July 24, 2022

Human Resource Management Subject Update



2021

Combining technology with human resources management to strengthen virtual teams
November 2nd, 2021

OR Techniques and HRM

The Importance of Values in Human Resource Management in the Post Pandemic World. 
What is a Value Driven HRM Approach and how can it be actualized in Practice?

Strategic human resource management practices and human capital development: The role of employee commitment
Main Naser Alolayyan , Mohammad Sharif Alyahy, Dana Ahmad Omari
http://dx.doi.org/10.21511/ppm.19(2).2021.13
Problems and Perspectives in Management , Volume 19 2021, Issue #2, pp. 157-169
https://www.businessperspectives.org/index.php/journals/problems-and-perspectives-in-management/issue-380/strategic-human-resource-management-practices-and-human-capital-development-the-role-of-employee-commitment

Research Article | Open Access
Optimization of the Enterprise Human Resource Management Information System Based on the Internet of Things
Haiqiu Li
Complexity, Volume 2021 |Article ID 5592850 | https://doi.org/10.1155/2021/5592850
https://www.hindawi.com/journals/complexity/2021/5592850/

Human Capital Management (HCM)
Put employees at the heart of everything you do with SAP SuccessFactors software. Our cloud HCM solutions are completely designed around employee experiences – what they need, how they work, and what motivates them.
https://www.sap.com/products/human-resources-hcm.html

https://www.cipd.co.uk/knowledge/strategy/hr/strategic-hrm-factsheet#gref

Innovative human resource management strategies during the COVID-19 pandemic: A systematic narrative review approach
Heliyon . 2021 Jun;7(6):e07233. doi: 10.1016/j.heliyon.2021.e07233. Epub 2021 Jun 7.
https://pubmed.ncbi.nlm.nih.gov/34124399/

TOP TRENDS IN HUMAN RESOURCE MANAGEMENT IN 2021
https://www.thehrdirector.com/top-trends-in-human-resource-management-in-2021/

It’s Time To Reinvent Corporate Learning: Join Our New Research
BY JOSHBERSIN · NOVEMBER 8, 2021

Changes have taken place.

The Corporate Universities of the last decade were replaced with digital learning academies of the last five years, soon to be replaced with learning in the flow of work, skills-based capability academies, and a new Metaverse of learning experiences. Already companies like STRIVR, Mursion, and Microsoft have delivered proven VR and AR solutions that drive more value than we ever thought possible.

https://joshbersin.com/2021/11/its-time-to-reinvent-corporate-learning-join-our-new-research/

2019
Making Joy a Priority at Work
HBR July 2019 Article
Alex Liu, AT Kearnye   Joy@Work Podcast
https://hbr.org/2019/07/making-joy-a-priority-at-work


2017

Six Principles of Effective Global Talent Management
Sloan Management Review: Winter 2012
Günter K. Stahl, Ingmar Björkman, Elaine Farndale, Shad S. Morris, Jaap Paauwe, Philip Stiles, Jonathan Trevor and Patrick Wright
http://sloanreview.mit.edu/article/six-principles-of-effective-global-talent-management/


2016
Top 20 Essential Skills of Human Resources Management
By Sravani -September 9, 2016
http://content.wisestep.com/essential-skills-human-resources-management/


2001
Human Capital Interview
https://www.siop.org/tip/backissues/TipOct01/pdf%20tip/392_058to063.pdf


Updated 2 September 2019,  7 May 2017, 10 December 2015

July 23, 2022

Analytics for Grocery Retail Sales



https://www.mckinsey.com/industries/retail/our-insights/pushing-granular-decisions-through-analytics-in-na      


Personalized promotions through insights from analytics can be utilized by retailers. Retailers can operate the use cases at scale because technology has evolved, and customer touchpoints for data collection and communication (especially through e-grocery and loyalty apps) have increased in recent years. When done right, promotions can provide a substantial benefit of 4 to 8 percent sales increase and 2 to 3 percent net income and EBIT uplift.

 

July 22, 2022

What is the Difference between Management and Leadership?

 


Rost distinguishes between management and leadership: 

“management is an authority relationship between at least one manager and one subordinate who coordinate their activities to produce and sell particular goods and/or services”. 

He defines leadership as “an influence relationship among leaders and followers who intend real changes that reflect their mutual purposes.” 

Divergence between   Management and Leadership 

While management strives for stability, “leadership is a process of  transformative change”.

Leadership is in action when a change has to be brought about in the behavior of a group.


Rost JC (1993) Leadership for the Twenty-first Century. Westport, CT: Praeger.

Barker RA (2002) On the Nature of Leadership. Lanham: University Press of America.

July 21, 2022

Marketing Management Subject Update




Marketing Management Revision Article Series

2022

Machine Customer Demand Sensing and Management - Gartner

Bring Brand and Performance Marketing Closer. 
Though the two marketing approaches have diverged, they each have a skill set that would benefit the other
By Adam Edwards
|June 8, 2022

For most marketing teams, there’s a wall separating brand marketing and performance marketing in social and search media advertising.
But that wall has to be dismantled for marketing effectiveness.

Marketing Management, 16è Indian Edition co-authored by Philip Kotler, Kevin Lane Keller, Alexander Chernev, Jagdish Sheth N Sheth, & Shainesh G. 
The most anticipated book is finally dropping on 31st May' 2022.

https://cherryflava.com/the-worlds-most-effective-ads-in-2022-all-have-one-thing-in-common/

2021

Marketing Trends to Plan for 2022

Supercharging customers with AI - Right offers at the right time - Post sales service

TechnologyAdvice Guide to Marketing Automation Software
December 7, 2021

Marketing analytics & AI solutions

The complete guide to managing marketing expenses




10 Truths About Marketing After the Pandemic
by Janet Balis
March 10, 2021
https://hbr.org/2021/03/10-truths-about-marketing-after-the-pandemic

SAP Customer Experience Marketing
https://www.sap.com/products/crm/marketing.html


Marketing Strategy 2021: Philip Kotler on Marketing Strategy

________________



https://www.youtube.com/watch?v=ghFwpoH71NM

00:00 Meeting The Global Challenges
40:23 Builing Your Marketing and Sales Organization
1:29:26 Moving From Traditional Marketing to Digital Marketing & Marketing Analytics
1:39:55 Moving to Marketing 3.0 & Corporate Social Responsibility

________________

2020

ANALYTICS
Is Your Marketing Strategy Based on the Right Data?
by Gregg Johnson
May 14, 2020, HBR
https://hbr.org/2020/05/is-your-marketing-strategy-based-on-the-right-data


Summary Strategic Brand Management (Keller) part 2

2019

Top Marketing Trends For 2020
Forbes Agency Council
Christian ThomsonForbes Councils Member
Forbes Agency Council

10 Principles of Modern Marketing

Research Highlight April 03, 2019  Reading Time: 19 min
Ann Lewnes and Kevin Lane Keller


  • Technology Is Just the First Step


Technology has changed everything. Fundamentally, it allows for new ways to create customer experiences, new mediums to connect with customers and other constituents, and trillions of data points to understand customer behavior and the impact of marketing programs and activities. Yet, there is more to marketing and use of technology in marketing.


  • Experience Is the New Brand
  • A New Type of Customer Relationship Prevails
  • Connect With Customers Online and Offline
  • Value Creation, Communication, and Delivery Still Rule
  • Data and Testing Are the New Lifeblood
  • Creativity Remains King
  • Don’t Try to Do It Alone
  • Have a Bigger Purpose: Do Good
  • Marketing Leadership Has Changed
https://sloanreview.mit.edu/article/10-principles-of-modern-marketing/


How Marketers Can Overcome Short-Termism

Christine MoormanLauren Kirby
November 21, 2019
https://hbr.org/2019/11/how-marketers-can-overcome-short-termism


Marketing Communication: “Think. Do. Say.”

