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.
Decisions Over Decimals - Striking the Balance between Intuition and Information
Description
Table of Contents
Foreword xi
Preface xiii
Prologue: The Certainty Myth xix
Quantitative Intuition (QI) (TM) xx
Why Quantitative Intuition (TM) 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 (TM): A Tool for Reasoning 17
The IWIK (TM) 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 (TM) 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 (TM) Culture 167
Recruiting for the Quantitative Intuition (TM) Skill Set 169
Building a Quantitative Intuition (TM) Team 175
Cultivating a Quantitative Intuition (TM) 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
Author Description
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 (TM) 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.