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  5. Global Business Analytics Models: Concepts and Applications in Predictive, Healthcare, Supply Chain, and Finance Analytics

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

  • Hokey Min

Published by Pearson FT Press (April 6th 2016) - Copyright © 2016

1st edition

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  • Practical techniques for developing reliable, actionable intelligence–and using it to craft strategy
  • Analytical opportunities to solve key managerial problems in global enterprises
  • Written for working managers: packed with realistic, useful examples

This guide helps global managers use modern analytics to gain reliable, actionable, and timely business intelligence–and use it to manage risk, build winning strategies, and solve urgent problems.


Dr. Hokey Min offers a practical, easy-to-understand overview of business analytics in a global context, focusing especially on managerial and strategic implications. After demystifying today’s core quantitative tools, he demonstrates them at work in a wide spectrum of global applications.


You’ll build models to help segment global markets, forecast demand, assess risk, plan financing, optimize supply chains, and more. Along the way, you’ll find practical guidance for developing analytic thinking, operationalizing Big Data in global environments, and preparing for future analytical innovations.


Whether you’re a global executive, strategist, analyst, marketer, supply chain professional, student or researcher, this book will help you drive real value from analytics–in smarter decisions, improved strategy, and better management.


In today’s global business environments characterized by growing complexity, volatility, and uncertainty, business analytics has become an indispensable tool for managing these challenges. Specifically, global managers need analytics expertise to solve problems, identify opportunities, shape strategy, mitigate risk, and improve their day-to-day operational efficiency.


Now, for the first time, there’s an analytics guide designed specifically for decision-makers in global organizations. Leveraging his experience teaching a number of students and training hundreds of managers and executives, Dr. Hokey Min demystifies the principles and tools of modern business analytics, and demonstrates their real-world use in global business.


First, Dr. Min identifies key success factors and mindsets, helping you establish the preconditions for effective analysis. Next, he walks you through the practicalities of collecting, organizing, and analyzing Big Data, and developing models to transform them into actionable insight.


Building on these foundations, he illustrates core analytical applications in finance, healthcare, and global supply chains. He concludes by previewing emerging trends in analytics, including the newest tools for automated decision-making.


Compare today’s key quantitative tools

Stats, data mining, OR, and simulation: how they work, when to use them


Get the right data…

…and get the data right


Predict the future…

…and sense its arrival sooner than others can


Implement high-value analytics applications…

…in finance, supply chains, healthcare, and beyond


Table of contents

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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