America’s crisis with fact is part of a wider problem for business innovation with evidence-based decision making
There are important lessons for evidence-based decision making in business from my favorite newspaper headline of the year so far is, “Scientists cast doubt on the accuracy of rodent weather predictions.”
The story was about this year’s weather pronouncement from the famous Pennsylvania-based groundhog “Punxsutawney Phil.” As we all know from the Bill Murray movie, Groundhog Day, Punxsutawney Phil is credited with an ability to predict the continuation of winter or the early onset of spring. However, the National Oceanic and Atmospheric Administration found that Phil is only 35% accurate in his predictions.
This short headline captured so much about the predicament of contemporary America. A country founded on the principles of science and engineering, with a proud history of invention and discovery, appears to be slipping into a post-fact era. The culture wars have ramped up to such a degree that facts no longer have the same status in public policy making. It that is true, then why shouldn’t the predictions of a groundhog carry the same weight as those of a science-backed forecast?
Instinct based decision making
People in business, like in society at large, tend to hold strong opinions about what a company should or should not do. Innovation is often a hot topic, particularly with a runaway new technology like AI hitting the headlines. In a large corporation, it increases the fear that they will move too slowly, and be disrupted by smaller, more nimble, competitor. The cry goes up: we need to be entrepreneurial.
We often talk about entrepreneurs as someone having an ability to identify opportunity based on “instinct.” This is an intuition that drives decision-making and, in the case of a successful entrepreneur, market success. Leaders of large companies often embrace this language when describing the reasons for a failure to innovate: “We lack people with entrepreneurial instincts.” What they mean by that is lacking people with courage to pursue opportunities based on intuition alone.
The problem with these definitions of entrepreneurship is that there is scant evidence that instinct is what drives success. We just have to look at the actual rates of startup failures to realize that having entrepreneurial instinct is not a guarantee of success. The answer lies elsewhere and has much more to do with an ability to assess evidence. This same disregard for evidence bleeds into the rest of Corporate America.
Corporates that follow the instinct-based approach to innovation end up in a hole. Jeff Immelt’s failed attempt to make GE a software (or “digital”) company failed for many reasons, but the most obvious amongst them was that he made no attempt to test any of the assumptions underlying the business model. So confident was he of his success that within a year of starting the initiative, he even invited a Harvard Business School professor to write a business case study.
Similarly, Goldman Sachs CEO David Solomon spent an estimated $4 billion seeking to create a consumer banking business. When challenged on why the business should succeed, he answered: “We are a big bank with a big balance sheet.” It’s unclear why that would matter to a customer looking for a new banking product.
These are emotional, not factual or evidence based decisions. We try to pretend emotions do not affect business decision-making, in reality the reverse is true, even in highly consequential decisions. For example, I wrote last year about the recent study that showed how Nokia made the fateful decision to adopt Windows operating system rather than Android as it tried to compete with iPhones. Executives now admit is was an emotional, not factual choice.
Evidence-based decision making
I am not an empiricist. Facts are very complicated things. We cannot rely on data and cold objectivity alone to make decisions. However, we can follow a disciplined approach of gathering evidence to test our assumptions. There is a simple trinity we can observe: Hypothesis-Experiment-Data:
1. Formulate a hypothesis about what we think customers want
2. Design and conduct experiments to test that hypothesis
3. Collect and analyze data from those experiments
This enables us to reexamine our hypotheses, adjust our assumptions, and adapt our plans accordingly. This is a process of learning. It can be laborious, but it is still much quicker than the alternative of having to write off losses of ventures like those at GE and Goldman Sachs that lacked evidence from the start.
If this disciplined approach to innovation is too much for an era of fantasy decision-making, then fortunately help is on the way. Although Punxsutawney Phil’s predictions are seriously flawed, it turns out that Staten Island Chuck, a groundhog residing in the Staten Island Zoo, has an accuracy rate of 85%.
Perhaps corporates should try employing their own trained rodents to short circuit decision making. There is a zinging final line about rats and political decision-making, but I’ll skip that in deference to editorial neutrality.