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.

Offers terminology, maturity model, and examples for predictive intelligence in business Applies knowledge from theory and practice using a problem-solving and application-oriented approach Presents case studies to show proof of concept

Autorentext

Uwe Seebacher is a method and structural scientist. He holds a doctorate in economics and business administration and is Professor for Predictive Intelligence at the University of Applied Sciences Munich (Germany) and Professor for Marketing and Communications at the University of Applied Sciences for Marketing and Communication at Vienna (Austria). He has over 30 years of experience as a business angel and investor, consultant, leader but also an entrepreneur in the media, manufacturing, and service industries. He is a popular keynote speaker and panelist. He has authored more than 50 books (in English and German) with many leading publishing houses, such as 'Assets-as-Service' (Springer Gabler, 2021), 'Data-driven Management' (Springer Gabler, 2021), 'Predictive Intelligence for Managers' (Springer, 2021), 'B2B Marketing Guidebook' (Springer, 2021), 'Marketing Resource Management' (AQPS, 2021), 'Leadership Development' (Linde, 2006) or 'Template-based Management' (Springer, 2020) and 'European Human Resource Management' (HBM, 2009). For his innovative concepts and initiatives, e.g., with Allianz, the European Union, the Austrian Federal Economic Chamber, Bayer Leverkusen, and BASF, he received various awards, such as the Diskobolos Innovation Award of the European Chamber of Commerce and the 2016 Export Award of the Austrian Federal Economic Chamber.

Inhalt

1. Predictive Intelligence and the Basic Economic Principles.- 2. Predictive Intelligence at a Glance.- 3. The Predictive Intelligence Ecosystem.- 4. The Predictive Intelligence Maturity Model.- 5. The Predictive Intelligence Self-Assessment.- 6. The Process Model for Predictive Intelligence.- 7. The Predictive Intelligence TechStack (PITechStack).- 8. The Predictive Intelligence Team.- 9. The Predictive Intelligence Case Studies.- 10. Why It Remains Exciting.