SEPTEMBER 5, 2019
If the product you make doesn’t support your brand belief or corporate purpose, then you’ve got it wrong. “And that’s why I think where organizations are getting confused."
https://the-message.ca/2019/09/05/ron-tite-on-how-modern-marketing-shaped-his-new-book-think-do-say/

The Marketing Topics That Resonated Most With Readers In 2019

Kimberly A. Whitler
Senior Contributor
CMO Network
As a former General Manager and CMO, who worked for nearly 20 years before getting a PhD and working as an Assistant Professor at the University of Virginia's Darden School of Business, I conduct research that focuses on helping the C-suite (and aspiring C-level marketers) better understand, develop, and lead marketing excellence.
https://www.forbes.com/sites/kimberlywhitler/2019/12/21/the-marketing-topics-that-resonated-most-with-readers-in-2019


The Dividends of Digital Marketing Maturity

FEBRUARY 18, 2019
By Dominic Field , Shilpa Patel , and Henry Leon
https://www.bcg.com/en-in/publications/2019/dividends-digital-marketing-maturity.aspx


Prescriptive Analytics in Sales and Marketing

How analytics can guide companies from insight to action.
Prescriptive analytics frequently takes three forms: guided marketing, guided selling and guided pricing.
By Chris Dent, David Burns and Saber Sherrard
August 27, 2019
https://www.bain.com/insights/do-this-not-that-prescriptive-analytics-in-sales-and-marketing/

Choosing Your Next Go-to-Market Investment

Where should you spend the next dollar on commercial capabilities? A diagnostic X-ray reveals the gaps that matter to your business.
By Jonathan Frick, Jason McLinn, Mark Kovac and Chris Dent
January 11, 2019
https://www.bain.com/insights/choosing-your-next-go-to-market-investment/


Agile in the consumer-goods industry product development: 

The transformation of the brand manager
April 2019
https://www.mckinsey.com/business-functions/marketing-and-sales/our-insights/agile-in-the-consumer-goods-industry-the-transformation-of-the-brand-manager

What CEOs and other execs really think of marketing

July 2019
Many executives now regard it as an investment and rely on it to drive growth. This consensus emerged from a series of surveys and in-depth interviews conducted with more than 200 leading C-suite executives by McKinsey consultants and researchers.
https://www.mckinsey.com/business-functions/marketing-and-sales/our-insights/views-from-the-top-what-ceos-and-other-execs-really-think-of-marketing


MAKING CONNECTIONS WITH THE NEW DIGITAL CONSUMER
PwC's Entertainment and Media Outlook
To thrive in a world of apps, platforms, and privacy concerns, marketers have to become multitaskers.
by Dan Bunyan and Karim Sarkis
https://www.strategy-business.com/feature/Making-connections-with-the-new-digital-consumer


Why B2B Buying Cycles Are So Long
http://b2bmarketingdirections.blogspot.com/2019/05/why-b2b-buying-cycles-are-so-long.html

What Abraham Maslow Can Teach Us About Customer Experience
http://b2bmarketingdirections.blogspot.com/2018/07/what-abraham-maslow-can-teach-us-about.html

Marketing Communication Plan
Communication for pull. Communication for push Communication for profile.
https://neilsbrandingblog.blogspot.com/2018/10/marketing-communication-plan.html
(To visit the blog and comment again)
http://neilsbrandingblog.blogspot.com/2018/08/week-1.html  (This is the first post. Above one is the last post.

Marketing 4.0


“Marketing 4.0: When Online Meets Offline, Style Meets Substance, and Machine-to-Machine Meets Human-to-Human” – Philip Kotler, Hermawan Kartajaya, Iwan Setiawan
May 5, 2018

Marketing 4.0 is about balancing machine-to-machine (M2M) with human-to-human (H2H).

New Ideas in Marketing 4.0

‘Segmentation and Targeting’ to ‘Customer Community Confirmation’
‘Selling the 4P’s’to ‘Commercializing the 4C’s’
‘Customer Service Processes’ to ‘Collaborative Customer Care’
‘Brand Positioning and Differentiation’ to ‘Brand Characters and Codes’
‘Segmentation and Targeting’ to ‘Customer Community Confirmation’
http://www.marketingjournal.org/marketing-4-0-when-online-meets-offline-style-meets-substance-and-machine-to-machine-meets-human-to-human-philip-kotler-hermawan-kartajaya-iwan-setiawan/


Why Great Innovation Needs Great Marketing
Denise Lee Yohn
FEBRUARY 20, 2019

Strategic, upstream marketing that is incorporated into the innovation development process can clearly define who to sell the new offering to and how to sell it.
Decide 4Ps of marketing using marketing expertise.

 Innovation alone may be enough to initiate the adoption life cycle, but marketing remains the bridge necessary to cross the chasm between early adopters to the wider group of people who will form a viable, valuable customer base.
https://hbr.org/2019/02/why-great-innovation-needs-great-marketing



2018


4 Ways to Improve Your Content Marketing
Frank V. CespedesRuss Heddleston
APRIL 19, 2018
The average viewing time for content is 2 minutes and 27 seconds.
Frank Cespedes is a Senior Lecturer at Harvard Business School and author of Aligning Strategy and Sales (Harvard Business Review Press).
https://hbr.org/2018/04/4-ways-to-improve-your-content-marketing

Why Marketing Analytics Hasn’t Lived Up to Its Promise
Carl F. MelaChristine Moorman
MAY 30, 2018

Communication theory tells us that the transmitter and receiver of information must share a common domain of knowledge for information to be transmitted. This means analysts need to understand what the firm’s managers can understand.
 it is critical for analysts to connect externally with customers and internally with the managers using their work.
Carl F. Mela is the T. Austin Finch Foundation Professor of Marketing at Duke University’s Fuqua School of Business and the Executive Director at the Marketing Science Institute.
https://hbr.org/2018/05/why-marketing-analytics-hasnt-lived-up-to-its-promise



2017

5 Ways Words Can Destroy Your Marketing Messages (And How to Fix Them)
Use these copywriting tips to improve your marketing messages and ensure you don't lose sales or money on your marketing investments.
https://www.entrepreneur.com/article/298766



There is No Luck. Only Good Marketing.

________________

________________
TEDx Talks

Article in HBR on Organization of Marketing Department
https://hbr.org/2014/07/the-ultimate-marketing-machine

Developing a marketing plan  (interesting information is in the article)
http://canadabusiness.ca/managing-your-business/marketing-and-sales/marketing-basics/developing-a-marketing-plan/

Key competencies for general sales effectiveness
By Amir Qureshi
12 December 2016
https://www.thomasinternational.net/en-gb/blog/december-2016/key-competencies-for-general-sales-effectiveness/


Dec 2016

https://medium.com/context/tagged/best-of-2016


March 2016

Marketing Managers' Salary Guide for USA - 2016
https://www.ama.org/career/Pages/2016-Marketers-Salary-Guide.aspx

https://hbr.org/topic/marketing

http://knowledge.wharton.upenn.edu/article/imagine-theres-no-marketing-its-easy-if-you-try/

http://knowledge.wharton.upenn.edu/article/six-digital-marketing-traps-that-cmos-should-avoid/

http://knowledge.wharton.upenn.edu/article/small-data-new-big-data/

http://knowledge.wharton.upenn.edu/article/recommended-for-you-how-well-does-personalized-marketing-work/


https://www.ted.com/talks/seth_godin_on_the_tribes_we_lead

__________________

__________________
TED


May 2015

Negotiation: What Makes the Right Business Deal
http://www.forbes.com/sites/ianaltman/2015/05/05/negotiation-what-makes-the-right-business-deal/


Macromarketing
I searched for this topic today in my interest to write an article on the topic marketing support for Make in India Campaign. I found that there a huge literature in the area of macromarketing. The reference I came across today are:

Marketing Theory: Philosophy of Science Perspectives
https://books.google.co.in/books?id=W4phEfAbHBQC


http://en.wikipedia.org/wiki/Macromarketing


April 2015

Marketing communication messages have to be different when you announce a product and build buying intention for it. The communication has to change when the product is actually made available in the market for purchase.  Read the summary of a recent research paper on adoption of products.
http://nraomtr.blogspot.com/2015/04/adoption-of-new-products-and-processes.html


February 2015
Planned Revision schedule for marketing chapters is in February and March

January 2015

Why Your Customers’ Social Identities Matter.

By: Champniss, Guy; Wilson, Hugh N.; Macdonald, Emma K. Harvard Business Review. Jan/Feb2015, Vol. 93 Issue 1/2, p88-96.

