One of the best predictors of a company's success is budget. But what if you can beat the odds? Using science and statistics can make you more productive and your employees happier.
In sports, one of the best predictors of success is budget. If one cursorily examines the budget of the 2014/2015 Eredivisie, it closely mirrors the current rankings. Within each year, there is of course some room for error, but averaged over the years, a club’s budget should be one of the stronger predictors. There’s one exception, and this exception will likely not surprise you – it is when people use their heads.
As psychologists, we know that people rely on all kinds of hidden biases, and such biases may cloud our judgments. When we become aware of these biases, we can vastly improve our decision making. This is not to say that intuition is worthless; on the contrary, intuition can be very worthwhile in making decisions, because it is often a much quicker way in providing solutions to problems in our daily work. But in this blog I will argue that intuition needs to be complemented by statistical insights to make businesses more effective – and employees happier and more engaged as a result.
Statistical insights in sports
Improving decision models can be accomplished through the use of statistical models. The most famous example of introducing statistical analyses into sports is the much discussed book and movie Moneyball. Moneyball reports on a baseball team from Oakland (the A’s) who had a limited budget (a “meager” $41 million) and were able to compete with teams that had much greater budgets. What the team did is draw upon vital statistics to predict which players would perform well. And, they ended outperforming the classical prediction that budget is the most important for the final ranking. This thus consisted of two steps. First, it consisted of collecting data, and, second, it consisted of identifying crucial predictors that would lead to better performance.
When they were able to identify these predictors, they were then able to hire better players that supported their goal: Winning games. The movie nicely illustrates how the coach, Billy Beane, was able to identify the predictors for the team’s success and statistics helped to identify weak spots in his organization. So can it be for your company. But statistical models are not the entire answer, as you will immediately recognize. Expertise – which typically revolves around the intuition and habits of daily life - is required to help formulating the correct models, and so can it help increase your company’s efficiency, and making your employees happier while you are at it.
Muddleheads vs. Simpleminds
Let’s draw another analogy, but now to explain why expertise is so important. It is quite intuitive to reject such formal, statistical models, because it is hard to see how a generalized model applies to a specific company. I buy this. But there is a way to get from expertise and your daily habits in your company, to crafting a better decision model. When you think about crafting a better decision model, you should not have too high expectations of what statistics can do for you. Because statistics are simply a tool that helps you understand the world.
Case in point is an old article by psychology’s hero Paul Meehl. In the 1950s, Meehl wrote about clinically oriented therapists (muddleheads) and statistically oriented therapists (simpleminded). The muddleheads observed dynamics, they interpreted their clients’ behaviors, and they became experts at inferring the personality of their clients from these observations. They likely had good intuitions and habits in terms of making relatively quick decisions (specifically, they inferred personality from interactions with clients).
At first, they were very successful at observing their clients. Their simpleminded colleagues instead advocated a more statistically oriented approach. Specifically, they advocated analyzing data, and formulated a formal protocol on the basis of which they could make decisions. As you can guess, deriving such a formal protocol required relying on expertise first, and analyzing data second. So, without expertise, the simpleminded failed miserably. But when the simpleminded colleagues relied on expertise, and analyzed the data to create what Meehl called a “good cookbook” did they consistently outperform their muddleheaded colleagues. The improvement of performance on the basis of the cookbook was about 19%. For clinicians and sports coaches alike, performance increased when relying on stats and expertise.
Creating a good cookbook for organizations
One of the biggest concerns in organizations right now is burnout and engagement, because being more engaged can lead people to be less burnt out, to be happier, and to be more productive – all facets that can lead people to lead a more meaningful life. But making your employees more engaged is easier said than done. As said, we often rely on biases or suboptimal decision models to do the things we do in daily life.
In order to attain our goals, it is first important to observe how we work in our respective work environments. But not only that, it is also important to get under the skin of the experts within the company, to know what the mission of the company is – or what their goals are. After having learnt this, one needs to collect the data, and conduct statistical analyses. What are the weak spots in the organization, and what are the most efficient ways to make employees happier and more engaged? In order to do so as accurately as possible, one does very careful archiving and one tries to reduce one’s own biases in order to craft that cookbook. But that is not sufficient. Once you know how the process works, it is important to remind people to maintain these improved habits.
Your cookbook can – and should be – created by carefully assessing your existing strategies, analyzing your own behavior, and building on the expertise of foreknown experts.