It’s important, but hard, to separate good process from good outcomes. Often it’s assumed that any good outcome, must reflect a good process and vice versa. But in risky situations this approach could lead you to make major mistakes. Assume you win the lottery. Now, you now have a very large amount of money, but that does not change the fact that lotteries are, as Adam Smith said, “a tax on idiots” and the expected return on any lottery ticket is negative – there are much better ways to spend your money. So just because people win the lottery each week does not mean playing lottery is a good idea (unless you like losing money). So playing the lottery is a bad process, but there’s a chance you hit a good outcome. In fact, it happens every week.
I’m just using the lottery as an example to show that in many cases closer to home, we might be making the same mistake. For example, your project finished ahead of schedule, but how much of that is due to good process that can be repeated? And how much is due to luck? The answer comes down to how good your process is.
Of course, there’s a more positive side to this too, just because you didn’t get the outcome you wanted didn’t mean the process was bad. Speed skating at the Winter Olympics is a good example of this, it takes many years of dedicated training to enter the Olympics, but in a speed skating race you can easily get pushed over by a competitor, and it might be totally out of your control. It doesn’t mean you shouldn’t have won gold, but it means you didn’t win goal. Good process, bad outcome.
So what to do in situations where risk means that outcome and process aren’t totally tied together?
Two things can help:
- Repetition – over time processes and outcomes will converge where risk is present. You might get lucky on one project, but across ten it’s far less likely. Look for multiple instances of a situation before forming a judgment.
- Analysis – good process can be supported by analysis. If something went wrong or poorly look at why it happened. Luck can often be identified with logical analysis – a good process should make sense and be robust.
|Bad Outcome||Good Outcome|
|Good Process||Changes could make things worse||Ideal situation|
|Bad Process||Process improvement needed||Unsustainable luck|