There is a quiet revolution going on in business schools. Some call it the “transition to predictability” others call it “causal based research”. A few business schools are transitioning from explaining success to predicting success. This is happening because of the way science naturally evolves, and it has major implications for you and your career. Broadly, scientific development comes in three stages:

Descriptive phase: The early efforts of scientific development are geared towards identifying and classifying phenomena. For example, when doctors opened the human body for the first time they had to identify what a kidney was and, most importantly, what it was not, and so on. Similarly, in management research, the distinction between people with skills for selling vs. skills for operating machines had to be clearly defined, same as the differences between a finance and a marketing department, and so on. Today we take these things for granted but this was the lifetime work of many researchers until around the 1960s.

Contingent phase: Suddenly, researchers observe that how things work depends (aka. is contingent) on an external factor. For instance, how well a kidney develops is dependent on your genes. How effective a marketing department is or the way to make money in a particular industry is contingent on the regulation, and so on. At this stage researchers start developing statements of correlation, they see for example that those companies that have good relationships with regulators are positively correlated with having higher profits, or that those companies that have a particular expertise in areas such as marketing, operations, etc. are also positively correlated with a variety of things such as market share, profits, retention of the best employees, etc. We are at the end of this era; most of the frameworks and models taught at business schools today are based on statements of correlation and contingency. But professors and students are realizing that these models are struggling more and more to explain the dynamics of today’s world.

Causality phase: Same as electronic microscopes showed a reality that was just not possible to see with optical microscopes, or how computing power helped us visualize for the first time the human genome, in business administration new causal based tools are showing us a reality that it is just impossible to see in the correlation and contingency stage. With these methodologies we can go back to previously unsolved problems and find an optimal solution just because we now have the tools. For instance, consider ‘customer uncertainty’: more than 50 percent of new firms fail because they couldn’t find a customer. Using these tools, we now have jobs-to-be-done, a method to find out what improvements in your product the customer will buy but that they can’t yet verbalize. That helps us visualize the causal mechanism that makes customers buy. Have you ever wondered why two identical companies that have exactly the same web page don’t sell the same? Why one succeeds while the other stagnates? The answer is in causality, and in particular in jobs-to-be-done.

Can you imagine knowing if a new business opportunity will be successful or not before launching it? Or a methodology for launching new firms with an acceptable failure rate? What if the risk of launching your own business is, for the first time, similar to the risk of losing your current job? How would that influence your life?

What about your current job? At the moment CEOs are struggling with the challenge of digitalization or disruptive change. With predictive management tools they no longer need to rely on opinion or luck to know what to do next.

Business schools are just at the beginning of teaching how to replicate success. This is a significant departure from today’s curricula, focused on explaining success. Predictive based tools are going to make a world of difference in your career, your options and in the influence of business schools. This is a natural process that happens in every scientific field, same as in the medical field. If you need to have a surgical procedure, the doctor can tell you the odds of success. The same is about to happen in management. You can use prediction to become a better manager and to have a successful career. The question is: will you?



  • This post gives the views of the author, and not the position of LSE Business Review or the London School of Economics. 
  • Featured image credit: Business School, University of Washington, Seattle Wonderlane CC-BY-2.0

Juan Pablo Vazquez Sampere is a professor of business administration at IE Business School.