A comprehensive guide offers practical solutions to common data challenges, exploring how businesses can leverage data effectively by addressing misconceptions, improving decision-making frameworks and integrating data-driven strategies to create tangible value and profitable in an AI-driven enterprise. Original.
CLEAR AND CONCISE TECHNIQUES FOR USING ANALYTICS TO DELIVER BUSINESS IMPACT AT ANY ORGANIZATION
Organizations have more data at their fingertips than ever, and their ability to put that data to productive use should be a key source of sustainable competitive advantage. Yet, business leaders looking to tap into a steady and manageable stream of “actionable insights” often, instead, get blasted with a deluge of dashboards, chart-filled slide decks, and opaque machine learning jargon that leaves them asking, “So what?”
Analytics the Right Way is a guide for these leaders. It provides a clear and practical approach to putting analytics to productive use with a three-part framework that brings together the realities of the modern business environment with the deep truths underpinning statistics, computer science, machine learning, and artificial intelligence. The result: a pragmatic and actionable guide for delivering clarity, order, and business impact to an organization’s use of data and analytics.
The book uses a combination of real-world examples from the authors’ direct experiences—working inside organizations, as external consultants, and as educators—mixed with vivid hypotheticals and illustrations—little green aliens, petty criminals with an affinity for ice cream, skydiving without parachutes, and more—to empower the reader to put foundational analytical and statistical concepts to effective use in a business context.
Acknowledgments xiii
About the Authors xvii
CHAPTER 1 Is This Book Right for You? 1
CHAPTER 2 How We Got Here 9
CHAPTER 3 Making Decisions with Data: Causality and Uncertainty 29
CHAPTER 4 A Structured Approach to Using Data 45
CHAPTER 5 Making Decisions Through Performance Measurement 53
CHAPTER 6 Making Decisions Through Hypothesis Validation 85
CHAPTER 7 Hypothesis Validation with New Evidence 113
CHAPTER 8 Descriptive Evidence: Pitfalls and Solutions 141
CHAPTER 9 Pitfalls and Solutions for Scientific Evidence 165
CHAPTER 10 Operational Enablement Using Data 187
CHAPTER 11 Bringing It All Together 211
Index 233
TIM WILSON has been an analytics practitioner since 2001, working in roles from business intelligence at high-tech B2B companies, to analytics leadership at marketing agencies, to consulting with Fortune Global 500 companies to improve their analytics investments.
DR. JOE SUTHERLAND has worked as an executive, public servant, and educator for the Dow Jones 30, The White House, and our nations top universities. His firm, J.L. Sutherland & Associates, has attracted clients such as Box, Cisco, Canva, The Conference Board, and Fulcrum Equity Partners. He founded the Center for AI Learning at Emory University, which focuses on AI literacy and integration for the general public.
