Business Analytics Principles, Concepts, and Applications What, Why, and How

Learn everything you need to know to start using business analytics and integrating it throughout your organization. Business Analytics Principles, Concepts, and Applications brings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives.

They offer a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making.

Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning.

Unlike most competitive guides, this text demonstrates the use of IBM's menu-based SPSS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself.

A valuable resource for all beginning-to-intermediate-level business analysts and business analytics managers; for MBA/Masters' degree students in the field; and for advanced undergraduates majoring in statistics, applied mathematics, or engineering/operations research.

MARC J. SCHNIEDERJANS (Lincoln, NE) is C. Wheaton Battey Distinguished Professor of Business in the College of Business Administration at the University of Nebraska-Lincoln, and a Fellow of the Decision Sciences Institute (DSI). His business experience includes owning and operating his own truck leasing business. A member of ISM, CSCMP, and POMS, he has taught extensively in operations management and management science, won numerous teaching awards, and is honorary member of the Golden Key Honor Society and Alpha Kappa Psi. He has authored or co-authored 20 books on management, is area editor for Operations Management Research, and has consulted with organizations ranging from Dow and Ralston Purina to Ontario Hydro.

DARA SCHNIEDERJANS (Kingston, RI), Assistant Professor of Supply Chain Management at University of Rhode Island's College of Business Administration, teaches courses in Supplier Relationship Management and Operations Management. She has published in several leading journals, co-authored two textbooks, co-edited a readings book, and was guest co-editor for a special issue on Business Ethics in Social Sciences in The International Journal of Society Systems Science.

CHRISTOPHER M. STARKEY (Storrs, CT),Economics Ph.D. student at the University of Connecticut-Storrs, has presented papers at the Academy of Management and Production and Operations Management Society meetings. Starkey's current research interests include macroeconomic and monetary policy, and other decision making methodologies.

Preface

Part 1. Introduction to Business Analytics

1. What is Business Analytics?

2. Why is Business Analytics Important?

Part 2. Integrating Business Analytics into the Organization

3. What Resource Considerations are Important to Support Business Analytics?

4. How Do We Align Resources to Support Business Analytics within an Organization?

Part 3. Descriptive Analytics

5. What is Descriptive Analytics?

6. How Do We Use Descriptive Analytics?

Part 4. Predictive Analytics

7. What is Predictive Analytics?

8. How Do We Use Predictive Analytics?

Part 5. Prescriptive Analytics

9. What is Prescriptive Analytics?

10. How Do We Use Prescriptive Analytics?

Appendices

References

The first text to bring together all the knowledge you need to start implementing business analytics: core concepts, methods, tools, and more.

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