 193Automation, 133, 183–186 Back office, 13, 101–102Back up data centers, presence, 179Benefits identification, 157Best practices, dissemination, 104–105Big data, 177–178, 185Blockchain, 170–172Bots, 131, 135, 200Brainstorming, limits, 35Brand, awareness/building, 117–118, 184, 185Branding, management, 185Build (QRate Model phase), 37

Business, 132–135, 211–212, 217–223competition, intensity, 43complaints, problems, 4decisions (support), technology (usage), 178global business, operation, 47model, threats, 58operations/processes, efficiency/throughput (improvement), 9process re‐engineering/digitalization, 193resources, shift, 11–12results, improvements, 212strategy, impact, 118–120transformation, 144, 153Business as usual (BAU), 165Business process outsourcers (BPOs), risk, 173–174Business‐to‐business (B2B), 3, 61, 106, 114, 142Business‐to‐consumer (B2C), 2–3, 114–115, 142Buy‐in (RPA stage), 134 Calls, making (cost), 48Candidates, interviewing, 91–92Captains, 85, 90, 95, 98Careers, 6, 80, 95Case studies, dissemination, 104–105Change, 51, 57, 64–65, 83, 141–143, 215Chatbots, 61–62, 200

Chief Information Officer (CIO), impact, 20, 23, 24Chief Technology Officer (CTO), vision, 69–70Citizen‐centric city (smart city), 167City led stage (smart city), 167Client engagement teams, impact, 24Client needs, 24–25Cloud, 12, 24, 172, 179–181AI capabilities, 123cloud‐based environments, 120services, sale opportunity, 106Collaboration, 4, 103–115, 122–123Collaborative city (smart city), 167Communication, 4, 49–50, 64, 65–67, 108–109Companies, 67, 150, 151, 216–217position, vision (establishment), 59turnover, high level, 96Competence, 97–98, 218Competition, 43, 71, 152Competitive advantages, creation (potential), 33Competitive environment, changes, 58Confidence, building/usage, 52–53, 88–89Confidentiality, Integrity, and Availability (C‐I‐A), 164Confidentiality, Integrity, and Availability and Safety (C‐I‐A + S), 164Consultants, excess (problem), 157Consumers, evolution, 221

Content contribution, ease, 109Conversations, improvement, 143, 144–145Corporations, examination, 28, 68–69, 95Create (QRate Model phase), 35Creation, 33–34Creativity, 28, 30–31Crisis, management ability, 104Cryptocurrencies, 171–172Culture, examination, 67, 71–72, 149, 155Customer relationship management (CRM) platforms, unavailability,183Customers, 57, 59, 61–63changes, examples/stories, 69–72engagement/learning (generation), Brandwave (usage), 41experience, 220–221needs, 23–25, 61, 68satisfaction, 45–47, 50–51, 51f, 55Customer service operations, wholesale automation, 199Cyber‐physical systems, risk, 162Cybersecurity practices, setup, 145

Data, 48, 177–179, 187, 196–197, 201–205analytics, 218collection, 182deep analysis, 132–133education, 46–51impact, 46–51, 221Data management platforms (DMPs), impact, 183–184Decentralization, business usage, 4–5Deep learning (DL), 191Demand‐side platforms (DSPs), 184Design thinking, 13, 139Desk information, capture/analysis, 47Digital alchemists, term (usage), 60Digital alchemy, 59–61Digital capabilities, development, 156Digital certification programs, 217Digital competence/digital maturity level, 213Digital competencies, 218Digital conversation designers, job/role, 200Digital environment, unfolding, 63Digital Evolution Index (DEI), 213Digital experiences, creation, 145Digital experiment, 214–215Digital identity, 223–224Digital innovations, scaling, 155Digital KPIs, creation, 155

Digital ledger technology (DLT), 13Digitally determined/distraught, 137, 153, 154fDigital operations, shift, 96Digital platforms, 63, 156Digital proficiency, 66, 125Digital road mapping, 218Digital skills, acquisition, 126–127Digital technologies, allowance, 139Digital transformation, 64, 103–104, 140–144, 159, 210–217business requirements, impact, 132–135completion, 57delivery, 14difficulty, 79enterprise‐wide digital transformation, 51importance/impact, 6, 160leading/leaders, 22, 188money, spending, 102organizational needs, impact, 132–135simple digital phase, 220strategic discussions, focus, 86–87term, 144, 169–170Digital value, demonstration, 155Direct accountability, 80Disaster recovery, back up data centers (presence), 179Discipline, 17, 19–26, 39Disruption, 2, 63, 151

Disruptive technologies, impact, 58Distributed ledger (DL), 206Distributed ledger technology, Artificial intelligence, extended Reality,Quantum computing (DARQ), 13–14, 205–207Distributed operations, business usage, 4–5Do‐it‐yourself (DIY) approach, 52–53Domain name server (DNS), connection (loss), 54Domain question, translation, 204–205Dynamic corporate culture, 69 Ecosystems, 77, 95, 101, 156, 180, 185Efficiencies, creation (potential), 33Electronic brains, 194–195Electronic communications, usage, 117Employees, impact, 105, 126, 199–201, 221End‐state digital organizational structure, establishment, 155Engagement, 32–33Enterprise‐wide digital transformation, 51Enterprise‐wide strategy, employment, 155Execution, lessons/strategy, 73, 114–115Executive leadership, 12Expectations, setting, 33Express, popularity/launch, 43–44Extended reality (XR), 13–14, 206External stakeholders, questions, 7

