Global Business Analytics Models: Concepts and Applications in Predictive, Healthcare, Supply Chain, and Finance Analytics, 1st edition

Published by Pearson FT Press (March 5, 2016) © 2016

  • Hokey Min
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Business analytics can help you manage the accelerating risk and uncertainty associated with today’s global business environments. In Global Business Analytics Models, Hokey Min empowers managers to use today’s analytical tools and techniques to gain reliable, actionable international business intelligence, and to solve many of the most urgent problems their global businesses face.

Min offers a practical, easy-to-understand overview of business analytics in a global context, focusing especially on managerial and strategic implications. After demystifying the basic quantitative tools of modern analytics, he demonstrates them at work in global applications ranging from finance and supply chain management to healthcare. Coverage includes:

  • Developing analytic thinking, and operationalizing Big Data in global environments
  • Capitalizing on business analytics to build a winning global strategy
  • Collecting, sorting, prioritizing, storing, and managing data
  • Predicting international customer behavior, segmenting global markets, and forecasting demand in unfamiliar foreign markets
  • Performing international risk and assessments more effectively
  • Using analytics to help plan the financing of global business operations
  • Integrating international social and mobile analytics
  • Overcoming cultural and technical differences that complicate the use of analytics in global firms
  • Establishing effective performance metrics for your use of analytics
  • Taming Big Data for global Enterprise Resource Planning (ERP)
  • Making better decisions about global suppliers, manufacturing, distribution, transportation, and supply chain resilience
  • Analyzing clinical, pharmaceutical, and patient behavior data to improve healthcare
  • Anticipating future paths of innovation in global business analytics

Chapter 1: Introduction to Business Analytics    1

1.1 The Origin and Evolution of Business Analytics    1

1.2 Developing Analytical Thinking    4

1.3 Operationalizing Big Data from Global Perspectives    6

1.4 Extracting Useful Information from Big Data    9

1.5 Unique Challenges for Business Analytics    13

1.6 Capitalizing on Business Analytics for Building a Winning Global Strategy    15

Chapter 2: Collecting, Sorting, Prioritizing, and Storing Big Data    21

2.1 Finding and Capturing the Right Data    21

2.2 Data Sampling    23

2.3 Data Preparation    25

2.4 Data Segmentation    27

2.5 Data Filtering    29

2.6 Data Warehousing    31

2.7 Data Security    35

2.8 Fitting Analytics Models to Data    37

Chapter 3: Business Analytics Models    43

3.1 Quantitative Tools for Business Analytics    43

3.2 Basic Statistical Techniques    45

3.3 R Programming    48

3.4 Hypothesis Testing    49

3.4.1 t-Test    50

3.4.2 ANOVA Test    52

3.4.3 Nonparametric Test    52

3.5 Power Analysis    54

3.6 Data Mining    55

3.6.1 Decision Trees    56

3.6.2 Neural Networks    57

3.6.3 Text Mining    60

3.6.4 Image Mining    62

Chapter 4: Predictive Analytics    67

4.1 Predicting International Customer Behavior    67

4.2 Demand Forecasting in Unfamiliar Foreign Markets    68

4.2.1 Moving Average    69

4.2.2 Exponential Smoothing    70

4.2.3 Trend Analysis    72

4.2.4 Focus Forecasting    73

4.2.5 Agent-Based Forecasting    75

4.3 Global Market Basket Analysis    76

4.4 Risk Analytics    79

4.5 Digital Analytics    81

4.6 Social Sensing    83

4.7 Mobile Analytics    85

Chapter 5: Essentials for the Successful Implementation of Business Analytics    93

5.1 Understanding the Voice of Overseas Customers    93

5.2 Collaborating with Foreign Business Partners for Sharing Big Data    95

5.2.1 Building Trust    96

5.2.2 Establishing an Information Exchange Mechanism    96

5.2.3 Ensuring Secure Data Transmission    97

5.3 Analytics Execution and Implementation     98

5.4 Performance Measurement and Metrics    100

5.5 Outcome Analysis    102

5.6 Corrective Actions    103

5.7 Emulating Best-in-Class Practices    105

Chapter 6: Global Finance Analytics    109

6.1 Foreign Market Scenario Planning    109

6.2 Financing Global Business Operations through Capital Management    111

6.3 Global Financial Risk Assessment    113

6.3.1 Foreign Direct Investment Risk Analysis    114

6.3.2 Loan and Credit Risk Assessment    116

6.3.3 Liquidity Risk Assessment    117

6.3.4 Foreign Currency Exchange Risk Assessment    118

6.3.5 Value at Risk (VaR) as the Financial Risk Measure    121

6.4 Foreign Investment Portfolio Analysis    124

6.5 Product/Service Pricing Using Analytics     126

6.6 Multinational Profit Planning and Budgeting Using Analytics    128

Chapter 7: Global Supply Chain Analytics    135

7.1 Turning Integrated Big Data into Supply Chain Intelligence    135

7.2 Global Sales and Promotion Analytics    137

7.3 Global Sourcing Analytics    140

7.4 Contract Manufacturing Analytics    142

7.5 Distribution Analytics    145

7.6 Transportation Analytics    147

7.7 Integrating Functional Analytics into Global Supply Chain Management    151

Chapter 8: Healthcare Analytics    159

8.1 Healthcare Analytics as an Emerging Discipline    159

8.2 Big Data in Healthcare    161

8.3 Analyzing Clinical and Pharmaceutical Data    164

8.4 Analyzing the Voice of the Patient    167

8.5 Healthcare Quality Function Deployment via Analytics    169

8.6 Healthcare Outcome Analysis    171

Chapter 9: Future of Business Analytics    177

9.1 Innovating Analytics    177

9.2 Embedding Business Analytics into Enterprise-wide Information Systems    180

9.3 Future Roles of Business Analytics in Global Business Intelligence    181

9.4 Epilogue    183

Index    187

 

 

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