Predictive Intelligence for Data-Driven Managers: Process Model, Assessment-Tool, IT-Blueprint, Competence Model and Case Studies

· Springer Nature
Libro electrónico
268
Páginas

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This book describes how companies can easily and pragmatically set up and realize the path to a data-driven enterprise, especially in the marketing practice, without external support and additional investments. Using a predictive intelligence (PI) ecosystem, the book first introduces and explains the most important concepts and terminology. The PI maturity model then describes the phases in which you can build a PI ecosystem in your company. The book also demonstrates a PI self-test which helps managers identify the initial steps. In addition, a blueprint for a PI tech stack is defined for the first time, showing how IT can best support the topic. Finally, the PI competency model summarizes all elements into an action model for the company. The entire book is underpinned with practical examples, and case studies show how predictive intelligence, in the spirit of data-driven management, can be used profitably in the short, medium, and long terms.

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Uwe Seebacher, Ph.D. in economics and business administration, is an executive advisor and has more than 25 years of top management experience as a consultant, entrepreneur, investor and manager. Uwe Seebacher is internationally known for his innovative Template-based Management (TMB) approach, first published in 2003. TBM can be used for any entrepreneurial project - with the TMB approach Uwe Seebacher was also able to open up the predictive intelligence topic of this book. He is also a lecturer at many recognized business schools and universities (such as FHWien der WKW in Austria), and has authored articles and books for many leading management publishing houses, for example, Template-based Management (Springer), B2B Marketing (Springer), Strategic Workforce Management (Harvard Business Manager), Handbook of Management Development (USP International), and Management Development (Linde Campus).

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