People are highly social animals. Most of us belong to many social groups, each with its own identity.

For five years the authors have been studying how social identity affects customer behavior in a wide range of industries. They have seen that companies can trigger more-favorable reactions in customers by subtly influencing which identities they tap into. This is something firms should take into account when doing market research or designing experiences.

The first step is to surface the range of  a customer's  possible identities. If a customer's identity encourages targeted behaviors, marketers can help reinforce it.  Marketers can also work to add a desired behavior to those that customers associate with an identity, prime different identities in customers, and even create new identities that deepen relationships with existing customers and attract new ones.




2014's top The Gunn Reports' Cases For Creativity

1. 1. IBM's 'A Boy And His Atom' Ogilvy & Mat her, USA
_________________

_________________
IBM upload
http://economictimes.indiatimes.com/magazines/brand-equity/2014s-top-the-gunn-reports-cases-for-creativity/articleshow/45952325.cms


2. Evian Baby & Me
_________________

_________________
EvianBabies
99,261,360 views 29 Jan 2015


"Contagious: Why Things Catch on" by Jonah Berger was named the best book of Marketing of 2014
Talk by Jonah Berger
___________________

___________________
Talks at Google upload
http://google.co.in/books?id=J2l7pgwTiW4C  (For previewing the book)

Marketing News - 15 January Issue
http://publications.ama.org/Marketing_News/MN-jan15/index.html

Why Uniqlo Is Winning
By: David Aaker
Uniqlo is Japanese clothing retailer now in top 5 and plans to beat Zara.
https://www.ama.org/publications/MarketingNews/Pages/why-uniqlo-is-winning.aspx


Updated 7 July 2020
26 December 2019,  1 June 2019. Dec 2015


Give your suggestions for adding any articles to the collection.

July 19, 2022

Operations, Strategy, and Technology - Hayes et al - Important Points

Operations, Strategy, and Technology Pursuing the Competitive Edge

Robert Hayes, Gary Pisano, David Upton and Steven Wheelwright

Harvard University

WILEY

www.wiley.com/college/hayes



Contents 



1. Operations Management Confronts a New Millennium 

1.1 Introduction 

1.1.1 The World Business Context 

1.1.2 The Evolving Bases of Competition 

1.2 Growing Disillusionment with the New Approaches to Operations 

Throughout the 1980s and 1990s, Western manufacturers had pursued world-class manufacturing status through a shotgun blast of three-letter acronyms: TQM, JIT, DFM, QFD, QPD and CIM.


The conclusion of most large studies on the successes of these programs has been that only about a third of the companies that attempted to implement the most popular NAOs achieved the results expected-by the companies' own admissions. 

1.2.1 The Limits of the NAOs II

1.2.2 The Limits of Process Reengineering 12

1.2.3 The Limits of Emulating "Best Practice" 13

1.3 Managing in the New World Economy 14

1.3.1 Globalization 14

1.3.2 Information Technology and Information-Intensive Operations 15

1.3.3 What's Different in Information-Intensive Operations? 17

1.3.4 Summarizing the Differences: O.M. in the Old and

New Economies 23

1.3.5 Redefining the Boundaries of Organizations and

Operations Management: 23

1.4 The Information Economy's Challenges for

Operations Management 26

1.5 An Outline of This Book 27

1.5.1 Operations Strategy 27

1.5.2 Operations Technology 29

1.5.3 Operating Improvement 30

Notes 31 2. Operations Strategy: Origins and New Directions 33

2.1 Introduction 33

2.2 The Concept of Strategy 34

2.2.1 Company Values—The Foundation for Strategy 36

2.3 The Operations Edge:

Creating a Competitive Advantage through Operations 36

2.3.1 The "American System": Mass Production for Mass Markets 37

2.3.2 The Japanese System: "Lean Production" 38

2.3.3 A Contingency Theory of Operations Strategy: Fit and Focus 38

2.3.4 Key Decisions Involved in Operations Strategy Implementation 41

2.3.5 Responding to Evolving Strategies, Markets, and Technologies 47

2.3.6 Strategy as an Art Form 49 


2.4 Challenges to the Operations Strategy Framework 49

2.4.1 Challenging the Necessity for Trade Offs 50

2.4.2 Challenging the Importance of Focus 51

2.5 Dynamic Organizational Capabilities 52

2.5.1 Path Dependencies: '

Reexamining Focus and Tradeoffs from a New Perspective 54

2.5.2 Strategic Choice in Operations 55

2.6 Attacking and Defending through Operations 56

2.6.1 Attacking through Operations 59

2.6.2 Sustaining an Operations Edge 64

2.6.3 Defending through Operations 65

2.6.4 Lessons in Attacking and Defending through Operations 66

2.7 Conclusion 68

Notes 68

Appendix . .

2A.I Evaluating an Operations Strategy 71

2A.2 The Concept of a Corporate Operations Strategy 72

2A.2.1 The Corporation's Dominant Orientation 74

2A.2.2 The Pattern of Diversification 74

2A.2.3 The Altitude toward Growth 74 3. Capacity Strategy 76

3.1 Overview 76

3.2 How Capacity and Operations Management Interact 78

3.2.1 The Impact of Variability on Capacity 80

3.2.2 Alternative Approaches for Expanding Capacity 82

3.2.3 The Consequences of a Capacity Squeeze 83

3.3 The Timing of Capacity Increments—The Capacity Cushion 85

3.3.1 Policy A: Lead Demand with Capacity 86

3.3.2 Policy B: Build to the Forecast 86

3.3.3 Policy C: Add Capacity Only after Demand Exceeds It 87

3.3.4 Alternative Types of Capacity Cushion 87

3.3.5 Determining the Appropriate Capacity Cushion 89

3.4 The Sizing of Capacity Increments—Scale Considerations 92

3.4.1 Economies of Scale 92

3.4.2 Diseconomies of Scale 98

3.4.3 Increasing Economies of Scale 100

3.4.4 Optimal Economic Size 101

3.5 Developing a Capacity Strategy 103

3.6 Four Philosophies of Capacity Expansion 105

3.7 Integrating a Firm's Capacity Strategy with

Its Business Strategy 107

Notes 109


Appendix

3A.1 Justifying the Simple Formula (3-2) for Estimating the Amount of

Capacity Cushion Warranted by a Given Cost Structure and

Demand Distribution 111

3A.2 Models for Evaluating Simple Capacity Expansion Strategies 1 11

3A.2A The Discounted Present Value of Simple Capacity Strategies in a

Growing Market, Assuming No Shortfalls in Capacity

Are Permitted 112 A Numerical Example 113

3A.23 A Minimum Cost Capacity Strategy When Shortfalls

Are Permitted 114

Notes 115 4. Determining Organizational Boundaries:

Vertical Integration and Outsourcing 116

4.1 Introduction 116

4.2 Trends and Evidence 116

4.3 Framing Vertical Integration and Sourcing Decisions 119

4.3.1 What Are the Choices? 120

4.4 Factors Influencing Vertical Integration Decisions 123

4.4.1 Capabilities/Resources 123

4.4.2 Coordination Requirements 125

4.4.3 Strategic Control and Risks 128

4.4.4 Protecting Intellectual Property 134

4.5 Summary 136

Notes 138 5. Designing and Managing Operating Networks 139

5.1 Introduction 139

5.2 The Rationale for Multifacility Networks 140

5.3 Designing the MuUifacility Network: Structure 142

5.3.1 Number and Size 142

5.3.2 Location 142

5.3.3 Specialization 143

5.3.4 Mixed Networks 145

5.3.5 Selecting between Horizontal and Vertical Network Structures 147

5.4 Managing the Network: Infrastructure 150

5.5 Managing Different Network Structures 152

5.5.1 Horizontal Networks 152 ' 5.5.2 Vertical Networks 153

5.5.3 Centralization versus Decentralization 154

5.5.4 Implementing and Maintaining Focus 157

5.6 The Dynamics ol Horizontal Networks 158


5.7 The Dynamics of Vertical Networks 160

5.7.1 Vertical Supply Chain Dynamics: The Bullwhip Effect 161

5.7.2 Dealing with the Coordination Problem 164

5.7.3 An Example: Managing the Bullwhip 165

5.7.4 Some Concluding Thoughts on Supply Chain Management 166

Notes 167 6. Information Technology and Operations 169

6.1 Introduction 169

6.2 The Expanding Role of IT 169

6.2.1 IT in Operations 169

6.2.2 Expansion of IT to Business and Network Operations 172

6.2.3 Enterprise Resource Planning 172

6.2.4 The Impact of the Internet 174

6.3 The Challenges of Integration, Standards, and Fit 175

6.3.1 Making IT Decisions that '"Fit" 175

6.3.2 How Did We Get into This Mess? 176

6.3.3 Selecting Standards 178

6.3.4 Principles and Decisions in IT Design 180

6.4 Strategic Hazards 180

6.4.1 Hazards to Disiinctiveness:

The Rebirth of the "One Best Way" 180

6.4.2 Hazards to Strategic Flexibility: IT as "Liquid Concrete" 181

6.5 Implementing IT Systems: Two Approaches 183

6.6 Making IT "Matter" 188

Notes 189

Appendix

6A.I Standards and Integration Outside the Firm 191 An Example of the Application of

