Algorithmic Business Thinking

As we embrace the new managerial paradigms of the digital era and the knowledge economy that fuels it, we need to become more acquainted with new definitions and terms.

One such term is “algorithmic business thinking” coined at MIT and defined as “a series of interconnected insights, frameworks, and models to help us break complex problems down into their smaller constituent parts.” This then allows us to work on them in parallel, and then recombine them in ways that uncover opportunities for sustainable growth.

Algorithms are essentially “a set of steps to solve a problem” and typically take the form of a sequence of computer instructions. And through developments in machine learning, these can improve with use, as they are fed more data through time - in other words, they can continually learn by themselves without further programming.

So how does this work in practice? Well, an algorithmic business approach involves breaking complex problems into smaller ones for easier solvability, recognizing the patterns of failure and success, and knowing how to apply strategies that were effective in one domain of the organization to others.