A Decision Matrix is a tool I sort of accidentally invented before learning it was a thing. Then I wrote all this in Column 430.
A decision matrix (aka “Pugh Matrix” aka a couple other names) is a tool to used to rank competing options in a rigorous and (supposedly) objective way. The general idea is you come up with criteria you care about, assign each of those criteria a weighting factor, score each of your options against each criteria, then finally multiply the scores received by the weighting factor and sum up the overall score to determine the “optimal” choice. If that doesn’t make sense, don’t worry. There’s an example below.
Decision Matrix Problems
My experience with decision matrices is that they aren’t objective. They are just subjective in a slightly more rigorous way. They have many potential points of failure.
Your decision matrix might suck if:
- You fail to include all criteria you care about, or include unnecessary criteria that dilute what is actually important
- You and your collaborators don’t agree on criteria, or criteria weighting
- You don’t have an objective scoring system for each criteria & rely on opinions
- An option on the table solves your problem in a way that just so happens to not line up with your criteria
Defending the Decision Matrix
So if a decision matrix is prone to failing in numerous ways, does that mean it’s useless? No. They can be helpful.
First, there are a number of mitigations you could put in place to make the scoring systems less subjective. You could use the wisdom of the crowds, or perhaps your situation lends itself to obvious criteria and objective metrics against which you can score each option without requiring judgment.
Even if none of that works, just by putting in the work to think about and talk about what’s important will probably give you the information you need in order to know what you want to win. Sometimes that’s all you need.
A Whiteboarding Decision Matrix
Options along the top, criteria along the side. Each criteria holds a weight factor, each option is ranked against each other option. The “best” option in each row gets the 10. The others are ranked relative to it. The score at the bottom of each column is the sum of the numbers in the column after they are multiplied by their corresponding weight factor. So, GoodNotes is a 10 in the “Fun on iPad” criteria, which has a weighting of “8”. So 8 x 10 = 80 points. Continue down each row and you end up with 380 points for GoodNotes. The other columns are scored in the same way.
Notes:
- All of those scores are subjective. Herein lies the myth that decision matrices are “objective”.
- GoodNotes means the app “GoodNotes 5”, which isn’t free… but is a one time expense that I’ve already paid, so continuing to use it for me is effectively free.
Source
- experience
- Column 430