New Communication Standards 191

6A.2 Open Source Software 193

Notes 194 7. Creating an Edge through New Process Development 195

7.1 Introduction 195

7.2 How Process Development and Operations Interact to Facilitate New

Product Development 196

7.2.1 The Product Life Cycle Concept Revisited 197

7.2.2 Mapping the Context 198

7.3 Leveraging Process Development Capabilities for

Competitive Advantage 199

7.3.1 Accelerated Time to Market 199

7.3.2 Rapid Ramp-Up 201


7.3.3 Enhanced Customer Acceptance 202

7.3.4 Stronger Proprietary Position 203

7.4 Achieving Speed, Efficiency, and Quality in the Development of New Processes 


At a highly simplistic level, a process technology is akin to a recipe. It encompasses input specifications, the sequence of tasks that must be performed, the equipment that must be utilized, the parameters at which equipment must be operated, the expected intermediate outputs, means for controlling the process, and ways of checking quality throughout.

7.4.1 Integrating Product and Process Development 204

7.4.2 Timing the Transfer of New Process

Technologies into Operations 208

7.4.3 Centralized versus Decentralized Process Development and

Technology Choices 213

7.5 Process Development in Perspective 217

Notes 217 8. Creating an Edge through Superior Project Management 219

8.1 Introduction 219

8.2 Two Historical Approaches to Project Management 220

8.2.1 Critical Path Analysis 220

8.2.2 Stage-Gate Approaches 224

8.3 Creating, Selecting, and Managing Project Portfolios 227

8.3.1 Seeding: Encouraging a Rich Mix of Alternative Project Ideas 228

8.3.2 Weeding and Feeding:

Winnowing Project Ideas and Providing Resources 229

8.3.3 Cultivating the Project Portfolio 232

8.3.4 Plowing Under 234

8.4 Maintaining Discipline and Focus in the Project Portfolio 234

8.5 Designing a Strategy for Project Execution 236

8.5.1 Project Definition 237

8.5.2 Project Teams 237 .

8.5.3 Structuring the Flow of Project Tasks and Activities 239

8.5.4 Methodologies for Design, Prototyping, and Testing 241

8.5.5 Senior Management Review and Control 242

8.5.6 A Contingent Model of Project Management 242

8.6 Learning from Project Experience 242

Notes 246 9. Evaluating and Justifying Capital Investments 247

9.1 Introduction 247

9.2 Managing the Investment Planning Process 249

9.2.1 Evaluate Existing Operations 250

9.2.2 Forecast Capacity and Competitive Requirements 250

9.2.3 Define Alternatives for Meeting Requirements 252 ' 9.2.4 Perform Financial Analyses of Each Alternative 253

9.2.5 Assess Key Qualitative Issues for Each Alternative 253

9.2.6 Select and Defend the Alternative to Be Pursued 254

9.2.7 Implement the Chosen Alternative 254

9.2.8 Audit Actual Results 255


9.3 Financial Analysis of Proposed Investments 255

9.3.1 A Framework for Assessing the Financial Attractiveness of Proposed Investments

9.3.2 Measures of Security 257

9.3.3 Measures of Recompense 259 '

9.3.4 Recompense—The Accumulated Cash Balance 260

9.3.5 Recompense—The Net Present Value 261

9.3.6 Recompense—The Internal Rate of Return 264

9.3.7 Measures of Predictability 266

9.3.8 Assessing a Proposed Investment's Option Value 270

9.3.9 Caveat Calculator! 273

9.4 Integrating Investment Proposals into Long-Term Strategies 275

Notes 111

10. Sharpening the Edge: Driving Operations Improvement 279

10.1 Introduction 279

10.2 A Framework for Analyzing Organizational Improvement 280

10.2.1 A Macro Perspective: Learning and Experience Curves 280

10.2.2 Different Mechanisms for Driving

Organizational Improvement 281

10.3 "Within" vs. "Across" Group Improvement 282

10.3.1 Enablers of, and Constraints on,

"Within" Group Improvement 282

10.3.2 Transferring Improvement Across Groups 287

10.4 Learning by Doing vs. Learning before Doing 288

10.5 Transferring Learning In from Outside the Organization 289

10.6 Breakthrough vs. Incremental Improvement 291

10.6.1 Implementing Strategic Leaps 292

10.6.2 Implementing Incremental Improvement 293

10.7 A Framework for Improvement Activities, with Two Examples 297

10.7.1 Example A: Business Process Reengineering 298

10.7.2 Example B: Total Quality Management (TQM) 301

10.7.3 Comparing Business Process Reengineering and TQM 304

10.8 Organizational Implications of Different Approaches 304

10.8.1. Quadrants I & IV:

Incremental improvement/Learning By Doing 305

10.8.2 Quadrant II:

Transferring Incremental Improvement Across Organizations 305

10.8.3 Quadrant III:

Breakthrough Improvement through Strategic Leaps 306

10.8.4 Quadrant IV: Breakthrough Improvement through Sustained

Incremental Efforts 307

10.8.5 The Risks of Different Approaches 309

Notes 311


Appendix

I0A.1 Calculating Learning Curves 313

10A.2 Using Experience Curves in Developing a Competitive Strategy 314

11. Guiding the Pursuit of an Operations Edge 316

11.1 Introduction 316

11.2 Why Do Companies Lose Their Competitive Advantage? 317

11.2.1 The False Promise of Simplistic Solutions 318

11.2.2 The Dynamics of Organizational Stagnation 321

11.3 Creating an Improvement Strategy 323

11.3.1 Tightly Focused, Top Management-Driven

Improvement Programs 325

11.3.2 Broadly Based, Diffused Improvement Programs 330

11.3.3 Top Management Directed, Staged Improvement Programs 333 I 1.4 Stepping Back: The Concept of "Improvement Pathways" 334

11.5 Operations Role: From Reactive to Proactive 339

Implications of Moving from a Reactive to a Proactive Role 340

11.6 Management: The Ultimate Source of Sustainable Advantage 341

Notes 343

Bibliography 345

Index 357

July 18, 2022

Management Science of Transformations - Breakthrough Improvements

 

I strongly support development and use of management science. In the area of productivity, I promote productivity science. McKinsey consultants published number of articles and papers on the "Management Science of Transformations."


The 24 actions of transformation

24 practical actions were identified based on the experience of McKinsey consultants as the supporting actions for  the successful implementation of a transformation. (Below are the list of actions in order of their impact (from greatest to least) on the likelihood of a transformation’s success, according to the results of a survey conducted among industry executives.