Failover options, 180–181Failure, fear (impact), 28Familiarization, usage, 8–9Fearful acceptance (RPA stage), 133Fears, calming, 8Feedback, 40, 119Finance, management, 24Financial counsel, 18–19Firewalls, setup, 145Flexibility, requirement, 31Focus, 17, 19–26Formal processes, necessity, 30Forward‐thinking companies, impact, 58Foundational technologies, upgrading/streamlining, 9 Gap analysis, 217Global 2000, business transformation (empowerment), 153Global business, operation, 47Global collaboration, 108, 113Global community, 111Global economy, 20, 138–139Global IT processes, improvement, 22Globalization, threats, 58Global/local balance, achievement, 105Global marketing campaigns, response times (increase), 88

Global markets, products, 193Global network, usage, 49–50Global research use case, 117–118Global resources, collaboration, 113Global social intranet, creation, 116Goals/objectives, communication, 73–74Growth, 23, 142, 207 Hands‐on experience, 91Hidden communities, 111Human intelligence, machine intelligence (partnerships), 194Human resources (HR) concerns (RPA stage), 134–135Hypercare stage, 39 Idea bank, 33Idea incubation, 23, 27Ideas, impact, 32, 33, 104Ideate, action steps, 37Ideation, 33–34Impact, bracing, 19, 21Important matrix, urgent matrix (contrast), 23f, 25fIncentives, system (impact), 55Incubation, 23, 24, 27, 40–44Incubator process/sessions, 31–34Indirect accountability, 81Industry, automation, 58

Information technology (IT), 24, 215–216Information, usage, 120–122, 143, 146–148, 215Informed/intelligent audiences, interaction, 115–116Infrastructure, 9, 109, 144Inner engineers, emergence, 33–34Inner strength, hiding, 97–98Innovation, 27–30, 60–61, 138agility paradox, relationship, 135–136digital proficiency, relationship, 125ideas, generation, 218targets, 112–113Instagram (collaboration platform), 3Institutional bias, impact, 87Integrity, transparency (combination), 72Interconnected networks, breakdown, 186Internal investment decision, usage, 174Internal stakeholders, questions, 7Internal technology, investment question, 177Internet, user browsing, 183–184Introversion/discomfort, 97–98Investment decision, 178, 180, 185, 187Issue resolution, usage, 40 Key individuals, idea, 10–11Key performance indicators (KPIs), 155, 218Knowledgeable audiences, interaction, 116–117

Knowledge sharing, 122, 209 Large‐scale transformations, failure, 68Lateral accountability, 81Leadership, 17, 74, 75Learning and development (L&D), 189, 190Left‐brain thinking, usage, 33–34Legacy infrastructure/communities, 9–10, 115Lessons learned, dissemination, 104–105Leverage, usage, 40–41, 142Limited community, 111Line of business (LOB) manager, 189–190, 196–197Logistic regression, 191Long‐term advantages, short‐term victories (impact), 6Long‐term digital roadmap, construction, 155Long‐term success, customer satisfaction (impact), 45–46 Machine‐assisted decision making, 198Machine learning (ML), 120–122, 191, 195, 202, 204–205Machine‐made decisions, informing, 196Malfeasance, 210Managed services ecosystem, 180Managed transformation process, 219–220Managers, one‐on‐one communication, 76

Map (process), 128, 130Marketing automation, 183–186Market viability, action step, 37–38Matrix, examination, 23–24, 23f, 79–80Media, disruptive market shifts, 12–13Meetings, rules, 32Mission, success, 22Models, delivery, 196Momentum, establishment, 35Motivation, culture (comparison), 67Multinational conglomerate, collaboration challenge, 121–122 Nation‐states, digital categories, 213–214Natural language processing (NLP), 191Net Promoter Score (NPS), 218Network (OSI model layer), 187Networks, 49–50, 92–93, 191access, loss, 54connectivity, proliferation, 179management, 24robustness/security, 109Neural networks, 191Non‐dedicated project management, 157Non‐linear TV, 185

Objectives and Key Results (OKRs), 218One‐click customer experience, 219Online inventory, publisher management, 184Open source, 113, 119Open Systems Interconnection (OSI) model, 186, 187Operational cadence, minimum, 157Operational efficiency, fixation, 140–141Operational excellence, 24, 27, 45–47Operational problem, solution, 50Operational technology, management, 24Opportunities, creation, 22Optimism, 21, 91Oracle, usage, 173Organizations, 2–4, 60–64, 132–135, 143–148alignment, creation, 155functions, problems, 157matrix structure, existence, 79messages, personalization, 220obstacles/frustrations, 10operational goals, conflict, 30specialized skills, finding, 104Originality, sacrifice, 28Outcomes, 35, 157Outright rejection (RPA stage), 133 Partner relationships, impact, 78

