Leading with AI and Analytics: Build Your Data Science IQ to Drive Business Value

by Eric Anderson, Florian Zettelmeyer

Lead your organization to become evidence-driven

Data. It’s the benchmark that informs corporate projections, decision-making, and analysis. But, why do many organizations that see themselves as data-driven fail to thrive? In Leading with AI and Analytics , two renowned experts from the Kellogg School of Management show business leaders how to transform their organization to become evidence-driven, which leads to real, measurable changes that can help propel their companies to the top of their industries.

The availability of unprecedented technology-enabled tools has made AI (Artificial Intelligence) an essential component of business analytics. But what’s often lacking are the leadership skills to integrate these technologies to achieve maximum value. Here, the authors provide a comprehensive game plan for developing that all-important human factor to get at the heart of data the ability to apply analytical thinking to real-world problems. Each of these tools and techniques comes to powerful life through a wealth of powerful case studies and real-world success stories.

Inside, you’ll find the essential tools to help
Written for anyone in a leadership or management role―from C-level/unit team managers to rising talent―this powerful, hands-on guide meets today’s growing need for real-world tools to lead and succeed with data.

Genres: Audiobook

352 pages, Hardcover

Published December 8, 2020

About the author

Librarian Note: There is more than one author by this name in the Goodreads database.

Eric Anderson is a tenured professor at Northwestern University’s Kellogg School of Management.

Reviews

[Ryan Lewis · Rating 5 out of 5]

Excellent book on data strategy. Highlights many of the problems I have seen and provides excellent solutions.

[Alireza Hejazi · Rating 4 out of 5]

This book discusses how to apply artificial intelligence (AI) and logic to leadership. It serves as a reminder to readers that the divide between data science and business may be quite costly. AI and analytics (AIA) can be an effective approach as suggested by the authors to narrow the gap in business processes. The book is organized in such a way that each component adds to readers’ comprehension of AIA in the organizational context, assisting them in increasing their “data science intuition quotient” (DSIQ). The book discusses critical issues such as the distinction between data integrity and the concept of “truth in data”– the idea that in most business scenarios, there can be multiple, competing truths that can only be understood through multiple angles, parameters, and, most importantly, a manager who understands the inputs and outputs. The book might be useful for business managers and executives who are in charge of implementing AI in their organizations.

[Kevin · Rating 4 out of 5]

Great primer on business analytics for those who don't actually do the number crunching. Getting into the statistical methods could be a little ... gentler ... for those of us who are less inclined to spreadsheets and formulas.