Decisions Over Decimals: Striking the Balance between Intuition and Information

Become a confident leader and use data, experience, and intuition to drive your decisions Agile decision making is imperative as you lead in a data-driven world. Amid streams of data and countless meetings, we make hasty decisions, slow decisions, and often no decisions. Uniquely bridging theory and practice, Decisions Over Decimals breaks this pattern by uniting data intelligence with human judgment to get to action — a sharp approach the authors refer to as Quantitative Intuition (QI). QI raises the power of thinking beyond big data without neglecting it and chasing the perfect decision while appreciating that such a thing can never really exist. Successful decision-makers are fierce interrogators. They square critical thinking with open-mindedness by blending information, intuition, and experience. Balancing these elements is at the heart of Decisions Over Decimals. This book is not only designed to be read - but frequently referenced - as you face innumerable decision moments. It is the hands-on manual for confident, accurate decision-making you've been looking for; the rare resource that provides a set of pragmatic leadership tools to accelerate: Effectively framing the problem for stakeholders Synthesizing intelligence from incomplete information Delivering decisions that stick Strike the right balance between information and intuition and lead the smarter way with the real-world guidance found in Decisions Over Decimals.

Table of Contents:
Foreword xi Preface xiii Prologue: The Certainty Myth xix Quantitative Intuition (QI)™ xx Why Quantitative Intuition™ xxviii Biases from Working Intuitively xxxiii Biases from Working with Data xxxvi Chapter 1 Asking Powerful Questions 1 Road to Powerful Questioning 3 Precision Questioning 3 The Power of Precision Questions 5 Building an Inquisitive Team 6 The Smartest Person in the Room 10 Key Learnings - Chapter 1 13 Chapter 2 Framing the Problem 15 IWIK™: A Tool for Reasoning 17 The IWIK™ Process 18 Framing the Decision 30 Key Learnings - Chapter 2 31 Chapter 3 Working Backward to Move Forward 33 Defining the Problem 35 Harnessing Inside of- the- Box Thinking 42 Taking the Road Less Traveled 45 Key Learnings - Chapter 3 48 Chapter 4 Learning to Become a Fierce Data Interrogator 49 Assessing the Data and Its Reliability 51 Putting the Data in Context 64 Pressure Testing Your Analysis 66 Key Learnings - Chapter 4 71 Chapter 5 Developing Intuition for Numbers 73 The Power of Approximations 74 Learning to Approximate 76 Approximating in Practice 78 Why Guesstimation Works 80 Getting Comfortable with Approximations 82 Guesstimation in the QI Framework 86 Key Learnings - Chapter 5 86 Chapter 6 From Analysis to Synthesis 89 The Value of Synthesis 90 Make Your Bottom Line Your Top Line 93 The Lack of Synthesis 95 Encouraging Synthesis 97 “What?”, “So What?”, and “Now What?” 99 Key Learnings - Chapter 6 100 Chapter 7 the Decision Moment 101 Dimensions of the Decision Moment 102 The First Two Dimensions: Time and Risk 103 The Third Dimension: Trust 106 Measuring Time, Risk, and Trust 108 Decision Reversibility 115 Navigating Ambiguity 118 From IWIKs™ to Decisions 121 Key Learnings - Chapter 7 123 Chapter 8 Delivering the Decision 125 The Story Arc in Decision- Making 126 Tuning the Narrative 128 Inform versus Compel 139 Key Learnings - Chapter 8 141 Chapter 9 Chasing the Decision 143 Strategy 1: Create the Case for the Decision 146 Strategy 2: Frame the Outcome 150 Strategy 3: Classify the Type of Decision 153 Strategy 4: Reduce the Scope of the Decision 154 Strategy 5: Right Size the Decision 156 Strategy 6: Pressure Test the Decision—Go to the Extremes 159 Strategy 7: Seek Consent Not Consensus 163 The Perfect Decsion Is an Illusion 164 Key Learnings - Chapter 9 165 Chapter 10 Creating a Quantitative Intuition™ Culture 167 Recruiting for the Quantitative Intuition™ Skill Set 169 Building a Quantitative Intuition™ Team 175 Cultivating a Quantitative Intuition™ Organization 181 Key Learnings - Chapter 10 183 Chapter 11 The Future of Data- Driven Decision- Making 185 Automation and Human Judgement 186 Predictions and the Digital Twin 190 Probabilistic versus Deterministic Thinking 193 Found Time for More Decisions 196 Epilogue 199 Acknowledgments 203 Index 207

About the Author :
CHRISTOPHER FRANK is a Vice President in the Global Advertising and Brand Management team at American Express. He is a senior strategist at the intersection of marketing, analytics, and commerce developing superior strategies applied to global markets working with B2B and B2C products. He is the co-author of Drinking from the Fire Hose and an Adjunct Professor at Columbia Business School. PAUL MAGNONE is Head of Global Strategic Alliances at Google. He is a leader in using technology and innovation to create and develop growth strategies for businesses. He has launched new high-growth businesses working in over 30 countries and has been an Industry Mentor in the NSF I-Corps™ Program. He is the co-author of Drinking from the Fire Hose and an Adjunct Professor at Columbia Business School. ODED NETZER is the Vice Dean of Research and the Arthur J. Samberg Professor of Business at Columbia Business School. He is also an Amazon Scholar and an affiliate of the Columbia University Data Science Institute. Professor Netzer is a world-renowned expert in data-driven decision-making. His award-winning research is broadly read and highly cited. He has published dozens of papers in the world’s leading marketing and management science journals.