Individual written case analysis: Future of the autonomous automobile – A strategy for BMW. Report providing analysis, diagnosis and recommendations for a business

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Strategy module case analysis assignment description for COM 200 Description: Report providing analysis, diagnosis and recommendations for a business case, including application of pertinent concepts/frameworks/tools covered in the strategy module. Submission method: Submit .pdf file via Brightspace by the deadline noted for your section (i.e., prior to the beginning of the class in which the case will be discussed). Submissions will not be permitted after the class discussion of the case so please be mindful of the deadline. Assignment instructions: The Case Method slide deck (discussed in class) provides instructions for case analysis and includes an evaluation rubric comprising 5 criteria. These instructions are reiterated and further elaborated here, as follows: Formatting instructions:

– 4 page limit, single-spaced, inclusive. Please insert page numbers in your document. – Font size: 10 point minimum, 12 point maximum. – Standard 1” (2.54cm) margins. – Font type: Any legible font type is ok. – Use organizing conventions (topic headings, bullet points, numbered lists, etc.) as

appropriate. Figures/tables/charts are not required but may make sense in some instances depending on the type of information you wish to present.

– Either first- or third-person voice is ok.

Content instructions:

– The written analysis should comprise three sections: 1) identification of the key issues/problems that will be the focus of your analysis (1 page or less), 2) analysis of the issues identified in section one (1-2 pp.), 3) recommendations focused on the problems identified and analyzed (1-2 pp.).

– No title page/introduction/background/executive summary is necessary. Begin by identifying the problems/issues that you will focus on.

– Limit your sources to: 1) the case, 2) any readings assigned for the strategy module, 3) any lecture content from the strategy module. Do NOT use sources other than these.

– Use parenthetical citations within the text to explicitly signal when you are applying concepts/tools/frameworks we covered in the module. Since formal references are NOT required, as would be the case for a research paper, there are no special formatting

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requirements for the parenthetical citations. But here is an example of what they might look like:

“Big Wheel burger implements a focused-differentiation business level strategy (Session 4 lecture – Types of Business Level Strategies) as is evidenced by their focus on product quality, local sourcing and sustainable production, and their focus on a relatively narrow Victoria-based market segment that values these product attributes. Their community-based, sustainable approach distinguishes them from other quick service restaurants and provides them with reputational assets that constitute core competencies, which provide them distinctive sources of sustained competitive advantage (Hitt, Ireland and Hoskisson, 2020 – Chapter 3).”

Evaluation rubric (as elaborated in class):

Case Evaluation Rubric

1. Internal consistency, organization, and overall communication style? 0 1 2 3 4 5 Has the student used organizing conventions (e.g., topic headings/subheadings, bullet points and/or numbered lists, diagrams,

tables, variations in font style, page #s) that make it easier for the reader to identify and follow the various components of their

analysis?

Is the paper efficiently written with proper spelling and grammar? Is the paper stylistically sound?

Has the student focused on the key issues and avoided tangential discussion not closely related to the issues at hand?

Are arguments made clearly and concisely, avoiding redundant, wordy or complicated sentences?

Has the student closely followed the directions laid out in the syllabus and provided in class (e.g., suggested

structure/organization; use of appropriate font size, spacing, margins; staying within page limits; refraining from use of

external sources beyond the case, assigned readings and lectures)?

not

applicable

not

applicable

2. Clear problem/issue definition? 0 1 2 3 4 5 Has the student clearly and concisely identified early in the paper the key problems/issues on which their analysis will focus?

Do the problems/issues identified correspond to those mentioned in the case? (are problems/issues that were prominently

mentioned in the case missing?)

Are the problems/issues stated in specific enough terms such that actionable solutions may be developed (i.e., are problems

stated too broadly?)

3. Adequate analysis & diagnosis of problem(s)? 0 1 2 3 4 5 Analysis vs. Description: Has the student provided substantial “value added” and new insights in their analysis or simply

restated information that is already provided in the case?

Symptoms vs. Causes: Has the student attempted to breakdown the problems/issues and identify their underlying causes, or

have they simply provided a list with no real attempt to ascertain why the problems have arisen?

4. Adequate use of analytical concepts/tools/frameworks from this course? 0 1 2 3 4 5 Has the student been explicit in their use of concepts/tools/frameworks (e.g., through using brief citations)? not

applicable

not

applicable

Has the student achieved a balance between breadth and depth? Or is their application either too expansive (and shallow) or

too narrow?

