Discussion Thread: Process Improvement: Benchmarking
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Discussion Thread: Process Improvement: Benchmarking
Key Concept: Benchmarking
Businesses use benchmarking as a method to assess their performance against that of other companies or organizations. Benchmarking might involve comparing an organization's operations, services, products, procedures, or a mix of these against its competitors. The ability to do benchmarking with unrelated organizations, such as comparing commission rates between a car manufacturer and a retailer, is a crucial benefit. Because benchmarking was mentioned just briefly in the reading yet is widely utilized in businesses and organizations, I decided to use this concept to discuss. The goal was to read in-depth articles regarding the procedures and uses of benchmarking across various industries.
Comparison
The reading lists each stage taken throughout the benchmarking process, which compares a business to others (David, 2021). Preparing for the benchmarking research is the initial phase, which can entail securing management support and gathering information on issue areas within the company. The second phase entails gathering information on other organizations from published data or in-house original research. The final step entails comparing the host company's data to those of its rivals in order to identify improvements or management suggestions.
These fundamental procedures were covered in the materials I read, along with best practices that increase the likelihood of discovering pertinent data. In one piece, it was highlighted how benchmarking strategic project managers might assist quantify expectations in a workplace where quarterly profits don't necessarily have a big influence (Sutia, 2020). The researchers were able to maximize the utilization of human resources in the business by using benchmarking to create better jobs that did not all have the same responsibilities.
Once established, benchmarking can be a repeatable, quantifiable procedure. In order to assess each country's capacity to comply with international health regulations, the World Health Organization (WHO) developed a scaling list. The article uses numerous categories, each graded from one to five, to assess each country's level of medical preparedness. The method employed by WHO demonstrates how benchmarking can develop a repeatable procedure and produce a measurable comparison (O.S. Albahri, 2020).
Article Summary
Direct purchases from manufacturers are not permitted in the US car sector. Instead, customers can acquire vehicles from dealerships connected to but not owned by manufacturing firms. Due to the partnership between car dealerships and manufacturers, it is essential for both parties to have an accurate system for identifying the characteristics of a successful car dealership that can sell plenty of new vehicles (Behzadan & Munir, 2019). Comparing auto dealerships can be challenging because location, certain salespeople, or vehicle brands can significantly affect the results of macro process comparisons. When comparing similar dealerships, the researchers removed superfluous data using a new model-based clustering benchmarking technique.
Numerous data factors, such as employee metrics, location, brand, and management incentives, are present in the new model, which includes hundreds of dealerships. After accounting for anomalous data, the research team overlaid dealership profitability to identify the characteristics that successful dealerships had in common. The team was able to forecast underperforming businesses when using the model on new dealerships. For the best business practices, the method can also be utilized to suggest new dealership locations and dealership upgrades.
Biblical Integration
Benchmarking and comparison between one another help make each other better through implicit friendly competition. The same sentiment is echoed in Proverbs (27:17), which reads “Iron sharpens iron, and one man sharpens another” (Open Bible, n.d.). This concept helps improve all parties involved as they continuously try to assess and outdo the other.
Application
Benchmarking was initially used to compare businesses exclusively to others that had similar products or business models. Benchmarking can now be used in novel and creative ways because of developments in computer technology and data collection; the only restriction is the research team's creativity (Banbury, 2021). Additionally, significant data storage capabilities allow businesses to maintain sizable information banks for conducting fresh comparisons, reducing the need for data collecting. The information that benchmarking gives will be crucial as more businesses attempt to reach the global market and as each one tries to increase its profit margin. Effective managers must be aware of the potential benefits of benchmarking in order to maximize business performance.
References
Banbury, C. R. (2021, January). Benchmarking TinyML Systems: Challenges & Direction. Retrieved from https://arxiv.org/pdf/2003.04821.pdf
TinyML hardware, which has recently made advances in ultra-low-power machine learning, holds the promise of enabling a completely new class of intelligent applications. However, the absence of a generally regarded baseline for these systems restricts further advancement. Benchmarking is essential for a field to mature since it enables systematic comparison, evaluation, and improvement of the performance of systems. In this position paper, researchers outline the current state of TinyML and talk about the difficulties and best course of action for creating an accurate and practical hardware benchmark for TinyML workloads. They also talk about their selection process and give four standards. The pooled opinions of the more than 30 organizations that make up the TinyMLPerf working group are reflected in their points of view.