Partnerships, 75, 77–79Perception matrix, 141fPerformance, judgment, 28Personal devices, proliferation, 151–152Physical (OSI model layer), 187Physical robots, 131Pilot, action steps, 37Planning community, capabilities, 118Platforms, 106, 109–111, 128Portfolio, idea bank service, 33Presentation (OSI model layer), 187Priorities, setting, 25Privacy, examination, 87–88, 218Process, alignment/governance, 133–134, 157Production, action step, 38Products, generation, 206Proficiency levels, imbalances, 127Programmatic advertising, 183–186Project management office (PMO), impact, 40–41Project sponsors, impact, 119Projects, usage, 22, 40–41, 53, 108 QRate Model/template, 34–41, 36fQuality, 75, 82–83Quantum computing (QC), 14, 206

Reactive corporate culture, 68Reality scenario, 175Receptionist, role, 93–95Reinforcement learning (RL), 191Research (process), 130Resolution time, response time (contrast), 53–55Resources, usage, 11–12, 18, 58, 75, 81–82Response times, 53–55Responsibilities, fulfillment, 22Retail transaction data sets, AI (application), 197–198Returns on Investment (ROIs), 218Revenue, generation, 217Reverse mentoring, 217Right‐brain thinking, shift, 33–34Risk, impact, 28–30Robotics, impact, 131–132, 172–174Robotics process automation (RPA), 131–135, 172–174, 191, 200 Science/sentiment, combination, 74–75Scripting, 173Search engine optimization (SEO), 212Security, breach/management, 171, 218Senior executives, AI questions, 190Sensors, usage, 181–182Servers, duplication (reduction), 179Service, examination, 50–51, 82, 182, 206

Service oriented architectures (SOAs), 187Session (OSI model layer), 187Shared vision, 219Short‐term victories, impact, 6Simplicity, importance, 40Simulation, usage, 8–9Single sign‐on (SSO), usage, 110Slack (collaboration platform), 3Smart cities, 159–162, 165–168Smart economy/environment, 165Smartest cities, evolutionary path (stages), 167Smart government/people, 165, 166Smart living/mobility, 165–166Smartness, areas, 165–166Smart robots, impact, 194–195Snapchat (collaboration platform), 3Social collaboration, 102–109, 119–120Social skills, absence, 96Social tools/media, 111–112, 113Soft skills, usage, 12Solutions, usage, 31–32, 39, 43Standardized transformation wave, 193Strategic audience, 38Strategic competitive advantage, 49–50Strategic leadership, 75Strategies, usage, 24, 73–83, 121–122

Structural accommodations, 222–223Structure, 75–77Structure, Partnerships, Accountability, Resources, and Quality(SPARQ), 75–83Subject‐matter expert (SME), search, 106Success, impact/usage, 19–28, 43, 104–105, 113–114, 148–150Supplier‐side platforms, online inventory (publisher management),184Support center data, impact, 48 Target audience, transformation adoption, 11Teams, impact, 21–22, 26, 77–78Technical proficiency, 125–126Technology, 11, 115–116, 119, 131–132decisions, problems, 157ecosystems, design, 77firms, standards (relaxation), 86leveraging, 142tech‐driven stage (smart city), 167usage, 178Test Concept, action steps, 37Tests, conducting, 40Thinking machines, 194–195Training, usage, 8–9, 25Transactions, acceleration, 143, 146–147Transform (process), 130

Transformation, 5–15, 64–68, 148–152, 218–220adaptive business process transformation, 193–194business strategy, impact, 118–120projects, 5, 157technology, focus, 102waves, 193–194work, enjoyment (absence), 82Transformational change, leadership (requirement), 74Transformational efforts, culture (impact), 149Transformational journeys, difficulty, 64Transformational leaders, questions/choices, 12Transformational strategy, 75–76Transformers, selection, 10–11Transparency, integrity (combination), 72Transport (OSI model layer), 187Travel communications, cost (reduction), 49Trust, earning, 52–53Truth matrix, 141f Unconscious bias, impact, 87Urgent matrix, important matrix (contrast), 23f, 25fUser experience (UX), 41, 182 Validate, action steps/QRate Model phase, 35, 37Value, human judgment, 11Vendor lock‐in, 180–181

Venn diagram, creation, 204Video campaign, usage, 47Virtual private network (VPN), 48–52Virtual reality (VR), 174–177Visionary corporate culture, 69Visionary solution, development, 29–30Visionary thinking, 24Visuals, information communication, 215Visual tools, usage, 26Voice‐friendly apps, 212 Wearables, 212Whiteboard, usage, 32Wide area networks (WANs), 179Work, ethic/perception, 71–72, 102, 204Workflow, tracking, 104Workforce, problems/experience, 127, 199Working sessions, usage, 32Workplace (collaboration platform), 33 Zero click, 214

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