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More About This Title Business Analytics for Managers: Taking BusinessIntelligence Beyond Reporting
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A vital blueprint for organizations that want to thrive in the competitive fray, Business Analytics for Managers presents a sustainable business analytics (BA) model focusing on the interaction of IT technology, strategy, business processes, and a broad spectrum of human competencies and organizational circumstances.
Proven guidance on developing an information strategyTips for supporting your company's ability to innovate in the future by using analyticsAn understanding of BA as a holistic information discipline with links to your business's strategyPractical insights for planning and implementing BAHow to use information as a strategic assetWhy BA is the next stepping-stone for companies in the information age todayDiscussion on BA's ever-increasing roleFilled with examples and forward-thinking guidance from renowned BA leaders Gert Laursen and Jesper Thorlund, Business Analytics for Managers offers powerful techniques for making increasingly advanced use of information in order to survive any market conditions.
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GERT H.N. LAURSEN is head of customer intelligence at Maersk Line, the largest containerized shipping company in the world. He focuses on helping product-oriented organizations become more customer-centered through the use of various data sources, including data warehousing, questionnaires, and one-to-one interviews with customers, first-line staff, sales organizations, and other subject matter experts.
JESPER THORLUND is a business intelligence consultant and frequent speaker on business intelligence, business analytics, and microeconomics throughout Europe.
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Foreword ix
Introduction xi
What Does BA Mean? Information Systems—Not Technical Solutions xiv
Purpose and Audience xvi
Organization of Chapters xix
Why the Term Business Analytics? xx
Chapter 1 The Business Analytics Model 1
Overview of the Business Analytics Model 2
Deployment of the BA Model 6
Conclusions 12
Chapter 2 Business Analytics at the Strategic Level 17
Link Between Strategy and the Deployment of BA 18
Strategy and BA: Four Scenarios 19
Which Information Do We Prioritize? 31
Summary 40
Chapter 3 Development and Deployment of Information at the Functional Level 43
Case Study: A Trip to the Summerhouse 46
Establishing Business Processes with the Rockart Model 55
Example: Establishing New Business Processes with the Rockart Model 57
Optimizing Existing Business Processes 65
Example: Deploying Performance Management to Optimize Existing Processes 67
Which Process Should You Start with? 72
A Catalogue of Ideas with KPIs for the Company’s Different Functions 90
Summary 91
Chapter 4 Business Analytics at the Analytical Level 93
Data, Information, and Knowledge 94
Analyst’s Role in the BA Model 95
Three Requirements the Analyst Must Meet 98
Required Competencies for the Analyst 101
Hypothesis-Driven Methods 117
Data Mining with Target Variables 120
Explorative Methods 127
Business Requirements 130
Summary 134
Chapter 5 Business Analytics at the Data Warehouse Level 137
Why a Data Warehouse? 137
Architecture and Processes in a Data Warehouse 140
Tips and Techniques in Data Warehousing 160
Summary 168
Chapter 6 The Company’s Collection of Source Data 169
What Are Source Systems, and What Can They Be Used for? 170
Which Information Is Best to Use for Which Task? 174
When There is More Than One Way to Get the Job Done 177
When the Quality of Source Data Fails 179
Summary 180
Chapter 7 Structuring of a Business Intelligence Competency Center 183
What Is a Business Intelligence Competency Center? 183
Why Set Up a Business Intelligence Competency Center? 184
Tasks and Competencies 185
Centralized or Decentralized Organization 191
When Should a BICC Be Established? 197
Summary 200
Chapter 8 Assessment and Prioritization of BA Projects 201
Is it a Strategic Project or Not? 201
Uncovering the Value Creation of the Project 203
When Projects Run Over Several Years 209
When the Uncertainty Is Too Big 211
Projects as Part of the Bigger Picture 214
Summary 222
Chapter 9 Business Analytics in the Future 223
Index 231
