In explanation of our 1st principle of optimum decision-making, I already approached the fact that there is a disconnect between business realities and the course of scientific investigation in the field of decision-making. Academia tends to oversimplify its theoretical model of decision-making ending up with a single (unattached) decision as a unit of its scientific interest. And while scientific abstraction is a legitimate method of academic inquiry, in the case of business decision-making, it brutally contradicts the key aspect of the business environment — continuity.
In business, there is no such animal as a standalone decision. All seemingly single decisions and steps taken along facilitating business processes are linked to each other actions. We do not consider the business as a finite process . And for decision-making, it is critical to realise that business is a continuous process. It continuously requires management to make decisions. Not one decision, but the chain of decisions. Or to rephrase — business stops if the chain of decisions ends. We basically must take for granted that in the business world decision-making is also a continuous process, similar to the production process or your customer service processes.
This continuity of the process of making business decisions stipulates as well that manager in the end is the professional business decision-maker. In other words, managers specialise in making decisions. It is their continuous day-by-day activity, their profession .
Economists will rightfully recall the very core economic principle of division of labor here. In essence, for our case, we will then have two distinct roles here: a subject matter expert (business analyst), and a decision-maker (manager).
If we would take a very mechanistic or functional approach to organisation, or, in other words, if we will deny a manager the right to be a human being (what in some cases can be well-deserved), we will say that a manager is a decision-making machine in business. A manager has information as input and decisions as output. If you are not completely scared already and still can proceed, we may unfold this logic further by saying that if we can talk about the productivity of a machine (usually measured in the amount of output produced in a period of time), then we should also talk about productivity of a manager which can be (and often should be) measured in the amount of made decisions .
If you don’t believe it, take a very pedantic manager`s schedule and simply count how many meetings he or she made a day — if you say that at least every meeting is a small (or big) decision — you have a rough estimate of the number of business decisions your manager does. If you are not yet convinced, take a fully agile manager who can work with Jira — and ask him or her to record all his decisions in Jira tickets so you can get a rough quantification.
