Business Analytics

by Saxena, Rahul; Srinivasan, Anand

• ISBN13: 9781461460794
• ISBN10: 1461460794
• Format: Hardcover
• Copyright: 2012-12-05
• Publisher: Springer Verlag

Summary

Business Analytics is the extensive and comprehensive use of data, data analysis, explanatory and predictive models and methods, and management based on facts, in support of decisions and actions. Business analytics may be viewed as comprising three phases: The first includes the difficult process of data gathering and cleaning, descriptive statistical characterization, and other preparations that must take place before applying Operations Research methods and models. The second phase consists of the OR skill set; that is, modeling and analysis of the model, to extract what can be learned from the data that is relevant to the decision process. Finally, the third phase consists of advanced analytical skills not included in a typical OR course of study: such as predictive modeling, logical inferences, cluster analysis, and tools from artificial intelligence, necessary to effect the most advantageous changes in the system being analyzed. Corporate and academic organizations seem to share an enthusiastic appreciation of what is termed Business Analytics, but they do not necessarily share a common understanding of all that it comprises; indeed, industry- and sector-specific requirements often demand specialization on the part of analysts and organizational teams of analysts working in different contexts. This process has presented organizational challenges, as new career paths have had to be established by which analysts from many traditional and respected fields can move in to fill the roles of Business Analytics practitioners and teams. The primary focus of this book is on concepts and processes for embedding business analytics into decision making. The domain of Business Analytics is becoming recognized and established as a field distinct from general management, by the creation of specialized Business Analytics practitioners and teams in many companies. These groups draw upon OR/MS, Statistics, and the IT practices for Business Intelligence, Analytics & Optimization and they craft the concepts, processes, and structures needed to establish business analytics practices in their organizations. This book offers a set of proven concepts, processes, and structures that collectively show how organizations can set up and evolve their analytics work in order to achieve the desired improvements in their operations. The book is intended as a practitioners' guide to Business Analytics. The word 'Analytics' conjures up different images for different people depending on the primary function that they work in. Effective application of Business Analytics involves a confluence of Business Analytics, Mathematical Modeling and IT capabilities. This book seeks to lay down a framework for effective interplay of these various groups, and positions Business Analytics as orthogonal to Mathematical Modeling and IT capabilities. It includes several case studies of how Business Analytics concepts, processes, and structures have been used to expose and deliver the benefits of improved decision making at various organizations where the authors have worked.