Preface

What distinguishes a person who makes smart, confident data-driven decisions? It is not exceptional analytic skills. Instead, successful decision-makers balance data, experience, and intuition. They quickly sort through information, apply judgment, and are fierce interrogators of data to cultivate sharp insights. They know there is more to decision-making than just the data. They resist being intoxicated by information. Instead, they apply first-order principles to understand what the decision really is, why it must be taken, and to what end. They then seek the relevant data to help make that decision. In short, they make informed decisions with incomplete information.

This approach to fast decision-making taps into a different set of skills, requiring a change in mindset by combining information and intuition. We call this approach Quantitative Intuition (QI)TM. QI is the product of years of discovery about making effective and efficient decisions. For too long, the debate has been on the value, veracity, and variety of Big Data. This trend has shifted the problem from data exploration to data sifting. This book dives into this emerging method to reimagine making decisions with imperfect information. By sharing a set of rapid response tools to get to the core of any business challenge, QI enables the reader to quickly interrogate and integrate data to make quick, effective, and often bold decisions. QI emphasizes the need to break the allure that an abundance of data is a crystal ball to eliminate all uncertainty and lead to perfect decisions.

With so much information available, leaders often falsely expect the data to provide both the question and the answer. They focus on what nuggets of insights can be found in the data? rather than what is the essential question to solve? They think they're moving forward, but they're often just churning, working hard, but achieving little.

The authors of this book have worked in highly competitive, fast-paced industries where the temptation to simply drowning in data is immense. We have seen this from working for startups to the most iconic technology brands, from teaching at notable institutions to working with colleagues worldwide.

Decisions Over Decimals uniquely bridges theory and practice. Oded Netzer is the Vice Dean of Research and the Arthur J. Samberg Professor of Business at Columbia Business School and an affiliate of the Columbia University Data Science Institute; he also works at Amazon as an Amazon Scholar. Christopher Frank is at American Express and formerly at Microsoft, and Paul Magnone is at Google and previously at IBM and Deloitte Consulting. Chris and Paul are Adjunct Professors at Columbia Business School, and along with Oded, teach Quantitative IntuitionT at Columbia. Oded says:

If you were to describe me in one word, it would be nerd. If you want to use two words, it would be data nerd. I am the type of person who likes to stare at data and look for patterns and business applications. Sometimes I miss insights in the data, and sometimes I see patterns that are not there, and occasionally, I find some really interesting and useful nuggets. More seriously, what I do for a living is to preach what I practice when it comes to data-driven decision-making. I preach through teaching data-driven decision-making to undergraduate students, MBA students, data science graduate students, doctoral students, and executives in executive education programs. I practice in terms of my research and consulting work. My research focuses on one of the major business challenges of the data-rich environment: developing quantitative methods that leverage data to gain a deeper understanding of customer behavior and guide firms' decisions. Similarly, my consulting work with Fortune 500 companies and entrepreneurial startups, as well as my work at Amazon as an Amazon Scholar, focuses on making better decisions with data.

After graduating with an engineering degree, I started my love-hate relationship with data-driven decision-making. I began in consulting: talk about a place where quantitative meets intuition. Over a few years, I realized the tools consultants used to solve complex questions were too simplistic for the problems. That is what led me to the other side of research in academia. I did my M.S. in statistics and Ph.D. in Marketing Analytics at Stanford University. It would take me a good 15 minutes to explain what I was doing at a cocktail hour (needless to say the "data nerd" wasn't the life of the party!). Today, it is easier to describe my area of focus since data science has become a household term. I then traded the sun of California for the city life of New York. For the past 18 years, I have been at Columbia University teaching executives and executives-to-be. One of the key learnings for me from years of teaching data-driven decision-making was that people are often afraid of using data to make decisions because they erroneously believe that data-driven decisions are reserved for those who were top of their class in math in school. As we discuss in this book, this is a myth. There are many skills needed to make data-driven decision but strong math skills is not one of them. I share in this book many of the learnings from the years of teaching, research, and work with companies about how to pour good amount of intuition and business acumen to convert numbers to effective business decision making.

Christopher is the Vice President of Amex Insights at American Express, leading the Global Advertising, Brand, and Communications research practice.

My background is in technology, startups, and consulting. I graduated from Stevens Institute of Technology with a Master of Science. I thrive in quantitative analysis, but quickly learned that was not enough. When I began my career, as an IT developer simply executing what the business needed. From there, I went into consulting. I applied the scientific method to tackle business problems using systematic observation, measurement, and the formulation, testing, and modification of hypotheses.

From consulting, I spent 10 years at Microsoft as Senior Director in the Corporate Marketing Research and Insights Group. When I started on the research team, we were eight people, and when I left, we were 103, reinforcing the increasing role of analytics in making decisions. While I am comfortable with numbers and quickly learned that the most valuable role I play is translating the numbers to business outcomes. I serve as the connector between analytics and strategy to create demand for the products and desire for the brand. My day-to-day focus is linking attitudes, behaviors, and outcomes with customers' needs, wants, and desires to fuel growth. I have developed a series of approaches to elevate the customer point of view, so it is influential at the highest levels to enable more thoughtful decisions. In the following pages, I share how to apply these practical techniques to everyday decision-making to help teams operate at a higher level, leading to greater impact.

This everyday application is where Paul Magnone contributes a unique voice.

While Oded and Chris approach decision-making from an analytic perspective, I come at it from building teams, structuring deals, and establishing strategic partnerships. Chris and I went to the same university, so we have a common foundation in the scientific method and approach to problem-solving. Currently, I work at Google, but if we go back in time, like Oded, I'm a recovering engineer. Yes, an engineering-only mindset is curable.

I spent my first 20 years after engineering school at IBM. About 10 years into it, after working with complex customers, I moved to the frontlines of the dot-com era working with venture capital firms and their portfolio companies in Silicon Valley, Europe, and Israel. After some time with the VCs, we realized we had all the resources to be creative, and I found myself in an entrepreneur-in-residence (or intrapreneur) role starting emerging IBM business units, developing a few patents, conducting business in over 30 countries, and driving acquisition integration of smaller software firms. So, a funny thing happens when you ask how do I reach a great decision and not just a good one; did I miss the turn? The difference between a good success and a billion-dollar business may be just a small handful of choices. How do you see the right alternative and make that choice? This is where coffee played a significant role because Chris and I would have virtual coffee on the weekends, and I'd say, "Chris, you do market research for a living. What am I missing? How am I not finding that needle in the haystack?" That was the genesis for the material in this book. It was the origin of marrying research with the frontline application.

From IBM entrepreneur-in-residence, I moved to a small telecom software firm at the forefront of 5G networking, then to a Deloitte Consulting Innovation group. Now I am at Google in the cloud business. I appreciate the academic view and helped form a lot of the strategic models in this book, but I also have experience working in the trenches, trying to understand what practical techniques will help sort out the blend of intuition and the quantitative-the head and the heart.

Bringing the head and the heart together is where leaders and teams struggle-striking the right balance so you can quickly move forward with confidence. This is the focus of...