Senior managers communicated openly across the organization about the transformation’s progress and success

Everyone can see how his or her work relates to organization’s vision

Leaders role-modeled the behavior changes they were asking employees to make

All personnel adapt their day-to-day capacity to changes in customer demand

Senior managers communicated openly across the organization about the transformation’s implications for individuals’ day-to-day work

Everyone is actively engaged in identifying errors before they reach customers

Best practices are systematically identified, shared, and improved upon

The organization develops its people so that they can surpass expectations for performance

Managers know that their primary role is to lead and develop their teams

Performance evaluations held initiative leaders  accountable for their transformation contributions

Leaders used a consistent change story to align organization around the transformation’s goals

Roles and responsibilities in the transformation were clearly defined

All personnel are fully engaged in meeting their individual goals and targets

Sufficient personnel were allocated to support initiative implementation

Expectations for new behaviors were incorporated directly into annual performance reviews

At every level of the organization, key roles for the transformation were held by employees who actively supported it

Transformation goals were adapted for relevant employees at all levels of the organization

Initiatives were led by line managers as part of their day-to-day responsibilities

The organization assigned high-potential individuals to lead the transformation (e.g., giving them direct responsibility for initiatives)

A capability-building program was designed to enable employees to meet transformation goals

Teams start each day with a formal discussion about the previous day’s results and current day’s work

A diagnostic tool helped quantify goals (e.g., for new mind-sets and behaviors, cultural changes, organizational agility) for the transformation’s long-term sustainability

Leaders of initiatives received change-leadership training during the transformation

A dedicated organizing team (e.g., a project management or transformation office) centrally coordinated the transformation

https://www.mckinsey.com/~/media/mckinsey/business%20functions/people%20and%20organizational%20performance/our%20insights/how%20to%20beat%20the%20transformation%20odds/how_to_beat_the_transformation_odds.pdf

They asked executives of a sample the actions they have taken among the list and their opinion on the success of the transformation initiative.


The science behind transformations: Maximizing value during implementation

Our latest transformation research shows that the largest share of value loss happens during implementation. What can leaders do to prevent it?

https://www.mckinsey.com/business-functions/people-and-organizational-performance/our-insights/the-organization-blog/the-science-behind-transformations-maximizing-value-during-implementation

https://www.mckinsey.com/business-functions/transformation/our-insights

https://www.mckinsey.com/business-functions/transformation/our-insights/how-many-people-are-really-needed-in-a-transformation

https://www.mckinsey.com/~/media/mckinsey/business%20functions/people%20and%20organizational%20performance/our%20insights/successful%20transformations/december%202021%20losing%20from%20day%20one/losing-from-day-one-why-even-successful-transformations-fall-short-final.pdf

https://www.mckinsey.com/business-functions/rts/how-we-help-clients

https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/five-moves-to-make-during-a-digital-transformation

https://www.linkedin.com/pulse/odds-transformation-24-actions-srikanth-ghanta/

https://hbr.org/2016/10/organizations-cant-change-if-leaders-cant-change-with-them

Best Management Consulting Firms

 

America's Best Management Consulting Firms 2022


https://www.forbes.com/best-management-consulting-firms/   


In 2022,  218 firms were classified as the best firms. The firms that received the most recommendations are ranked according to star ratings: five stars for “very frequently recommended,” four stars for “frequently recommended” and three stars for “recommended.”



Strategy


5 Star Rating


Name

CEO/Principal

Year Founded

Headquarters


Accenture

Julie Spellman Sweet

1989

Dublin, Ireland


Bain & Company

Manny Maceda

1973

Boston, Massachusetts


BCG (Boston Consulting Group)

Christoph Schweizer

1963

Boston, Massachusetts


IBM

Arvind Krishna

1911

Armonk, New York


McKinsey & Company

Bob Sternfels

1926

New York, New York


Microsoft

Satya Nadella

197

Redmond, Washington

Marketing, Brandng & Pricing

Name
CEO/Principal
Year Founded
Headquarters


Accenture
Julie Spellman Sweet
1989
Dublin, Ireland

Bain & Company
Manny Maceda
1973
Boston, Massachusetts

BCG (Boston Consulting Group)
Christoph Schweizer
1963
Boston, Massachusetts

McKinsey & Company
Bob Sternfels
1926
New York, New York

Operations


Name
CEO/Principal
Year Founded
Headquarters


Accenture
Julie Spellman Sweet
1989
Dublin, Ireland

Deloitte
Punit Renjen
184
London, United Kingdom

IBM
Arvind Krishna
1911
Armonk, New York

KPMG
Bill Thomas
1987
Amstelveen, Netherlands

Microsoft
Satya Nadella
197
Redmond, Washington






2021
https://www.forbes.com/sites/samanthatodd/2021/03/16/meet-americas-best-management-consulting-firms-2021/    
Samantha Todd, Forbes Staff
I cover leadership, the C-suite and small business.
Mar 16, 2021

The 230 firms were classified as best firms. They received the most recommendations and are ranked according to star ratings: five stars for “very frequently recommended,” four stars for “frequently recommended” and three stars for “recommended.”

Accenture has served 6,000 clients in more than 120 countries.


Operations, Strategy, and Technology: Pursuing the Competitive Edge - Hayes et al - Table of Contents - Book Information

 


Hayes, Pisano, Upton, Wheelwright: Operations, Strategy, and Technology: Pursuing the Competitive Edge



Table Of Contents

Chapter 1: Operations Management Confronts a New Millennium

Chapter 2: Operations Strategy: Origins and New Directions

Chapter 3: Capacity Strategy

Chapter 4: Determining Organizational Boundaries: Vertical Integration and Outsourcing

Chapter 5: Designing and Managing Operating Networks

Chapter 6: Information Technology and Operations

Chapter 7: Creating an Edge Through New Process Development

Chapter 8: Creating an Edge Through Superior Project Management

Chapter 9: Evaluating and Justifying Capital Investments

Chapter 10: Sharpening the Edge: Driving Operations Improvement

Chapter 11: Guiding the Pursuit of an Operations Edge


Lecture notes available in above link.

Sections in chapters

Chapter 1: Operations Management Confronts a New Millennium



Chapter 2: Operations Strategy: Origins and New Directions

Chapter 3: Capacity Strategy

Chapter 4: Determining Organizational Boundaries: Vertical Integration and Outsourcing

Chapter 5: Designing and Managing Operating Networks

Chapter 6: Information Technology and Operations

Chapter 7: Creating an Edge Through New Process Development

7.1 Introduction

7.2 How Process Development and Operations Interact

7.3 Leveraging Process Development Capabilities for Competitive Advantage

7.4 Achieving Speed, Efficiency, and Quality in the Development of New Processes

7.5 Process Development in Perspective

Chapter 8: Creating an Edge Through Superior Project Management

Chapter 9: Evaluating and Justifying Capital Investments

Chapter 10: Sharpening the Edge: Driving Operations Improvement

Chapter 11: Guiding the Pursuit of an Operations Edge

11.1 Introduction

11.2 Why do companies lose their competitive advantage?


Operations, Strategy,

and Technology

Pursuing the Competitive Edge

Robert Hayes

Harvard University

Gary Pisano

Harvard University

David Upton

Harvard University

Steven Wheelwright

Harvard University

WILEY

www.wiley.com/college/hayes

Contents 1. Operations Management Confronts a New Millennium 1

1.1 Introduction 1

1.1.1 The World Business Context 3

1.1.2 The Evolving Bases of Competition 7

1.2 Growing Disillusionment with the New Approaches to Operations 9

1.2.1 The Limits of the NAOs II

1.2.2 The Limits of Process Reengineering 12

1.2.3 The Limits of Emulating "Best Practice" 13

1.3 Managing in the New World Economy 14

1.3.1 Globalization 14

1.3.2 Information Technology and Information-Intensive Operations 15

1.3.3 What's Different in Information-Intensive Operations? 17

1.3.4 Summarizing the Differences: O.M. in the Old and

New Economies 23

1.3.5 Redefining the Boundaries of Organizations and

Operations Management: 23

1.4 The Information Economy's Challenges for

Operations Management 26

1.5 An Outline of This Book 27

1.5.1 Operations Strategy 27

1.5.2 Operations Technology 29

1.5.3 Operating Improvement 30

Notes 31 2. Operations Strategy: Origins and New Directions 33

2.1 Introduction 33

2.2 The Concept of Strategy 34

2.2.1 Company Values—The Foundation for Strategy 36

2.3 The Operations Edge:

Creating a Competitive Advantage through Operations 36

2.3.1 The "American System": Mass Production for Mass Markets 37

2.3.2 The Japanese System: "Lean Production" 38

2.3.3 A Contingency Theory of Operations Strategy: Fit and Focus 38

2.3.4 Key Decisions Involved in Operations Strategy Implementation 41

2.3.5 Responding to Evolving Strategies, Markets, and Technologies 47

2.3.6 Strategy as an Art Form 49 xv

xvi Contents

2.4 Challenges to the Operations Strategy Framework 49

2.4.1 Challenging the Necessity for Trade Offs 50

2.4.2 Challenging the Importance of Focus 51

2.5 Dynamic Organizational Capabilities 52

2.5.1 Path Dependencies: '

Reexamining Focus and Tradeoffs from a New Perspective 54

2.5.2 Strategic Choice in Operations 55

2.6 Attacking and Defending through Operations 56

2.6.1 Attacking through Operations 59

2.6.2 Sustaining an Operations Edge 64

2.6.3 Defending through Operations 65

2.6.4 Lessons in Attacking and Defending through Operations 66

2.7 Conclusion 68

Notes 68

Appendix . .

