Biggest problem with failure

The biggest problem with failure is that, too often, it isn’t intentional.

When you run an experiment and you don’t get the result you want, you might call that a failure: but it’s an instructive failure.

You set up a test, you had specific measures, and you received a result–and not only that, but you have some indication (hopefully) from the conditions of the test and the individual data points about why the result was received.

With that data, you can set up *yet another experiment–*and, key point: this experiment will be different from the last.

Edison didn’t randomly try lots of different materials and methods for making a lightbulb.

He went through 1,000+ variations until he found the one that worked.

There was a huge solution set, but he tested it methodically, eliminating the ‘failures’ one by one.

Unfortunately a lot of our ‘failures’ were not the result of experiments.

Some ‘failures’ simply mean things didn’t go our way.

We lost the contract, we lost the girl (or boy), we lost the game. We look back in hindsight and think we know ‘why’ we failed, but in reality we often don’t.

The conditions were uncontrolled, the measurements are unclear, the data is sparse and uncertain.

The best we can say is that it didn’t go the way we wanted it to.

(In fact, we might look back 20 years later and say “we didn’t fail, we just didn’t know how good it would be”–but this is often just reverse justification.) Some ‘failures’ simply mean something that was broken in the past, and poorly healed/fixed – be it a tool or a toy or a character trait – has broken yet again.

Some ‘failures’ simply mean we reached for something that we knew was slightly beyond our present abilities and failed to get to it.

This is where the old adage ‘try, try again’ comes into play.

One-off failures (accidents, etc) can simply be written off to things beyond our control.

Repeated failures, however, suggest that a pattern that is controllable.

That’s when we need to stop accepting failure and start learning from it–to replace the worst way to fail (repeatedly) with the best way to fail: to plan for it, to plan the conditions, run the experiment, accept the result, and *learn from it–*and never repeat it

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