Data-Driven Decision-Making for Business
by 作者: Claus Grand Bang (Author)
Publisher Finelybook 出版社: Routledge
Edition 版本: 1st
Publication Date 出版日期: 2024-08-22
Language 语言: English
Pages 页数: 308 pages
ISBN-10 书号: 1032601493
ISBN-13 书号: 9781032601496
Book Description
Research shows that companies that employ data-driven decision-making are more productive, have a higher market value, and deliver higher returns for their shareholders. In this book, the reader will discover the history, theory, and practice of data-driven decision-making, learning how organizations and individual managers alike can utilize its methods to avoid cognitive biases and improve confidence in their decisions. It argues that value does not come from data, but from acting on data.
Throughout the book, the reader will examine how to convert data to value through data-driven decision-making, as well as how to create a strong foundation for such decision-making within organizations. Covering topics such as strategy, culture, analysis, and ethics, the text uses a collection of diverse and up-to-date case studies to convey insights which can be developed into future action. Simultaneously, the text works to bridge the gap between data specialists and businesspeople. Clear learning outcomes and chapter summaries ensure that key points are highlighted, enabling lecturers to easily align the text to their curriculums.
Data-Driven Decision-Making for Business provides important reading for undergraduate and postgraduate students of business and data analytics programs, as well as wider MBA classes. Chapters can also be used on a standalone basis, turning the book into a key reference work for students graduating into practitioners. The book is supported by online resources, including PowerPoint slides for each chapter.
About the Author
Claus Grand Bang is Associate Professor at Dania Academy, Denmark. He has more than ten years of business experience developing companies based on data and another ten years in academia teaching students from all over the world. As a lecturer, he has specialized in the fields of applied data analysis, supply chain management, and project management. He created one of the first applied data analytics degrees in Europe. Now, as Head of Data and IT, at a global biotech company he applies what he has taught in academia.