Has the student made full use of the readings and lectures, or focused only on a narrow range of readings/lectures?

Does the application demonstrate adequate understanding of the concepts/tools/frameworks? Are they applied correctly, or

does the application suggest otherwise?

Does the application provide value-added insights into strategic issues in the case, or is the use of tools/concepts/frameworks

too mechanical with few insights into the strategic implications of the analysis? Is the reader left wondering: “so what?”

5. Detailed, compelling, implementation-focused recommendations? 0 1 2 3 4 5 Is there correspondence between the problems/issues identified in the problem ID/assessment section of the case and the

recommendations provided? (i.e., do the recommendations seem unrelated to the problems identified earlier?)

Are problems/issues that were prominently mentioned in the case addressed specifically in the recommendations?

Do the recommendations appear to address the underlying causes of the problems? Do they seem to flow naturally from the

analysis or are they disconnected from it?

Are the recommendations internally consistent? Do they mesh nicely and make sense together as a total ‘package’? I.e., are

they feasible given the information provided in the case?

Are the recommendations implementation focused? Are they specific? Or do they leave the reader wondering “how?”

Poor Acceptable Outstanding

Part 4: Case StudiesC-44

CASE 3

Future of the Autonomous Automobile: A Strategy for BMW

By Olaf J. Groth, Ph.D., Eleonora Ferrero and Aleksey Malyshev

Norbert Riedheim, the head of BMW’s Future Car group, which is situated between BMW’s global strategy, mar- keting and research and development (R&D) units, has just been informed that three automakers have received California permits to test an on-road autonomous auto- mobile: Google testing on a Toyota car, Volkswagen’s Audi, and Mercedes-Benz. BMW did not apply, because the company was in the process of developing a rela- tionship with Baidu, the Chinese Google-like Internet company, to start testing in Shanghai and Beijing. At the same time, Apple announced its electric-autonomous iCar concept. However, BMW has been making signifi- cant investments in the space of autonomous driving and reconfirmed its intentions to lead in this space during its recent shareholder meetings.

Reviewing BMW’s innovation legacy, the state of the autonomous auto ecosystem, and a range of critical uncertainties, Riedheim thinks about potential alterna- tive futures for the evolution of the space. His reflections are driven by a need to present a strategy to the Board of BMW during an upcoming high stakes meeting. What kind of business should BMW aim to be over the next 10 to 15 years? What are its aspirations? What strategy should the company pursue and why?

Introduction1 Norbert Riedheim, the head of BMW’s Future Car group in its global research and development (R&D) division, has just been informed that three automakers have received California permits to test an on-road autonomous automobile: Google testing on a Toyota car, Volkswagen’s Audi, and Mercedes-Benz. BMW did not apply for the permit because the company was

in the process of developing a relationship with Baidu, the Chinese Google-like Internet company, to start testing similar automobiles in Shanghai and Beijing. Given the rapidly changing scenarios, he wonders what position BMW should aspire to, and what their strategy should be.

Riedheim has been in Silicon Valley and knows all those companies well, and enjoys friendly relations with management and even selective partnerships with Google. He knows that in the era of “co-opetition” new technologies and new alliances can change the chess- board of innovation very quickly. In order for the com- pany to remain relevant for the next 20 years, he and his colleagues need to be vigilant and stay on top of the latest developments in the ecosystem of autonomous driving. BMW is focused and committed to developing auton- omous vehicles, as evidenced by CEO Harald Krueger revealing at a BMW’s recent shareholder meeting that the company is gearing up to launch its first autonomous vehicle by 2021: “. . . the BMW iNEXT, our new innova- tion driver, with autonomous driving, digital connectivity, intelligent lightweight design, a totally new interior and ulti- mately bringing the next generation of electro-mobility to the road.”1

Riedheim is excited by this bold vision. He has been at the company for a long time in different positions. Having signed on with the automaker right after his graduate studies in engineering, he spent 3 years as an assistant to the general manager of a factory producing the 3-series sedan, followed by shorter stints in supply chain, marketing and finally product management for the company’s i3-series, the company’s first foray into electric mobility. Having witnessed the engineering and marketing prowess of his employer, he is confident that BMW will master the autonomous challenge as well. Yet, Riedheim knows that the evolution of the autonomous automobile is still in its very beginning stages. How will

1 Some names of certain persons and programs are being used for narrative purposes. They are either fictitious or have been altered. Narrative statements on the part of these persons do not necessarily represent the official views or opinions of the companies mentioned in this case.