2A.I Evaluating an Operations Strategy 71

2A.2 The Concept of a Corporate Operations Strategy 72

2A.2.1 The Corporation's Dominant Orientation 74

2A.2.2 The Pattern of Diversification 74

2A.2.3 The Altitude toward Growth 74 3. Capacity Strategy 76

3.1 Overview 76

3.2 How Capacity and Operations Management Interact 78

3.2.1 The Impact of Variability on Capacity 80

3.2.2 Alternative Approaches for Expanding Capacity 82

3.2.3 The Consequences of a Capacity Squeeze 83

3.3 The Timing of Capacity Increments—The Capacity Cushion 85

3.3.1 Policy A: Lead Demand with Capacity 86

3.3.2 Policy B: Build to the Forecast 86

3.3.3 Policy C: Add Capacity Only after Demand Exceeds It 87

3.3.4 Alternative Types of Capacity Cushion 87

3.3.5 Determining the Appropriate Capacity Cushion 89

3.4 The Sizing of Capacity Increments—Scale Considerations 92

3.4.1 Economies of Scale 92

3.4.2 Diseconomies of Scale 98

3.4.3 Increasing Economies of Scale 100

3.4.4 Optimal Economic Size 101

3.5 Developing a Capacity Strategy 103

3.6 Four Philosophies of Capacity Expansion 105

3.7 Integrating a Firm's Capacity Strategy with

Its Business Strategy 107

Notes 109

Contents xvii

Appendix

3A.1 Justifying the Simple Formula (3-2) for Estimating the Amount of

Capacity Cushion Warranted by a Given Cost Structure and

Demand Distribution 111

3A.2 Models for Evaluating Simple Capacity Expansion Strategies 1 11

3A.2A The Discounted Present Value of Simple Capacity Strategies in a

Growing Market, Assuming No Shortfalls in Capacity

Are Permitted 112 A Numerical Example 113

3A.23 A Minimum Cost Capacity Strategy When Shortfalls

Are Permitted 114

Notes 115 4. Determining Organizational Boundaries:

Vertical Integration and Outsourcing 116

4.1 Introduction 116

4.2 Trends and Evidence 116

4.3 Framing Vertical Integration and Sourcing Decisions 119

4.3.1 What Are the Choices? 120

4.4 Factors Influencing Vertical Integration Decisions 123

4.4.1 Capabilities/Resources 123

4.4.2 Coordination Requirements 125

4.4.3 Strategic Control and Risks 128

4.4.4 Protecting Intellectual Property 134

4.5 Summary 136

Notes 138 5. Designing and Managing Operating Networks 139

5.1 Introduction 139

5.2 The Rationale for Multifacility Networks 140

5.3 Designing the MuUifacility Network: Structure 142

5.3.1 Number and Size 142

5.3.2 Location 142

5.3.3 Specialization 143

5.3.4 Mixed Networks 145

5.3.5 Selecting between Horizontal and Vertical Network Structures 147

5.4 Managing the Network: Infrastructure 150

5.5 Managing Different Network Structures 152

5.5.1 Horizontal Networks 152 ' 5.5.2 Vertical Networks 153

5.5.3 Centralization versus Decentralization 154

5.5.4 Implementing and Maintaining Focus 157

5.6 The Dynamics ol Horizontal Networks 158

xviii Contents

5.7 The Dynamics of Vertical Networks 160

5.7.1 Vertical Supply Chain Dynamics: The Bullwhip Effect 161

5.7.2 Dealing with the Coordination Problem 164

5.7.3 An Example: Managing the Bullwhip 165

5.7.4 Some Concluding Thoughts on Supply Chain Management 166

Notes 167 6. Information Technology and Operations 169

6.1 Introduction 169

6.2 The Expanding Role of IT 169

6.2.1 IT in Operations 169

6.2.2 Expansion of IT to Business and Network Operations 172

6.2.3 Enterprise Resource Planning 172

6.2.4 The Impact of the Internet 174

6.3 The Challenges of Integration, Standards, and Fit 175

6.3.1 Making IT Decisions that '"Fit" 175

6.3.2 How Did We Get into This Mess? 176

6.3.3 Selecting Standards 178

6.3.4 Principles and Decisions in IT Design 180

6.4 Strategic Hazards 180

6.4.1 Hazards to Disiinctiveness:

The Rebirth of the "One Best Way" 180

6.4.2 Hazards to Strategic Flexibility: IT as "Liquid Concrete" 181

6.5 Implementing IT Systems: Two Approaches 183

6.6 Making IT "Matter" 188

Notes 189

Appendix

6A.I Standards and Integration Outside the Firm 191 An Example of the Application of