Behzadan, V., & Munir, A. (2019). Adversarial Reinforcement Learning Framework for Benchmarking Collision Avoidance Mechanisms in Autonomous Vehicles. IEEE Intelligent Transportation Systems Magazine, 13(2).
The group of researchers implements data-driven benchmarking analytics for specific auto dealerships that take geography, demographics, and surroundings into account. The new approach consolidates dealerships depending on store performance using model-based clustering. In order to increase dealership sales while still maintaining manufacturing criteria, the model seeks to identify stores outside of the clustered model. The team developed the new benchmarking technique and then used it in real-world vehicle dealerships of significant American manufacturers. The data-driven benchmarking method may identify dealerships that are underperforming. Using this technique, the research team can make recommendations that are specific to the environment, demographics, and location of the store.
David, E. (2021). Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods. Science Partner Journals, 2021.
The research team examines the capacity of various project management office roles to carry out strategic planning in significant public organizations engaged in societal development. The study team recruited project participants from a wide range of organizations using a qualitative survey as a data-gathering method. Multiple regression was used to analyze this data, and the results showed that implementing a project management office enhanced the likelihood that the firm would succeed in attaining its strategic objectives. The study's goal was to ascertain how well the project management office jobs contributed to the achievement of business objectives, and it discovered that every position increased the likelihood of success. The amount of people assigned to each function did, however, show a diminishing return in the study, although further study is required to pinpoint when this diminishing return begins.
O.S. Albahri. (2020, October). Journal of Infection and Public Health, 13(10), 1381-1396.
To assess the capabilities of different countries to regulate health, researchers established a benchmarking process. To ascertain how prepared governments can be to support a range of health problems, it uses various distinct criteria. The group uses the benchmarking tool to numerically divide countries in order to improve aid distribution and create backup plans in case of a global medical emergency. After gathering the required data and making the necessary assumptions, the benchmarking tool was created to be used by any analytics team. It subcategorizes each of the categories into a few capacity levels. It also offers suggestions for enhancing a country's strengths in each area.
Open Bible. (n.d.). Retrieved from https://www.openbible.info/topics/competition
Sutia, S. (2020). Benefit of Benchmarking Methods in A Several industries: A systematic Literature Review. Systematic Reviews in Pharmacy, 11(8), 508-518.
The research group examines computer calculation techniques used in to assess if they can be applied to datasets used for business benchmarking. The group creates a set of guidelines and uses them while conducting open-source benchmarking studies. Their research examines if their method yields the same comparison and best course as conventionally used benchmarking studies in a number of company industries. The group then created a computer software based on their methods, optimizing it for business benchmarking. The researchers used tons of benchmarking techniques, and with enough data, they may all run simultaneously and produce useful results.
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Operations and Supply Chain Management for MBAs
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Sixth Edition
Jack R . Meredith
Scott M. Shafer Wake Forest University
Operations and Supply Chain Management for MBAs
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ISBN: 978-1-119-23953-6 (PBK)
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Names: Meredith, Jack R., author. | Shafer, Scott M., author.
Title: Operations and Supply Chain Management for MBAs / Jack R. Meredith, Scott M. Shafer.
Description: Sixth edition. | Hoboken, NJ : John Wiley & Sons, 2016. |
Includes bibliographical references and index.
Identifiers: LCCN 2015038625 | ISBN 978-1-119-23953-6 (pbk. : alk. paper)
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This book is dedicated to the Newest Generation:
Avery, Mitchell, Ava, Chase, and Ian. J.R.M.
Brianna, Sammy, and Kacy S.M.S.