Professor Olaf Groth of Hult International Business School, with assistance from Eleonora Ferrero and Aleksey Malyshev (both Hult MBAs, 2014), devel- oped this fictitious case based on discussions with various company officials and from published materials. It is not meant as an endorsement or critique of any particular company, nor intended to be a source of primary data.

Acknowledgement 1 The authors wish to thank the helpful people of Quid.com for making their technology available for the illustrations which appear in Figures 2 and 3 in this case and for their tireless counsel on its use and value.

COPYRIGHT ©2016 Hult International Business School. This publication may not be reproduced, digitized or photocopied without Hult’s permission. To order copies or request permission, contact Hult Publishing at Hult International Business School at One Education Street, Cambridge, MA 02141 U.S.A. or email [email protected]. Copies can be ordered though The Case Centre (www.casecentre.org).

Copyright 2020 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.

Case 3: Future of the Autonomous Automobile: A Strategy for BMW C-45

common feature in luxury and performance automobiles of many brands.

Finally, on January 8th 2014 during the Consumer Electronic Show in Las Vegas, BMW demonstrated its first fully automated car prototypes based on its regular car models.3 The car uses 360 degree radar technology, as well as a set of other sensors including cameras and ultrasound to accelerate, steer, and brake without driver intervention. The company also demonstrated another feature called “Emergency Stop Assistant,” which will pull the vehicle to the side of the road, stop, and acti- vate an emergency call in case the driver experiences an unexpected health condition, such as fainting, a heart attack or a stroke.4 These advancements demonstrated the ability of BMW to stay on top of the new technology.

A litany of prizes and awards recognized BMW’s strengths:

■ Brand reputation: BMW is acknowledged worldwide as a successful carmaker. In 2012, Forbes elected BMW as the most reputable business in the world, and in 2016 it became the second most valuable brand in the auto- motive industry, with a market value of $26.4 billion.5

■ Handling, engines and traction motors: BMW was able to become a market leader in the production of engines, which led the company to win several ‘engine of the year’ awards, in an industry where technology is a top priority and competition is fierce.

■ Information technology integration: BMW was able to integrate technology innovation in its vehicles, winning international prizes such as the Berthold Leibinger Innovation award in 2014 for its laser-light technology and the Autoblog’s 2014 Technology of the Year award for the whole technology suite work- ing together on the BMW i8.6

■ Environmentally friendly vehicles: BMW researched dual fuel engines, hydrogen-driven cars, and hybrid electric cars. Furthermore, 80% of its automobiles are made from recycled and recyclable materials.7 The Brand won the World Green Car of the Year Award in 2015 at the New York International Auto Show8 and at the 2014 Los Angeles Auto Show, BMW was presented with the Green Car of the Year Award from the Green Car Journal for the BMWi3.9

The Ecosystem of Autonomous Driving Today The idea of cars driving themselves has existed for a few decades, since the early days of Tsukuba Lab in Japan in 1977 and the European EUREKA Prometheus project

this new world evolve and how will BMW evolve its position in it? What will he say about BMW’s emerg- ing strategy in his upcoming briefing with an important BMW board member?

He goes back to his desk, and reviews the facts once more.

A Brief History of BMW The automaker got its start as a manufacturer of aircraft engines in Munich, Germany, in March 1916 and turned into a motorcycle and automobile company in 1928.2 Since then, BMW has manufactured motorcycles and cars. It is most well known for its high-quality cars in the upper segment of the market. After WWII the company had to restore its manufacture and reputation. The first car that started a new era for BMW was the 501 model, a famous classic today that quickly established the com- pany as a producer of high-quality, technically advanced cars. Most prominent among its superior engineering capabilities are its engines, which many experts attribute to its early legacy in aero-turbines (“turbine” still being the nickname of its 6-cylinder car engines). In 1973 the factory in Munich started building the BMW 2002 turbo engine. This was the same year that the first oil crisis hit the western world, which had become dependent on cheap gas. Sales of gas-guzzling volume-produced per- formance cars slumped and BMW started to develop a strong skillset in more fuel-efficient turbo-diesel engines.

In 1990 the Bavarians, leveraging their competency in making high-agility, precision steering, introduced a new kind of rear axle that allows the rear wheels to turn a few degrees in the same direction as the front wheel. This improved car stability in turns at high speed, as well as the fun of the driving experience by a BMW driver, which is central to BMW’s value proposition. Since then, few other manufacturers have managed to match this active handling experience, which today is a hallmark of the BMW brand.