New Communication Standards 191

6A.2 Open Source Software 193

Notes 194 7. Creating an Edge through New Process Development 195

7.1 Introduction 195

7.2 How Process Development and Operations Interact to Facilitate New

Product Development 196

7.2.1 The Product Life Cycle Concept Revisited 197

7.2.2 Mapping the Context 198

7.3 Leveraging Process Development Capabilities for

Competitive Advantage 199

7.3.1 Accelerated Time to Market 199

7.3.2 Rapid Ramp-Up 201

Contents xix

7.3.3 Enhanced Customer Acceptance 202

7.3.4 Stronger Proprietary Position 203

7.4 Achieving Speed, Efficiency, and Quality in the Development of

New Processes 203

7.4.1 Integrating Product and Process Development 204

7.4.2 Timing the Transfer of New Process

Technologies into Operations 208

7.4.3 Centralized versus Decentralized Process Development and

Technology Choices 213

7.5 Process Development in Perspective 217

Notes 217 8. Creating an Edge through Superior Project Management 219

8.1 Introduction 219

8.2 Two Historical Approaches to Project Management 220

8.2.1 Critical Path Analysis 220

8.2.2 Stage-Gate Approaches 224

8.3 Creating, Selecting, and Managing Project Portfolios 227

8.3.1 Seeding: Encouraging a Rich Mix of Alternative Project Ideas 228

8.3.2 Weeding and Feeding:

Winnowing Project Ideas and Providing Resources 229

8.3.3 Cultivating the Project Portfolio 232

8.3.4 Plowing Under 234

8.4 Maintaining Discipline and Focus in the Project Portfolio 234

8.5 Designing a Strategy for Project Execution 236

8.5.1 Project Definition 237

8.5.2 Project Teams 237 .

8.5.3 Structuring the Flow of Project Tasks and Activities 239

8.5.4 Methodologies for Design, Prototyping, and Testing 241

8.5.5 Senior Management Review and Control 242

8.5.6 A Contingent Model of Project Management 242

8.6 Learning from Project Experience 242

Notes 246 9. Evaluating and Justifying Capital Investments 247

9.1 Introduction 247

9.2 Managing the Investment Planning Process 249

9.2.1 Evaluate Existing Operations 250

9.2.2 Forecast Capacity and Competitive Requirements 250

9.2.3 Define Alternatives for Meeting Requirements 252 ' 9.2.4 Perform Financial Analyses of Each Alternative 253

9.2.5 Assess Key Qualitative Issues for Each Alternative 253

9.2.6 Select and Defend the Alternative to Be Pursued 254

9.2.7 Implement the Chosen Alternative 254

9.2.8 Audit Actual Results 255

xx Contents

9.3 Financial Analysis of Proposed Investments 255

9.3.1 A Framework for Assessing the Financial Attractiveness of

Proposed Investments

 ; 256

9.3.2 Measures of Security 257

9.3.3 Measures of Recompense 259 '

9.3.4 Recompense—The Accumulated Cash Balance 260

9.3.5 Recompense—The Net Present Value 261

9.3.6 Recompense—The Internal Rate of Return 264

9.3.7 Measures of Predictability 266

9.3.8 Assessing a Proposed Investment's Option Value 270

9.3.9 Caveat Calculator! 273

9.4 Integrating Investment Proposals into Long-Term Strategies 275

Notes 111

10. Sharpening the Edge: Driving Operations Improvement 279

10.1 Introduction 279

10.2 A Framework for Analyzing Organizational Improvement 280

10.2.1 A Macro Perspective: Learning and Experience Curves 280

10.2.2 Different Mechanisms for Driving

Organizational Improvement 281

10.3 "Within" vs. "Across" Group Improvement 282

10.3.1 Enablers of, and Constraints on,

"Within" Group Improvement 282

10.3.2 Transferring Improvement Across Groups 287

10.4 Learning by Doing vs. Learning before Doing 288

10.5 Transferring Learning In from Outside the Organization 289

10.6 Breakthrough vs. Incremental Improvement 291

10.6.1 Implementing Strategic Leaps 292

10.6.2 Implementing Incremental Improvement 293

10.7 A Framework for Improvement Activities, with Two Examples 297

10.7.1 Example A: Business Process Reengineering 298

10.7.2 Example B: Total Quality Management (TQM) 301

10.7.3 Comparing Business Process Reengineering and TQM 304

10.8 Organizational Implications of Different Approaches 304

10.8.1. Quadrants I & IV:

Incremental improvement/Learning By Doing 305

10.8.2 Quadrant II:

Transferring Incremental Improvement Across Organizations 305

10.8.3 Quadrant III:

Breakthrough Improvement through Strategic Leaps 306

10.8.4 Quadrant IV: Breakthrough Improvement through Sustained

Incremental Efforts 307

10.8.5 The Risks of Different Approaches 309

Notes 311

Contents xxi

Appendix

I0A.1 Calculating Learning Curves 313

10A.2 Using Experience Curves in Developing a Competitive Strategy 314

11. Guiding the Pursuit of an Operations Edge 316

11.1 Introduction 316

11.2 Why Do Companies Lose Their Competitive Advantage? 317

11.2.1 The False Promise of Simplistic Solutions 318

11.2.2 The Dynamics of Organizational Stagnation 321

11.3 Creating an Improvement Strategy 323

11.3.1 Tightly Focused, Top Management-Driven

Improvement Programs 325

11.3.2 Broadly Based, Diffused Improvement Programs 330

11.3.3 Top Management Directed, Staged Improvement Programs 333 I 1.4 Stepping Back: The Concept of "Improvement Pathways" 334

11.5 Operations Role: From Reactive to Proactive 339

Implications of Moving from a Reactive to a Proactive Role 340

11.6 Management: The Ultimate Source of Sustainable Advantage 341

Notes 343

Bibliography 345

Index 357

Ud. 19.7.2022,  3.2.2022

Pub 22.8.2021

July 11, 2022

Best Practices in Remote Working - Prof. Tsedal Neeley

 


https://hbswk.hbs.edu/item/succeeding-in-the-new-work-from-anywhere-world


Remote Work Revolution - Prof. Tsedal Neeley

__________________



__________________ 

Developing a Digital Mindset


Digital mindset as a set of approaches we use to make sense of, and make use of, data and technology.

Once people are able sense data and related technology and figure ways of using them, they see new possibilities and chart a path for the future. 

This set of attitudes and behaviors enable people and organizations to see new possibilities and chart a path for the future. 


https://www.linkedin.com/pulse/developing-digital-mindset-following-30-rule-tsedal-neeley/ 


https://hbswk.hbs.edu/item/why-digital-is-a-state-of-mind-not-a-skill-set


Digital Mindset by Tsedal Neeley


Regularly advises top leaders who are embarking on virtual work and large scale-change that involves global expansion, digital transformation, and becoming more agile. Recent work provides remote workers and leaders with the best practices necessary to perform at the highest levels in their organizations.

https://thinkers50.com/biographies/tsedal-neeley/

July 10, 2022

Learn - How to Become Industry 4.0 Digital Manufacturing Champion

Do You Want 55% Increase in Efficiency in the Next 5 Years?

Become Digital Champion.

Possible Efficiency Gains in the Next 5 Years due to Digital Manufacturing


Digital novice - 5%
Digital followers - 15 to 25%
Digital innovator  35 to 45%
Digital  champion greater than 55%

Industry 4.0 manufacturing and distribution systems utilize end-to-end digitization and data integration in all information generation, processing, analysis & decision making and communication activities. Industry 4.0 companies offer along with traditional products, digitally enhanced products and digital products/services also. In these production systems there are digital twins, physical assets and virtual assets that are connected and communicate. The connected information systems integrate all suppliers, all customers and all manufacturing and service facilities of the enterprise. Each and every machine and each and every person are connected in these digital manufacturing companies/factories.

Mastering Industry 4.0 implementation and transformation requires initial learning and subsequent deep understanding of the scientific and managerial knowledge and technologies of Industry 4.0 by the complete enterprise staring with the top management. A top management with a compelling vision for  the transformation is essential for the company to become  a champion.

PWC, one of the top management consultancy organizations did a survey in 2018 about the implementation status of Industry 4.0 and identified digital champions from 1100 companies surveyed. 10 percent of the companies surveyed were classified as digital champion companies.

Four ecosystems are essential in digital manufacturing systems: Customer ecosystem, Operating ecosystem (suppliers, manufacturing facilities, internal logistics, external logistics), Technology ecosystem and People ecosystem.

Customer ecosystem is the basis for exchange of information and value. Integrated operations, technology and people ecosystems serve the customers through the customer ecosystem that is integrated with the other three ecosystems.

Digital champions implement new digital technologies in purposeful manner and deploy them in various application in value creating mode. They are able apply the technologies in multiple applications by employing partners instead of slowing down implementation due to paucity of internal talent.

Artificial intelligence is being used in 9 per cent of companies and its use is increasing. Employees with relevant digital skills are required and they are in short supply. Hence tailored training programs development and organization are crucial. Digital champions have to invest heavily in people development training. 

How to Become Industry 4.0 Digital Manufacturing Champion? - Blueprint


1. Invest in Learning Industry 4.0 Knowledge and Skills
2. Conduct an Audit of Four Ecosystems - Customer, Operations, Technology, and People
3. Define Ecosystem Vision and Value Proposition
4. Develop a Model for Each Ecosystem
5. Set Ecosystem Project Investment Decision Board and Encourage Project Proposals
6. Approve Projects and Build EcoSystem Components. Improve Capabilities iteratively
7. Realize the Value of the New Production System
8. Reinvest and Expand Operations


Read the excerpts and  download PWC Report from https://www.strategyand.pwc.com/industry4-0


Customer Ecosystem - Subsystems and Components 



Products
Complementary Products
Performance Services
Financial Solutions

Digital Technology
Hardware and Infrastructure
Software and Apps
Platform Integration
Third Party Platforms
E Commerce Service
Advanced Customer Services
Demand Signals and Insights
Data Acquisition and Analytics

Multichannel Interaction
Customization of Product and Service

Operations Ecosystem - Subsystems and Components

The Operations ecosystem encompasses the physical activities and flows that support the customer solution offering. These might include product development, planning, sourcing, manufacturing, warehousing, logistics and services. Any external partners that are part of a company’s operations, including contract manufacturers, logistics partners and academia, are part of this ecosystem.


