Entrepreneurs as Scientists

Book 3 of 52 in the Mitch’s Notes Project

The Book of Why: The New Science of Cause and Effect by Judea Pearl. LINK.

My Mercato colleagues and I read this book as part of our monthly book club. We’ve read several books that have inspired new ways of thinking. This book was inspiring, but not in the way the other books in the project have. Unlike the previous books, The Book of Why has little startup application (unless promoting Bayesian statistics while downplaying Frequentist statistics is crucial for success). However, I was struck by an analogy and a framework that are worth sharing in the context of supporting high-growth CEOs.

A Brief Book Review

The book was partially written with the following purpose:

“to share with you some of the heroic journeys, both successful and failed, that scientists have embarked on when confronted by critical cause-effect questions.”

A Story of a Scientist

The story from the book that I found most compelling was that of Sewall Wright. Wright studied genetics at Harvard where he began researching the hereditary factors that affected fur color in rabbits in the early 20th century. Wright later focused on guinea pigs. Yes, guinea pigs. In fact his guinea pigs were the “springboard to his whole career.” His study of guinea pigs led to the development of a mathematical method for answering causal questions from data — path diagrams.

Wright packaged his findings and presented a detailed thesis on the topic. At the time (and still to this day) there is a strong debate around the merits of Bayesian statistics and causation theory. One academic in particular, Henry Niles, excoriated Wright. The author noted that “Academia is full of genteel savagery…[but] I have seldom seen a criticism as savage as Niles’s.” The author’s interpretation of Wright’s actions is particularly compelling:

My admiration for Wright’s precision is second only to my admiration for his courage and determination. Imagine the situation in 1921. A self-taught mathematician faces the hegemony of the statistical establishment alone. They tell him, “Your method is based on a complete misapprehension of the nature of causality in the scientific sense.” And he retorts, “Not so! My method generates something that is important and goes beyond anything that you can generate.” They say, “Our gurus looked into these problems already, two decades ago, and concluded that what you have done is nonsense. You have only combined correlations with correlations and gotten correlations. When you grow up, you will understand.” And he continues, “I am not dismissing your gurus, but a spade is a spade. My path coefficients are not correlations. They are something totally different: causal effects.”

Imagine that you are in kindergarten, and your friends mock you for believing that 3 + 4 = 7, when everybody knows that 3 + 4 = 8. Then imagine going to your teacher for help and hearing her say, too, that 3 + 4 = 8. Would you not go home and ask yourself if perhaps there was something wrong with the way you were thinking? Even the strongest man would start to waver in his convictions. I have been in that kindergarten, and I know.

But Wright did not blink. And this was not just a matter of arithmetic, where there can be some sort of independent verification. Only philosophers had dared to express an opinion on the nature of causation. Where did Wright get this inner conviction that he was on the right track and the rest of the kindergarten class was just plain wrong? Maybe his Midwestern upbringing and the tiny college he went to encouraged his self-reliance and taught him that the surest kind of knowledge is what you construct yourself.

One of the earliest science books I read in school told of how the Inquisition forced Galileo to recant his teaching that Earth revolves around the sun and how he whispered under his breath, “And yet it moves” (E pur si muove). I don’t think that there is a child in the world who has read this legend and not been inspired by Galileo’s courage in defending his convictions. Yet as much as we admire him for his stand, I can’t help but think that he at least had his astronomical observations to fall back on. Wright had only untested conclusions — say, that developmental factors account for 58 percent, not 3 percent, of variation. With nothing to lean on except his internal conviction that path coefficients tell you what correlations do not, he still declared, “And yet it moves!”

Entrepreneurs as Scientists

I loved these snippets on Wright and Galileo. As I read this I couldn’t help but notice the similarities between entrepreneurs and scientists. The “us against the world” contrarian mentality is one of the best parts of the venture industry and the one that creates such significant opportunity for founders. Wright and Galileo were convinced they were right. They staked their careers on their beliefs. They each had their critics and opportunities to turn back, but that didn’t change the way they saw the world. Time has shown that Galileo was right. Less so for Wright, but that doesn’t make his story less noble. There are similar successes and failures in venture capital. Entrepreneurs, like scientists, shouldn’t bet their careers, reputation, and their time on unworthy hypotheses. Scientists have a framework to help them avoid those types of mistakes. This review is about how the scientific method can also serve as a proven framework for entrepreneurs.

The Scientific Method

The Scientific Method is the tried and true framework for scientists. There’s some debate on the exact number of steps, but I submit this seven step process for your review:

1. Question
2. Research
3. Hypothesis
4. Experiment
5. Analyze the Data
6. Form a Conclusion
7. Communicate the Results

The Startup Scientific Method

The seven steps above are really two processes working together: the founding phase and the operations phase.

The Founding Phase

This is where you come up with the idea to be tested. Whether the question, research, or the entire observation comes first, the end result is thoughtful, researched observation that can be tested. The startup observation is a business plan. You question whether something could be done better or differently, you research that question, and you pose a solution to an observed problem. Once you have this plan you are ready to start the second research phase: operations phase.