In 2001 the company built another competency, this time pioneering cutting edge electronics: a new kind of “head unit” (the control and entertainment console that sits in the center of a dashboard). It was called “iDrive” and it allowed operating the unit easily with a joystick-like knob giving tactile feedback to the driver, without having to take his or her eyes off the road. iDrive had been developed in collaboration with BMW’s Technology Office in Palo Alto, at the heart of Silicon Valley. After an initial period of drivers’ adjustment to the new technology and user interface, the iDrive and various iDrive-like derivatives quickly became a

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Part 4: Case StudiesC-46

in 1987. But only recently, with the advances in com- puter technology, has it become a reality. The 2004, 2005, and 2007 Urban Challenges conducted by the Defense Advanced Research Projects Agency (DARPA) in the U.S. yielded significant advances, with cars eventually completing a 132-mile course successfully as exemplified by the winner of the 2005 DARAP Urban Challenge: Stanford University’s VW Touareg “Stanley.”

The domain of autonomous driving promises stun- ning prospects as well as some key uncertainties. It is at the intersection of large opportunity and the uncertainty of a number of future trends that could affect the domain to take a turn in one direction or another. According to Navigant Research, annual sales of autonomous vehicles could reach nearly 95 million by 2035.10 Morgan Stanley analysts also believe that self-driving cars will change the auto industry.11

At the core of the self-driving car is state-of-the- art microprocessors, i.e., computer chips called Central Processing Units (CPU) or Graphical Processing Units (GPU). GPUs are CPUs that have special capabilities related to processing imagery or graphics. Two major players in the microprocessor technology market are working on the hardware for self-driving cars—Intel,12 maker of CPUs and NVIDIA, maker of GPUs. Recently, through cooperation with these Silicon Valley stars, car manufacturers globally have obtained processing tech- nology that powers critical components to allow them to build self-driving cars. Several companies and research centers13 are working on an even more powerful type of processor—Quantum Computers that will be able to handle massive computational tasks in parallel—a quality essential for the artificial intelligence needed for autonomous driving. With Google recently joining the effort,14 the prospect of creating one (quantum com- puter?) becomes more realistic.

There are different levels of self-driving, which means ‘autonomous automobile’ can mean different things to different people. For BMW to craft a more nuanced strategy, the company will need to draw the distinction between the different modes of the car’s autonomous assistance for the driver:

Self-parking: A car with this feature can park itself without driver intervention. This is primarily a convenience feature for most drivers, but can also aid drivers that are physically impaired. It can help avoiding fender-bender accidents that may increase car insurance costs.

Lane control: Helps the driver to steer though curv- ing highway roads. This is mainly a security feature that helps drivers to avoid potentially dangerous accidents like the car driving into oncoming traffic or veering off the road.

Speed control in heavy traffic: This feature goes a bit further by allowing the driver to let the car nav- igation system accelerate and slow down the vehi- cle when the car moves in a traffic jam. This adds the driver some relief to an otherwise tiring journey through tough traffic conditions.

Fully automated car: The highest level of automa- tion is achieved when the car can drive itself in any conditions, including driving through crossroads and crosswalks with or through traffic lights, making turns, changing lanes, keeping distance with other vehicles, and responding to any kind of emergency situations. In this case the driver inputs the desti- nation into the navigation system and allows it to drive. This feature has been widely discussed as the future of mobility. Most drivers would spend their time being entertained, being social, or being pro- ductive in their cars.

Fully Automated Cars: The Competitive Landscape While BMW15 and Audi16 have already presented proto- types of fully automated cars, other car manufacturers are developing and testing partial autonomy approaches. Toyota/Lexus are working on the concept of assisted driving. Tesla recently announced that it is already installing navigation hardware on its cars,17 although its system is not intended to take full control either, but rather provide assistance for the driver to improve safety. GM first invested $500M in ride-hailing company Lyft and then the two companies announced plans to test a fleet of autonomous Chevrolet Bolt electric taxis on the road within a year.18

Other players are more skeptical: Volvo’s head of R&D, Peter Mertens, has been very direct in saying that the prospect of a driver reading a newspaper or answer- ing e-mails while driving “is a very, very long term vision.”19 The carmaker is concentrated on safety instead, such as object avoidance and more traditional protection such as material strength. Yet, in a surprising twist, that same year, (which year?) Uber’s Founder and Co-CEO Travis Kalanick, started to hire dozens of autonomous auto experts at leading technical institutions, and it was

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Case 3: Future of the Autonomous Automobile: A Strategy for BMW C-47

approaches between car makers is only the beginning of a complex picture: as a seasoned, technology-savvy strategist, Norbert Riedheim knows that competition may not only come from established players, but also from new entrants into a given market: BMW needs to anticipate.

