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

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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 science: 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 you:

  • Develop a strong data science intuition quotient
  • Lead and scale AI and analytics throughout your organization
  • Move from “best-guess” decision making to evidence-based decisions
  • Craft strategies and tactics to create real impact
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.


ISBN-13: 9781260459142

Media Type: Hardcover

Publisher: McGraw Hill LLC

Publication Date: 12-08-2020

Pages: 352

Product Dimensions: 5.80(w) x 9.10(h) x 1.40(d)

Eric Anderson and Florian Zettelmeyer are tenured professors at Northwestern University’s Kellogg School of Management. They are known across academic and business arenas as go-to experts in data analytics.

Table of Contents

Preface v

Section 1 Introduction

Chapter 1 Al and Analytics Are a Leadership Problem 3

Chapter 2 A Framework for AI and Analytics Success 21

Section 2 Consuming Al and Analytics

Chapter 3 Exploratory Analytics: What Is Going on with My Data? 47

Chapter 4 Distinguishing Good from Bad Analytics 59

Section 3 Actively Participating in Al and Analytics

Predictive Analytics

Chapter 5 Anatomy of a Crystal Ball 89

Chapter 6 A Smarter Crystal Ball 113

Causal Analytics

Chapter 7 Designing Your Data for Analytics: Experiments and Quasi-Experiments 143

Chapter 3 Working with Data You Have Part 1: Using Opportunistic Data 171

Chapter 9 Working with Data You Have Part 2: Learning from Natural Experiments 193

Making Decisions

Chapter 10 Optimizing and Scaling Your Decisions 211

Section 4 Executing on Al and Analytics

Chapter 11 Identifying Opportunities and Planning for AlA 237

Chapter 12 Understanding Barriers to Success 257

Chapter 13 Organizing for Success 273

Section 5 Success Stories with AIA

Story 1 Allstate Builds Firmwide DSIQ 295

Story 2 Vanguard Builds an Ecosystem of Analytics Excellence 299

Story 3 Canadian Tire Creates an Enterprisewide Analytics System 303

Story 4 Royal Caribbean Sets Sail for Continuous Analytics Improvement 310

Story 5 Accenture Builds Analytics Capability for Competitive Advantage 317

Acknowledgments 327

Notes 329

Index 335