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Decision-Driven Analytics

Language EnglishEnglish
Book Paperback
Book Decision-Driven Analytics Stefano Puntoni
Libristo code: 44523733
Publishers WHARTON SCHOOL PR, May 2024
Companies have more data at their fingertips than ever before. Yet, studies show that many executive... Full description
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Companies have more data at their fingertips than ever before. Yet, studies show that many executives and organizations fail to extract real value from it.
Challenging the conventional wisdom of data-driven decision-making, marketing professors and behavioral scientists Bart De Langhe and Stefano Puntoni argue that many analytics efforts flounder because data analyses are disconnected from the decisions to be made. In their important book, they offer a new approach they call decision-driven analytics. Counterintuitively, they argue that the key to making good decisions with data is to start by putting data in the background.
Drawing from their own research and teaching, as well as real-world business cases, De Langhe and Puntoni offer four pillars of decision-driven analytics and guide you around common mistakes that have held back many organizations from using data for impact.
In Decision-Driven Analytics, you will learn how to:
+ Avoid common pitfalls in data-driven decision-making;
+ Close the gap between managers and decision-making on one side, and data scientists and data analytics on the other;
+ Enhance the impact of data analytics on business outcomes;
+ Think without data to make better decisions;
+ Prepare for artificial intelligence's impact on data analytics; and
+ Evaluate the costs and benefits of decision-driven analytics.

A must-read for anyone who wants to harness the power of data for competitive advantage, Decision-Driven Analytics will equip you with the skills and tools you need to more effectively use data for business outcomes and to make better decisions in today's complex and data-rich world.

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About the book

Full name Decision-Driven Analytics
Language English
Binding Book - Paperback
Date of issue 2024
Number of pages 112
EAN 9781613631713
ISBN 1613631715
Libristo code 44523733
Publishers WHARTON SCHOOL PR
Weight 166
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