Advanced Business Analytics [electronic resource] : Essentials for Developing a Competitive Advantage /
Bhaduri, Saumitra N.author.
Fogarty, David.author.
The present book provides an enterprise-wide guide for anyone interested in pursuing analytic methods in order to compete effectively. It supplements more general texts on statistics and data mining by providing an introduction from leading practitioners in business analytics and real case studies of firms using advanced analytics to gain a competitive advantage in the marketplace. In the era of “big data” and competing analytics, this book provides practitioners applying business analytics with an overview of the quantitative strategies and techniques used to embed analysis results and advanced algorithms into business processes and create automated insight-driven decisions within the firm. Numerous studies have shown that firms that invest in analytics are more likely to win in the marketplace. Moreover, the Internet of Everything (IoT) for manufacturing and social-local-mobile (SOLOMO) for services have made the use of advanced business analytics even more important for firms. These case studies were all developed by real business analysts, who were assigned the task of solving a business problem using advanced analytics in a way that competitors were not. Readers learn how to develop business algorithms on a practical level, how to embed these within the company and how to take these all the way to implementation and validation.
Includes bibliographical references at the end of each chapters.
Chapter 1. Introduction and Overview (by David J Fogarty) -- Chapter 2. Severity of Dormancy Model (SDM): Reckoning the Customers before they Quiescent (by Saumitra N Bhaduri, S Raja Sethu Durai and David J Fogarty) -- Chapter 3. Double Hurdle Model: Not if, but when will Customer Attrite? (by Saumitra N Bhaduri, S Raja Sethu Durai and David J Fogarty) -- Chapter 4. Optimizing the Media Mix- Evaluating the Impact of Advertisement Expenditures of Different Media (by Saumitra N Bhaduri, S Raja Sethu Durai and David J Fogarty) -- Chapter 5. Strategic Retail Marketing through DGP Based Models (by Saumitra N Bhaduri, Anuradha V., S. Raja Sethu Durai and David J Fogarty) -- Chapter 6. Mitigating Sample Selection Bias through Customer Relationship Management (by Saumitra N Bhaduri, Anuradha V. and David J Fogart) -- Chapter 7. Enabling Incremental Gains through Customized Price Optimization (by Saumitra N Bhaduri, Anuradha V. Avanti George and David J Fogarty) -- Chapter 8. Customer Relationship Management (CRM) to Avoid Cannibalization: Analys Through Spend Intensity Model (by Saumitra N Bhaduri, Anuradha V. Avanti George and David J Fogarty) -- Chapter 9. Estimating Price Elasticity with Sparse Data: A Bayesian Approach (by David J Fogarty and Saumitra N Bhaduri) -- Chapter 10. New Methods in Ant Colony Optimization using Multiple Foraging Approach to Increase Stability (by David J Fogarty, Avanti George and Saumitra N Bhaduri) -- Chapter 11. Customer Lifecycle Management – Past, Present and Future (by Avanti George, Saumitra Bhaduri and David J Fogarty).
The present book provides an enterprise-wide guide for anyone interested in pursuing analytic methods in order to compete effectively. It supplements more general texts on statistics and data mining by providing an introduction from leading practitioners in business analytics and real case studies of firms using advanced analytics to gain a competitive advantage in the marketplace. In the era of “big data” and competing analytics, this book provides practitioners applying business analytics with an overview of the quantitative strategies and techniques used to embed analysis results and advanced algorithms into business processes and create automated insight-driven decisions within the firm. Numerous studies have shown that firms that invest in analytics are more likely to win in the marketplace. Moreover, the Internet of Everything (IoT) for manufacturing and social-local-mobile (SOLOMO) for services have made the use of advanced business analytics even more important for firms. These case studies were all developed by real business analysts, who were assigned the task of solving a business problem using advanced analytics in a way that competitors were not. Readers learn how to develop business algorithms on a practical level, how to embed these within the company and how to take these all the way to implementation and validation.
Management information systems.
Industrial management.
Econometrics.
Operations research.
Management science.
Leadership.
Statistics .
Business Process Management.
Econometrics.
Operations Research, Management Science.
Business Strategy/Leadership.
Statistics for Business, Management, Economics, Finance, Insurance.