Digital Research and Development
Procurement 4.0
Smart Manufacturing - Connected Manufacturing System
Connected Logistics and Distribution - Smart Warehouses and Trucks
After Sales Services - Digital Channels and Digital Support to Service Professionals
Product Life Cycle Management
Digital Industrial Engineering (Computer Aided Industrial Engineering - CAIE)
(IE redesigns facilities, products and processes to increase productivity)


Persons and Firms as Partners

Research Institutes
Open Innovation Platforms and Participants
Development Partners
Development Stage Component and Material Suppliers

Materials Suppliers
Component Suppliers
Internal Production Facilities
Contract Manufacturers
Inbound Logistics Service Providers
Warehouses and Distribution Centers
Transporters and Last Mile Delivery Centers and Facilities
Repair Centers
Service Providers

Digital Champions - Bosch, Daimler Benz

Digital Transformation at Daimler Benz - Now Daimler is Digital Champion of PWC Survey

The Technology Ecosystem - Subsystems and Components




Digital Technologies

Blockchain
Sensors
IIoT
3D Printing
Robots
Artificial Intelligence
Augmented Reality
Virtual Reality
Drones
Automated Guides Vehicles
Mobile Devices
Driverless Trucks

Networks and Connectivity
Cloud Computing
Edge Computing

Integrated Platforms
Human Machine Interfaces
User Experience
Data Networks
Integration Layers

Applications

Core ERP
CRM
Integrated Business Planning Models
Manufacturing Execution Systems
Data Analytics
PLM and Digital Twins

2018 Survey

At least 90 percent of Digital Champions have already implemented, piloted, or planned some of the most critical current technologies. 


• Integrated end-to-end supply chain planning (100 percent of Digital Champions)
• Predictive maintenance of assets and products (96 percent)
• Manufacturing execution systems (94 percent)
• Industrial Internet of Things (97 percent)
• Digital twins, which essentially are virtual versions of physical assets or products, such as factories, that can be used for digitally supported planning, scheduling, and product development, among other 
possibilities (94 percent)
• Advanced robotics (90 percent)

By comparison, only about one-third of Digital Novices have adopted the most common operational technologies, like predictive maintenance (39 percent) and integrated supply chain planning (32 percent).

People Ecosystem - Subsystems and Components


Skills - Skill Sources - Mindset and Behavior - Career Development

Skills

Skill Sources

Mindset and Behavior

Career Development




Updated 11.7.2022, 11July 2021
Pub 11 July 2018


July 9, 2022

What is Data Science? - Evolution of Data Science

Excerpts from Global Data Science Forum What is Data Science?
By Paco Nathan posted Mon March 04, 2019
https://community.ibm.com/community/user/datascience/blogs/paco-nathan/2019/03/04/what-is-data-science

What is Data Science?

A popular 2012 tweet by Josh Wills:

Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician.

Data Science gained traction in industry circa 2008, just as tooling for big data was on the rise, and as business use cases for machine learning (ML) became popularized. Those three grew together in contrast to an earlier era of business intelligence (BI), which was initially popularized by Gartner analyst Howard Dresner. Most of BI was defined atop data warehouse (DW) practices, based on work by Barry Devlin and Paul Murphy, Ralph Kimball, Bill Inmon, et al. BI and DW were both introduced in the late 1980s, then became widespread practices throughout the 1990s.

Data science emerged in response to demand for more advanced techniques and larger scale-out than what the best practices from the prior decade could provide. Cloud resources were becoming popular, and crucial insights could be obtained more quickly and more cost-effectively due to popular open source tools such as Hadoop, Spark, plus a whole range of Python libraries.

In 1962, a Bell Labs mathematician named John Tukey wrote a paper called “The Future of Data Analysis”.  Tukey urged a provocative new stance for applied mathematics which he called data analysis. The interesting section headings are:

“We should seek out wholly new questions to be answered.”
“We need to tackle old problems in more realistic frameworks.”
“We should seek out unfamiliar summaries of observational material, and establish their useful properties.”
“And still more novelty can come from finding, and evading, still deeper lying constraints.”

In the  books on visualizing data by Ed Tufte, references to Tukey show up throughout most all of books.

A generation later, another Bell Labs researcher named William Cleveland coined the term data science in a 2001 paper citing Tukey among others,  “Data science: An action plan for expanding the technical areas of the field of statistics”. Cleveland proposed an outline for a multi-disciplinary curriculum:

(25%) Multidisciplinary Investigations: data analysis collaborations in a collection of subject matter areas.
(20%) Models and Methods for Data: statistical models; methods of model building; methods of estimation and distribution based on probabilistic inference.
(15%) Computing with Data: hardware systems; software systems; computational algorithms.
(15%) Pedagogy: curriculum planning and approaches to teaching for elementary school, secondary school, college, graduate school, continuing education, and corporate training.
(5%) Tool Evaluation: surveys of tools in use in practice, surveys of perceived needs for new tools, and studies of the processes for developing new tools.
(20%) Theory: foundations of data science; general approaches to models and methods, to computing with data, to teaching, and to tool evaluation; mathematical investigations of models and methods, of computing with data, of teaching, and of evaluation.

This curriculum indicates what Cleveland thought the field required, namely that data science is a space in which statistics and computing needed to interact, to provide the necessary resources and scale.

That same year, a UC Berkeley professor named Leo Breiman wrote “Statistical Modeling: The Two Cultures”. One culature is of the previous era which he called data modeling and a new trend emerging which he called algorithmic modeling. That culture of data modeling was what Tukey had argued against.  The newer culture embraced much larger data rates and more computation and also leveraged machine learning algorithms to help automate decisions at scale.

The current heyday of data science began when some of these applications which required more data started to become tractable, reliable, and cost-effective (in that order).

Check out these histories by lead architects at those firms – roughly centered on Q3 1997, which turned out to be a key inflection point for the Dot Com Boom:

“Early Amazon: Splitting the website”, Greg Linden, Amazon
“eBay Architecture”, Randy Shoup, eBay
“Inktomi’s Wild Ride”, Erik Brewer, Yahoo! Search (0:05:31 ff)
“Underneath the Covers at Google”, Jeff Dean, Google (0:06:54 ff)

The timing for those projects was during the peak of data warehouses and business intelligence adoption. However, a common theme among those four architects’ reflections is that they recognized how they’d need to scale ecommerce applications but could not do so with available tooling. Instead they turned to open source tools (such as Linux) for early data science work on proto clouds, leveraging ML at scale for ecommerce. Their timing was impeccable, particularly for Amazon: just in time to monetize the first big wave of ecommerce in the holiday season of Q4 1997. The rest is history.

The gist is that ecommerce firms split their web apps using a principle of horizontal scale out, i.e., proto cloud work on server farms. Those many servers generated lots of log files (proto Big Data), which in turn were analyzed using machine learning algorithms, which in turn provided predictive analytics that improved customer experience in the web apps. A virtuous cycle emerge, with data as a product.

However, after Q4 1997 the world of data changed, predictive analytics loomed large. Breiman described that sea change quite succinctly:

A new research community using these tools sprang up. Their goal was predictive accuracy. The community consisted of young computer scientists, physicists and engineers plus a few aging statisticians. They began using the new tools in working on complex prediction problems where it was obvious that data models were not applicable: speech recognition, image recognition, nonlinear time series prediction, handwriting recognition, prediction in financial markets.

Plenty of other people also helped further the cause of “data science” and deserve credit, such as Jeff Wu who likely coined the phrase (in its contemporary usage) during his U Michigan appointment lecture “Statistics = Data Science?”

The main takeaway from this article:

Looking at decades of history, data science found its place by applying increasingly advanced mathematics for novel business cases, in response to surges in data rates and compute resources.

In the latest wave of AI applications in industry, we have the term ABC emerging to describe a winning combo of “AI”, “Big Data”, and “Cloud Computing” – as the latest embodiment of that takeaway described above.

Beyond the well-known roles of data scientist and data engineer, there’s another important role emerging which has not yet been named. We found that 23% of the enterprise organizations attempting to leverage data science, machine learning, artificial intelligence, etc., cite recognize business use case as a critically missing skill within their teams. What would you call that role? Where and how does a person learn to perform it?

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 In a 2009 McKinsey&Company article, Hal Varian, Google's chief economist and UC Berkeley professor of information sciences, business, and economics, predicted the importance of adapting to technology’s influence and reconfiguration of different industries. 2

“The ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it — that’s going to be a hugely important skill in the next decades.”
https://datascience.berkeley.edu/about/what-is-data-science/

Chapter 1. Introduction: What Is Data Science?
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https://www.oreilly.com/library/view/doing-data-science/9781449363871/ch01.html

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https://www.simplilearn.com/data-science-vs-big-data-vs-data-analytics-article

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Updated on 10.7.2022,  31 May 2019, 26 May 2019