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vi
Part 1 Strategy and Execution 1
1 Operations and Supply Chain Strategy for Competitiveness 2
2 Executing Strategy: Project Management 34
Part 2 Process and Supply Chain Design 65
3 Process Planning 66
4 Capacity and Scheduling 97
5 Supply Chain Planning and Analytics 126
6 Supply Chain Management 157
Part 3 Managing and Improving the Process 199
7 Monitoring and Controlling the Processes 200
8 Process Improvement: Six Sigma 225
9 Process Improvement: Lean 258
Cases 284 Glossary 338 Index 343
Brief Contents
Preface xiii
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vii
Part 1 Strategy and Execution 1
1 Operations and Supply Chain Strategy for Competitiveness 2
1.1 Operations 4
1.1.1. Systems Perspective 5
1.1.2. Inputs 6
1.1.3. Transformation Processes 6
1.1.4. Outputs 7
1.1.5. Control 9
1.1.6. Operations Activities 9
1.1.7. Trends in Operations and Supply Chain Management 10
1.2 Customer Value 11
1.2.1. Costs 11
1.2.2. Benefi ts 12
1.2.3. Innovativeness 12
1.2.4. Functionality 14
1.2.5. Quality 14
1.2.6. Customization 15
1.2.7. Responsiveness 18
1.3 Strategy and Competitiveness 19
1.3.1. Global Trends 19
1.3.2. Strategy 21
1.3.3. Strategic Frameworks 22
1.3.4. Core Capabilities 28
2 Executing Strategy: Project Management 34
2.1 Defi ning a Project 37
2.2 Planning the Project 38
2.2.1. The Project Portfolio 38
2.2.2. The Project Life Cycle 41
2.2.3. Projects in the Organizational Structure 42
2.2.4. Organizing the Project Team 42
2.2.5 Project Plans 43
Contents
Preface xiii
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viii Contents
2.3 Scheduling the Project 46
2.3.1. Project Scheduling with Certain Activity Times: A Process Improvement Example 47
2.3.2. Project Scheduling with Uncertain Activity Times 50
2.3.3. Project Management Software Capabilities 55
2.3.4. Goldratt’s Critical Chain 56
2.4 Controlling the Project: Earned Value 58
Part 2 Process and Supply Chain Design 65
3 Process Planning 66
3.1 Forms of Transformation Systems 68
3.1.1. Continuous Process 68
3.1.2. Flow Shop 69
3.1.3. Job Shop 75
3.1.4. Cellular Production 79
3.1.5. Project Operations 83
3.2 Selection of a Transformation System 83
3.2.1. Considerations of Volume and Variety 84
3.2.2. Product and Process Life Cycle 86
3.2.3. Service Processes 87
4 Capacity and Scheduling 97
4.1 Long‐Term Capacity Planning 99
4.1.1. Capacity Planning Strategies 100
4.2 Effectively Utilizing Capacity Through Schedule Management 104
4.2.1. Scheduling Services 106
4.3 Short‐Term Capacity Planning 109
4.3.1. Process‐Flow Analysis 109
4.3.2. Short‐Term Capacity Alternatives 115
4.3.3. Capacity Planning for Services 117
4.3.4. The Learning Curve 119
4.3.5. Queuing and the Psychology of Waiting 122
5 Supply Chain Planning and Analytics 126
5.1 Importance of Supply Chain Planning and Analytics 128
5.2 Demand Planning 129
5.2.1. Forecasting Methods 130
5.2.2. Factors Influencing the Choice of Forecasting Method 131
5.2.3. Time Series Analysis 132
5.2.4. Causal Forecasting with Regression 141
5.2.5. Assessing the Accuracy of Forecasting Models 147
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ixContents
5.3 Sales and Operations Planning 148
5.3.1. Aggregate Planning Strategies 149
5.3.2. Determining the Service Level: An Example Using the Newsvendor Problem 150
5.3.3. Collaborative Planning, Forecasting, and Replenishment 153
6 Supply Chain Management 157
6.1 Defining SCM 160
6.2 Supply Chain Strategy 162
6.2.1. Strategic Need for SCM 163
6.2.2. Measures of Supply Chain Performance 165
6.3 Supply Chain Design 166
6.3.1. Logistics 167
6.4 Sourcing Strategies and Outsourcing 175
6.4.1. Purchasing/Procurement 177
6.4.2. Supplier Management 179
6.5 Inventory and Supply Planning 180
6.5.1. Functions of Inventories 181
6.5.2. Forms of Inventories 182
6.5.3. Inventory‐Related Costs 183
6.5.4. Decisions in Inventory Management 185
6.6 Role of Information Technology 185
6.6.1. ERP 186
6.6.2. Customer Relationship Management Systems 188
6.7 Successful SCM 188
6.7.1. Closed‐Loop Supply Chains and Reverse Logistics 189
Supplement A—The Beer Game 195
Supplement B—The Economic Order Quantity Model (online)
Part 3 Managing and Improving the Process 199
7 Monitoring and Controlling the Processes 200
7.1 Monitoring and Control 201
7.2 Process Monitoring 203
7.2.1. Stages of Operational Effectiveness 203
