Data Driven (eBook)

Jeremy David Curuksu is a data scientist, management consultant and researcher. He worked at the strategy firm Innosight, at the Chief Analytics Office of IBM and at Amazon Web Services. He holds a PhD in bioinformatics and was a research scientist for 6 years in applied mathematics at the Polytechnic School of Lausanne in Switzerland and at the Massachusetts Institute of Technology in the US. He published multiple first-author peer reviewed articles and blog posts and presented 50+ seminars in data science and management consulting at MIT and at Harvard University. He is now advising Amazon’s clients and working on solving their business issues through the use of artificial intelligence.

Endorsements 5
Acknowledgments 6
Contents 7
Detailed Contents 8
List of Figures 12
List of Tables 13
About the Author 14
Introduction 15
1: Analysis of the Management Consulting Industry 19
1.1 Definition and Market Segments 19
1.1.1 The Value Proposition 19
1.1.2 Industry Life Cycle 20
1.1.3 Segmentation by Services 20
1.1.4 Segmentation by Sectors 22
1.1.5 Segmentation by Geography 27
1.2 Success Factors 29
1.3 Competitive Landscape 30
1.3.1 Basis of Competition 30
1.3.2 Emergence of New Information Technologies 30
1.3.3 Main Players 31
1.4 Operations and Value Network 32
2: Future of Big Data in Management Consulting 35
2.1 General Outlooks in the Management Consulting Industry 35
2.2 Future of Big Data in Management Consulting 36
2.2.1 Factors that Favor the Integration of Big Data in Management Consulting 36
2.2.2 Factors that Refrain the Transition 39
2.3 So What: A Scenario Analysis 40
3: Toolbox of Consulting Methods 45
3.1 Organizational Development 46
3.1.1 Strategic Planning 46
3.1.2 Innovation 46
3.1.3 Re-engineering 48
3.1.4 Scenario Planning 48
3.1.5 Brainstorming 49
3.1.6 Resource Allocation 49
3.1.7 Cost Optimization 50
3.1.8 Downsizing 50
3.2 Consumer Market Research 51
3.2.1 Documentary Research 51
3.2.2 Customer Segmentation 52
3.2.3 Surveys 52
3.2.4 Focus Group 54
3.2.5 Interviews 55
3.2.6 Big Data Analytics 56
3.2.7 Pricing 56
3.3 Competitive Intelligence 57
3.3.1 Supply Chain Management 57
3.3.2 Due Diligence 58
3.3.3 Benchmarking 58
3.3.4 Outsourcing 58
3.3.5 Mergers and Acquisitions 59
4: The Client-Consultant Interaction 60
4.1 Nature of the Relationship 60
4.1.1 The Big Picture: Theoretical Models 60
4.1.2 The Models in Practice 63
4.2 On the Client’s Expectations: Why Hire a Consultant? 66
4.3 Ethical Standards 68
4.4 The First Interview: Defining the Case and Objectives 69
4.4.1 Goals of First Meetings 69
4.4.2 Sample of Questions Consultant-to-Client 69
4.4.3 Sample of Questions Client-to-Consultant And How to Respond 70
4.5 Working with the Client During the Engagement 71
4.5.1 Clarifying Objectives 71
4.5.2 Executing Consulting Activities 72
4.5.3 Implementing the Recommendations 72
4.6 Stand and Deliver: Terminating the Assignment 72
4.6.1 Preparing the Slides 73
4.6.2 Delivering the Presentation 75
5: The Structure of Consulting Cases 77
5.1 How to Develop a Tailored Structure? 77
5.2 Proposition for a “One-Size-Fits-All” 79
5.3 The Profit Framework 80
5.4 The Pricing Framework 81
5.5 Operations 82
5.6 Growth and Innovation 83
5.7 Mergers and Acquisitions 85
5.8 New Ventures and Startups 86
6: Principles of Data Science: Primer 88
6.1 Basic Mathematic Tools and Concepts 90
6.2 Basic Probabilistic Tools and Concepts 96
6.3 Data Exploration 99
7: Principles of Data Science: Advanced 102
7.1 Signal Processing: Filtering and Noise Reduction 103
7.2 Clustering 106
7.3 Computer Simulations and Forecasting 108
7.3.1 Time Series Forecasts 109
7.3.2 Finite Difference Simulations 110
7.3.3 Monte Carlo Sampling 114
7.4 Machine Learning and Artificial Intelligence 117
7.4.1 Overview of Models and Algorithms 117
7.4.2 Model Design and Validation 124
7.4.3 Natural Language Artificial Intelligence 127
7.5 Case 1: Data Science Project in Pharmaceutical R& D
7.6 Case 2: Data Science Project on Customer Churn 137
8: Principles of Strategy: Primer 143
8.1 Definition of Strategy 143
8.2 Executing a Strategy 144
8.3 Key Strategy Concepts in Management Consulting 144
8.3.1 Specialization and Focus 144
8.3.2 The Five Forces 145
8.3.3 The Value Chain and Value Network 147
8.3.4 Integration 149
8.3.5 Portfolio Strategies 150
8.3.6 Synergy 152
8.3.7 The Ansoff Growth Matrix 153
8.3.8 Innovation Strategies 154
8.3.9 Signaling 158
8.4 Marketing Strategies 160
8.4.1 Customer Segmentation 160
8.4.2 Market Analysis 161
8.4.3 Competitive Analysis 162
8.4.4 Positioning 163
8.4.5 Benchmarking 165
9: Principles of Strategy: Advanced 167
9.1 Functional Strategy 167
9.1.1 Performance Strategies 167
9.1.2 Quality Management 170
9.1.3 Operation Strategies 172
9.1.4 Information Technology Strategies 173
9.1.5 Turnaround Strategies 175
9.1.6 Downsizing Strategies 176
9.2 Business Strategy 176
9.2.1 Marketing Strategies 176
9.2.2 Small Business Innovation Strategies 180
9.3 Corporate Strategy 181
9.3.1 Resource Allocation Portfolio Strategies 181
9.3.2 Outsourcing Strategies 182
9.3.3 Merger and Acquisition Strategies 182
9.3.4 Collaboration, Cooperation (and Coexistence…) Strategies 183
Conclusion 184
References 186
Index 195