Decisions Over Decimals is one of the best business books I’ve read over my consulting career. It is packed with useful tools and frameworks that you can apply to identify the right questions to ask, the right data to gather, and how to tailor your approach to the nature of the decision. I wish I had read this earlier in my career, as it would have greatly shortened the amount of time and effort it’s taken to learn similar practices over the years! By reading this book, you’ll pick up many tricks of the trade that consultants and other professionals apply to help clients make decisions and galvanize sustained action.

At the core of the book is an approach called Quantitative Intuition (QI), which is about combining experience with data with intuition to enhance decision making effectiveness. QI is the ability to make decisions with incomplete information via better questioning, contextual analysis, and synthesis to see the situation as a whole. QI is based on years of teaching by the book's 3 authors, all of whom are professors at Columbia Business School (where I got my own MBA years before they started teaching this course).

The authors bring complementary perspectives to their work together. Oded Netzer has studied best practices in decision-making for nearly two decades and is the Vice Dean of Research and the Arthur J Samberg Professor of Business at Columbia Business School.  Christopher Frank is VP of Insights at American Express, and an adjunct professor. He has developed a set of approaches to elevate the customer point of view as part of executive-level decisions. Paul Magnone approaches decision-making from the perspective of building teams, structuring deals, and establishing strategic partnerships, given his role as Head of Global Strategic Alliances at Google. He's also an adjunct professor at Columbia. They have been teaching QI four times per year as an executive education program, as well as conducting hundreds of client workshops.

The authors debunk two myths in the book. The first is that you don’t need to be a math whiz to make better decisions. The second is that there is no “perfect” decision, and that gathering more data is not always the right thing to do. The challenge is not a lack of information, but the training and wisdom to use it effectively.

QI is more than a set of frameworks. It is an “interrogative mindset and the ability to put the data in context and ask the right questions” (hence the quote I selected above). Intuition is not to be avoided but embraced and combined with data-driven analysis to lead to better decisions. This is similar to a concept I really like in another book I reviewed, The Art of Ideas, by Amy Murphy and William Duggan, which shows how breakthrough innovation is the ability to combine existing things in new ways. Business intuition can be limiting if it leads to “in the box thinking” and closed thinking that limits your ability to interrogate the data and explore different perspectives. Like in Art of Ideas, the authors of Decisions over Decimals focus on ways to bring range of perspectives together to enable more effective decision-making.

The authors also recognize the business judgement is often a subconscious process. It taps into holistic thinking rather than being purely linear and analytical, and “involves your gut as well as your brain.” Intuition allows you to respond to clues, which are often subconscious. With training you can pay better attention to clues and respond to them faster with the right training. This aligns well to Think Fast and Slow by Daniel Kahneman,  The Power of Habit by Charles Duhigg, and Clued In by Lou Carbone, three of the books in my initial top ten list that I reviewed, which you can find here.

QI is the ability to make decisions with incomplete information via better questioning, contextual analysis, and synthesis to approach your decision systematically and holistically. QI helps you to combine intuition with data to overcome the risk of looking at data through a biased lens or ignoring data and relying solely on intuition. Key biases include: overconfidence bias (experts value their own opinion too highly); optimism bias (overestimating your chances of success); availability bias (using what’s easily available to reduce effort to gather new data); anchoring bias (overvaluing the first piece of information); confirmation bias (seeking out data to confirm our existing beliefs);  conservatism bias (favoring older information and discounting new data points); and information bias (seeking out new information even if it’s not relevant or needed to make a decision).

The book is structured in three parts. The first part is about Precision Questioning, which includes assessing the situation, framing it appropriately, and identifying the core question you should address. Part two of the book is Contextual Analysis: nurturing your intuition and exercising your ability to move confidently from data to analysis to making decisions. The third section is focused on Synthesis, which involves transforming analysis into insights, insights to actions, and actions to outcomes.

My father was very passionate about education and helped create a “school of the future” while he was a partner at Arthur Anderson. I will always cherish my conversations with my dad about some of the ideas that went into this passion of his. One of the key take-aways for me is that people have an inherent love of learning, but that it is undermined by our experiences at school, at work, and in other facets of life. This is one of the reasons I was so interested in the four-drive theory that I applied in an article I collaborated on with two others called The Social Life of Brands (found here), which focuses on how digital media has impacted the practice of marketing. The four-drive theory focuses on how the human brain constantly balances four equally powerful drives to acquire, defend, bond, and learn. The authors of Decisions over Decimals recognize this and lament the way that our “questioning mindset is inherent but crushed out of us.” At work, we are often encouraged through both formal and informal means to favor answers over questions. Solutions are expected and asking “too many questions” is all too often discouraged. How often have you heard that good leaders need to encourage a “safe space” to ask questions and to encourage challenging the status quo. This is seen as taking courage and being a change agent, rather than the norm at most organizations. Sadly, as the authors point out, we discourage the very behaviors we need for more effective decision-making.

The book provides a series of very pragmatic tools that you can apply to improve the way you and your teams work on CX projects and make better decisions together. Here are ten examples that are introduced throughout the book:

1. Generate “I wish I Knew” (IWK) statements, which can be brainstormed upfront and inform your data gathering efforts. They can be generated iteratively in 20-minute bursts, ideally in small groups as this makes the process most productive.

2. Develop a “Knowledge Matrix” which uses a simple 2x2 to sort data you could gather into what you know and don’t know today on one axis, and what you need to know and don’t need to know on the other axis. This helps you prioritize where to spend your time gathering  missing.

3. Use the “5 Whys” to helps you frame the problem better. Asking why iteratively and engaging people with diverse perspectives in digging into the issues allows you to understand the nature of the problem better and where to focus your effort to develop potential solutions.

4. Creating a “decision tree” is effective after engaging in these other activities above. By working backwards from your decision tree to the analysis and information needed, you will speed the time it takes to make a better decision together as a team. Note that if at least two branches are not viable on your decision tree then you have already made your decision!

5. Learn to approximate, continuously asking “what do I have to believe.” This is why consultants do case interviews, to test comfort with ambiguity and ability to put things in context quickly.

6. Apply the “Pyramid Principle.” Once you have completed synthesis of your data, communicate your bottom line, and show the insights that support it. This allows you to be hypothesis driven, and avoid “burying the lead.”

7. Conduct a “Gallery Walk,” also called “Walking the Wall.”  This can be quite effective in CX work where you lay out a set of insights mapped to the customer journey and get participants in the exercise to put stickies up on the wall and talk about them in their breakout group.

8. Apply the “Decision Moment” model,  which maps decisions in a 2x2 for time and risk, allowing you to choose the appropriate model for how to approach decision-making. If the decision falls into high risk and more time, then a committee-based approach makes more sense. If it is high risk and you face significant time pressure, then a crisis management approach is better. If it is either low risk with a lot of time (analysis paralysis) or low-low (irrelevant) then you should try to avoid spinning your wheels.

9. Recognize which decisions are one-way vs. two-way doors (reversible).

10. Navigate ambiguity, imputing the data (approximation) where it is costly or not necessary to spend the time and money to generate better data.

This review covers just a portion of the valuable tools and techniques available in the book. It’s well worth the read to discover the rest of them and to reflect on how you are applying these practices in your own organization to drive greater decision-making effectiveness.

I hope this book review sparks some great ideas for you!