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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