7.2.2. Balanced Scorecard 204
7.2.3. The Strategy Map 206
7.2.4. ISO 9000 and 14000 207
7.2.5. Failure Mode and Effect Analysis (FMEA) 208
7.3 Process Control 209
7.3.1. Statistical Process Control 210
7.3.2. Constructing Control Charts 213
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x Contents
7.4 Controlling Service Quality 216
7.4.1. Service Defections 217
8 Process Improvement: Six Sigma 225
8.1 Approaches for Process Improvement 228
8.2 Business Process Design (Reengineering) 229
8.3 Six Sigma and the DMAIC Improvement Process 231
8.3.1. Example Six Sigma Project 232
8.4 The Define Phase 235
8.4.1. Benchmarking 235
8.4.2. Quality Function Deployment 236
8.5 The Measure Phase 238
8.5.1. Defects per Million Opportunities (DPMO) 239
8.5.2. Measurement Systems Analysis 241
8.6 The Analyze Phase 243
8.6.1. Brainstorming 244
8.6.2. Cause-and-Effect Diagrams 246
8.6.3. Process Capability Analysis 246
8.7 The Improve Phase 249
8.7.1. Design of Experiments 249
8.8 The Control Phase 251
8.9 Six Sigma in Practice 251
8.9.1. Six Sigma Roles 251
8.9.2. Becoming Certified 252
8.9.3. The Need to Customize Six Sigma Programs 252
9 Process Improvement: Lean 258
9.1 History and Philosophy of Lean 261
9.1.1. Traditional Systems Compared with Lean 262
9.2 Specify Value and Identify the Value Stream 266
9.2.1. Identify the Value Stream 268
9.3 Make Value Flow 271
9.3.1. Continuous Flow Manufacturing 272
9.3.2. The Theory of Constraints 273
9.4 Pull Value through the Value Stream 275
9.4.1. Kanban/JIT in Services 276
9.5 Pursue Perfection 277
9.5.1. 5S 277
9.5.2. The Visual Factory 277
9.5.3. Kaizen 278
9.5.4. Poka Yoke 278
9.5.5. Total Productive Maintenance 278
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xiContents
9.6 Benefits of Lean and Lean Six Sigma 279
9.6.1. Lean Six Sigma 280
Cases 284
BPO, Incorporated: Call Center Six Sigma Project 284
Peerless Laser Processors 297
General Micro Electronics, Inc.: Semiconductor Assembly Process 302
Heublein: Project Management and Control System 315
D. U. Singer Hospital Products Corp. 327
Automotive Builders, Inc.: The Stanhope Project 331
Case (online)—United Lock: Door Hardware Division (A)
Bibliography (online)
Glossary 338
Index 343
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xiii
The enthusiasm of the users of this MBA‐oriented book has been greatly rewarding for us, and
we thank them for their comments, suggestions, criticism, and support. Although the book is not
the massive seller that an undergraduate textbook can become, it is clear that there is, as we felt,
a need for a solely MBA‐level text. The book was originally written because of the express need
we felt in our many MBA programs at Wake Forest University for an operations management
textbook directed specifically to MBA students and especially to those who had some real‐world
experience. We tried all of the current texts but found them either tomes that left no time for the
cases and other materials we wanted to include or shorter but simplistic quantitative books.
Moreover, all the books were so expensive they did not allow us to order all the cases, readings,
and other supplements and class activities (such as the “Beer Game”; see Chapter 6 Supplement)
that we wanted to include in our course.
What we were looking for was a short, inexpensive book that would cover just the introduc-
tory, basic, and primarily conceptual material. This would allow us, as the professors, to tailor the
course through supplementary cases and other materials for the unique class we would be teach-
ing: executive, evening, full time, short course, and so on. Although we wanted a brief,
supplementary‐type book so that we could add other material, we have colleagues who need a
short book because they only have a half‐semester module for the topic. Or they may have to
include another course (e.g., statistics) in the rest of the semester.
Changes in this Sixth Edition A lot has happened since our previous edition, and we felt compelled to reorganize the book to
reflect these changes. First, we amended the title to reflect the increased importance of supply
chain management concepts and added an extra chapter ( 5 ) as well, focusing on demand plan-
ning, forecasting, analytics, and sales and operations planning. Also, project management is now
being used for
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