In a previous post, I discussed using decisiveness to reduce or eliminate decision debt; but how do you do that? I mean, if you haven’t made the decision yet, doesn’t that—by definition—indicate that you aren’t yet ready to make the decision?
From my perspective, there is only one useful way to categorize decisions: by their cost to revert. It’s less a taxonomy than a scale, but the basic organizational schema for decisions should be in ascending order from most costly to change to least costly. From there, logic dictates that you should only exhaust as much exploratory effort to make a decision as its cost to alter.
For a decision that is trivial to wind back, I expend almost no energy in trying to find the best route. Whenever a new decision is brought to me, I want to first drill through all of the data to find the answer to one important question: What happens if we are wrong? In most cases, you will find that precious little happens if you are wrong, you just pick a better direction.
“How should we solve this technical problem? We think that option A solves the problem and it only takes a half day to implement, but it requires a half day of validation to see if it will solve for all aspects of the issue. Option B, however, will assuredly work, but could take multiple days to solve the problem.”
Right there, after just that much data, I can make my decision. Obviously, do option A. If it works, we’re out a half day and we have a solution. If it doesn’t work, we’re out a half day that we would be out after investigating anyway and we can just do option B. As an added benefit, by performing an implementation, we’ve naturally learned more about our problem domain just by working with it.
The solution is obvious, when you think about it in terms of what happens if we make a bad choice. Cheap, bad choices can be made with impunity. The more costly a decision change becomes, the more energy I am willing to spend to plan on it.
Another common example would be determining which off-the-shelf product to use to solve a problem. The expense of the product can be very high often times; but a trial period (or even a liberal return policy) can suddenly mitigate that.
So when evaluating decisions, ask yourself what happens if you are wrong—not “what is the worst that could happen” but “what is the real result of an incorrect choice here” and spend only the effort that the cost to course correct demands. If you are like most people, you will find that many of your decisions have been getting a degree of attention that they do not deserve.