This fancy label ‘Data-driven’ does not come by itself and neither it comes for free. It must be built. And in building it there will be a key struggle for management: namely, they will have to change the way they make decisions .
Practical observations show that it is very hard to resist a natural tendency of a manager to decide on the spot and by gut feeling. To help to overcome this difficulty, I propose to follow a framework which I designed for my projects, and which demonstrated its effectiveness throughout many encounters with ‘quick’ decision makers. I call this framework “data-driven decision-making pyramid” (or just Pyramid).
On top of the pyramid is the decision. To get to this top, the analytics crunch through the width of data starting from the bottom of the pyramid. The width of available data or information is often too big for a manager to cover while being also busy with operational tasks in parallel. The need for condensed information to make a decision defines the value of data analysis and, in a broader view — analytical support of decision-making in business.
Business analysis may often be wrongly seen as “data crunching”. This is a too narrow view because the true purpose of the analysis is at first to investigate the business situation (usually called the problem) upon which the decision should be made for possible root causes so, that they can be further addressed by decision makers. This investigation should bring a clear and cohesive explanation of the problem at hand, eliminate complexity, and, most importantly, it should drop off the ‘noise’ — useless data to use and wrong trajectories to take as the next steps. Good business analysis does this through exploration and quantification of possible alternatives to a decision. Investigation, exploration and quantification of the problem should rely on data and facts as much as possible. So, there is data ‘crunching’ but with a business purpose in mind.
More business analytics in the process should mean better elaboration of possible alternative scenarios (namely pros and cons) for decision-makers . And, in Pyramid terms, it means the higher the pyramid, the more developed (also from a data perspective) your alternatives are, more clarity you have on what might happen (not on what will happen) if you decide to take this or that alternative.
The framework of the Pyramid Principle helps to ask yourself — where am I, on what level is my decision-making now? And the goal is to bring your managerial decision-making to the highest level. Where higher the level of the decision-making preparation (the higher you climb the pyramid by investigating the problem with your business analysts) — the more weighted your decisions are. However, the decision itself — is still a mystery of the decision-maker`s brain cells chemistry, and therefore the top level of the pyramid is simply called “Biased level”.
At this top, the decision-maker is making his own estimations on how reality will play out in the future and how capable he or she will be in steering the organisation further once this or that scenario will materialise. It is thus obvious and inevitable that personality traits (risk appetites, subjective situational perceptions, and a full list of known biases) would still heavily impact even the most prepared decisions.
By applying principles of effective decision making which I`m presenting here, organisations will be able to mitigate and fix these biased detours from the optimum. Biases are best discovered in retrospect. This reinforces the 1st principle of efficient decision-making — an organisation needs a feedback loop and retrospective analysis of performed decisions to be able to fight biases and to tune decision-making practices.