The Operations Phase

Hypothesis

The first step is to create a hypothesis. In order to have a hypothesis it must be testable. Therefore, your business hypothesis must come with a Minimum Viable Product and your Go-To-Market strategy. These are the what and how of your business model. Once you have both of those clearly outlined you can begin to experiment.

Experimentation

Experimentation is crucial if you are going to push the limits of growth. Experimentation is by nature a risk-taking exercise, but just like science, experiments must be controlled. How to experiment is less science and more entrepreneurial creativity. So how do you test, control, and get the data you need without unnecessarily risking cash, time, or customer exposure?

The rest of the scientific method revolves around measuring, analyzing, refining, and communicating the results. We will take them in turn.

When performance is measured, performance improves. When performance is measured and reported, the rate of improvement accelerates.

Analyze the Data

How do you measure your experimentation? Annual revenue, sure. Growth, yeah. But what about quarterly, monthly, weekly, daily? What are you doing today that will improve those outcomes. One quality that many of the best CEOs inside and outside of Mercato’s portfolio share, is their ability to run data-driven organizations, with the most telling and important data visible to the entire organization. There are key performance indicators (KPIs) in each business domain that if measured, analyzed, refined, and reported, will accelerate performance. So here are two frameworks for holding your organizations accountable.

1. V2MOM
2. OKRs

Pick one, it doesn’t matter which. Modify it if you feel the need, but do pick one. The key benefit is that a framework will help you find the key performance indicators and measure them. The process will focus your attention on refining and improving the most important KPIs. It will hold you, your direct reports, and the entire organization accountable to each other as you communicate the results.

Refine / Iterate

You won’t get it right the first time. But keep going. If you get to this stage and think, “the observation we made in the founding phase was wrong.” This isn’t the end. If your original observation still holds, you need a new MVP and/or a new GTM. Slack was a gaming developer before it was Slack the real time collaboration tool. Starbucks originally only sold coffee beans. If you get to this stage and think you are on to something, then iterate. Not all iterations are pivots, some are truly just tweaks to be further tested. Netflix traded below $10/share before they produced House of Cards, Instagram was a check-in app with photo capabilities before it focused on photos, and Pinterest was a retail shopping notification platform before it was a collections catalog. Your product and go to market will need to be refined, new hypotheses posited, experiments run, and data analyzed.

Communicate

Communication brings accountability to the scientific method. If the scientific results were never communicated there would be no progress, no scientific breakthroughs, replicability, or advancement. You MUST effectively communicate the results. Let’s first identify the audiences.

External: current and potential customers, competitors, potential employees, partners, potential acquirers, investors.

Internal: co-founders, executives, employees, board members, advisory board members, customer advisory council.

As in all communication, the how you communicate with these groups often matters more than the specific results the communications convey. If you’ve followed the other steps there should be a clear plan. A plan to change the hypothesis through experimentation, data analysis, and additional refinement. The various audiences inside and outside of the organization will know what to expect from you. They will know your leadership style and vision for the organization. They will get behind your vision and hold themselves accountable for their roles in supporting that vision. Or they will self select out. Both are positive. In every case, internal and external communication will lead to accountability and accelerate performance.

Current and potential customers will have a clear idea of your observation and hypothesis. You will be able to point to a clear positioning, messaging, and branding strategy. (See links to previous book summaries.) Customers are the most important resource in the experimentation, data analysis, and refinement stages. Consistent communication here is crucial.

Competitors will know you have a plan and that plan is to dominate your observed and hypothesized market. Your iterative pace, data-driven experimentation, observation, and hypothesis will force them to react or exit.

Potential employees will hear, see, and feel your communicated leadership. Stories about the communicative culture will help them believe your observation and hypothesis and induce them to join the cause.

Investors, whether board members or not, oftentimes care more that there is a plan in place than they will care about any one operations blip. Your job as the CEO is to competently communicate the results and present a plan for improving performance. Early, accurate, communication will help them know you are in control and that you have a plan. It will also provide an opportunity for them to collaborate and provide support in the refining process.

As the business scales, don’t forget to communicate with your co-founders. They believed in the observation and hypothesis before anyone else did. Even as their roles have changed, communication here will contribute to culture and cohesion in the rest of the organization.

Communication with executives is about accountability. The V2MOM and OKR frameworks are so effective because they hold executives accountable to each other for their performance. If changes need to be made, it shouldn’t be a surprise to anyone as to why. In fact, they will opt out. If you are communicating effectively from the outset, however, that need will rarely arise.

Boards and board member under-utilization is endemic in the venture community because of communication problems. Too often boards are thought of as reporting entities and not strategic and valued entities. If candid, comprehensive results were provided in combination with a scientific plan to improve performance and specific areas where board members could help, CEOs would unlock their power. And accelerate performance.

Customer advisory councils are effective for the same reasons indicated above about customers, but also because of the what that membership itself communicates. If you never listened at all (which I wouldn’t advise) they would still be effective because of the “illusion of inclusion.” Important customers want to feel important. They want to be heard. Communicate that they are.

It takes conviction, confidence, and exceptional hard work to create and discover scientific breakthroughs that will grow a businesses. No matter what crusade you are on, the scientific method will help you improve the conditions of success until you find it.