One of these new entrants is Internet giant Google, which demonstrated its self-driving car in the sum- mer of 2014. The technological program at the heart of the Google car is called Google Chauffeur.23 It is an example of a truly driverless car that can move itself in a targeted, pre-programmed fashion from point A to point B using advanced sensors that collect and interpret data from the environment. This is enabled by multiple Google technologies, including its Maps navigation technology. Google uses a Toyota-brand vehicle for testing its autonomous driving system, but it is not in a formal joint venture with the firm and could still choose any other automaker as a partner.24 Being cash-rich, the company could also develop its own car, as has been successfully demonstrated by Tesla.

Alternatively, much like Tesla, Google could coop- erate with an established carmaker (in Tesla’s case it was a design collaboration with Lotus in the UK). Along those lines, the company announced its new self-driving

Volvo with its well-established reputation of making some of the safest automobiles on the road, that heeded the call to partner.20

Along similar lines, Ford engineer Torsten Wey opined that he does not believe cars will ever be fully autonomous: “I doubt we will ever get there,” he said.21 According to Wey there are situations when the car’s autopilot is not intelligent enough to make decisions. The human driver does not only consider behavior of his own car, but also takes into account behaviors of others. Experienced drivers can intuitively predict what other cars on the road will do and act accord- ingly, augmenting the measurable data of the moment with their own experience. For instance, when a driver sees a car in front of them slow down to turn into a restaurant parking lot, the driver can judge that the car will likely not stop right there in the middle of the lane, based on subtle contextual clues and a life- time of learning. A computerized system, however, does not yet have that intuition and will not acquire it for a long time. Yet earlier, Ford tripled its auton- omous vehicle development fleet and accelerated its on-road software and sensor testing.22

Clearly, automakers are in an uncomfortable dance of cautioning expectations yet forging ahead full steam. But this diversity of signals, views and

Figure 1 Select Carmaker Competitors Positioning for Autonomous Driving

The chart above represents projected year of availability of Autonomous Automobiles for some car manufacturers. The size of the bubbles corresponds to the total car production by the company for the year 2013. The X axis shows the year in which car makers are expected to go to market with their versions of autonomous cars. The Y axis shows the degree of autonomy, as described above.

D eg

re e

o f

A ut

o m

at io

n

2014 2015 2016 2017 2018 2019

Tesla

BMW

Audi

VW

Toyota

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Part 4: Case StudiesC-48

technology development center in Novi, Michigan, in May 2016 and one of the first projects at the new facility will be the self-driving Chrysler Pacifica hybrid minivan, developed in-house.25

But given its deep pockets, Google could conceiv- ably also still buy an ailing carmaker, such as Saab, still struggling to recover after its purchase by National Electric Vehicles Sweden (NEVS), which is owned by Hong Kong-based energy company National Modern Energy Holdings. Or it could approach Volkswagen to take over the Seat or Skoda subsidiary, which seem to be duplicating each other’s offerings in the VW brands family.

To further complicate things, it is not just in the visible corners of the technology world that prominent companies like Google are working on autonomous automobiles and from which sudden advances could emerge. In start-ups, universities, and R&D centers around the world, leading technologists are work- ing on pre-commercial solutions. In early 2013 there were multiple reports about companies and individ- uals who were working on an affordable self-driving feature. One of them is Professor Paul Newman from Oxford University who works on self-driving technol- ogy that utilizes cheap sensors.26 Also, Intel awarded the top prize in its Gordon E. Moore competition27 to a Romanian teenager for using artificial intelligence to create a viable model for a low-cost, self-driving car. One company took it a step further and designed a commercial self-driving accessory that can be installed on selected models of compatible cars with sensors mounted on the rooftop. It is a startup called Cruise,28 which emerged from a Silicon Valley incubator, Y-Combinator, and started accepting pre-orders for it assisted driving system in mid-2014. In March 2016, Cruise was acquired by GM, which appears to be interested in integrating the system into the design of its own cars.

Another critical element of autonomous driving— mapping and location ser

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