Consider a continuum of things that you can do, divided up by difficulty. You can have 3 kinds of results
1. For some part of it, you will always succeed,
2. For some part of it, it's a mix of sucess and failure, and
3. For some even more difficult part, you always fail.
Now in order to succeed at something consistently, you need to master it, which also means that the things you always succeed at are fully mastered. Any knowledge or skills to be gained in those areas are at best minuscule improvements.
Then there's the part where you succeed sometimes and fail sometimes. But each time you fail, you gain more data on how you failed, and you think about how you can fix those points. You're learning, and you're improving.
Now there are also tasks at which you'll consistently fail. Passing the BAR exam as a programmer with no preparation would be a good example. Since you have no sucesses to compare to in that area, you wouldn't learn a lot trying to retake the BAR exam, no matter how often you did it. You're lacking in knowledge and skills required, and trying to perform at that level doesn't do you any good.
Now the ratio of failures and sucesses is more of a rule of thumb, and not an ironclad model. The reason that the common adage is "If you're failing, you're doing something right", at least so I believe, is that "If you're failing some and succeeding some, you're closer to your optimum failure/success ratio for growth than if you are at either end of the extreme" simply doesn't roll off the tongue quite as nicely. You can't put that on the cover of a self-help book. And since almost everyone is inclined to default to the "sucess" side of the continuum (coloquially known as your comfort zone) instead of the "failure" side, it makes a lot more sense to tell someone to fail more often. It's not a curse, it's a call for more ambitious projects. In this specific case, it's a comforting call to the fact that they're trying hard enough to fail at something. And I think that is commendable.
Risk of failure should be weighed against the consequences of failure.
If I'm writing code for robots as a hobby and my robots behave exactly as I intended all of the time, then I'm probably not learning anything, and I should try to make the robots do more sophisticated tasks. The consequences of failure are minimal, so the optimum failure rate is high.
If I'm at work writing avionics code, the cost of failure is astronomical. It's nice to push boundaries and learn things, but it's better to avoid plane crashes. The consequences of failure are high, so the optimum failure rate is low.
1. For some part of it, you will always succeed,
2. For some part of it, it's a mix of sucess and failure, and
3. For some even more difficult part, you always fail.
Now in order to succeed at something consistently, you need to master it, which also means that the things you always succeed at are fully mastered. Any knowledge or skills to be gained in those areas are at best minuscule improvements.
Then there's the part where you succeed sometimes and fail sometimes. But each time you fail, you gain more data on how you failed, and you think about how you can fix those points. You're learning, and you're improving.
Now there are also tasks at which you'll consistently fail. Passing the BAR exam as a programmer with no preparation would be a good example. Since you have no sucesses to compare to in that area, you wouldn't learn a lot trying to retake the BAR exam, no matter how often you did it. You're lacking in knowledge and skills required, and trying to perform at that level doesn't do you any good.
Now the ratio of failures and sucesses is more of a rule of thumb, and not an ironclad model. The reason that the common adage is "If you're failing, you're doing something right", at least so I believe, is that "If you're failing some and succeeding some, you're closer to your optimum failure/success ratio for growth than if you are at either end of the extreme" simply doesn't roll off the tongue quite as nicely. You can't put that on the cover of a self-help book. And since almost everyone is inclined to default to the "sucess" side of the continuum (coloquially known as your comfort zone) instead of the "failure" side, it makes a lot more sense to tell someone to fail more often. It's not a curse, it's a call for more ambitious projects. In this specific case, it's a comforting call to the fact that they're trying hard enough to fail at something. And I think that is commendable.
Risk of failure should be weighed against the consequences of failure.
If I'm writing code for robots as a hobby and my robots behave exactly as I intended all of the time, then I'm probably not learning anything, and I should try to make the robots do more sophisticated tasks. The consequences of failure are minimal, so the optimum failure rate is high.
If I'm at work writing avionics code, the cost of failure is astronomical. It's nice to push boundaries and learn things, but it's better to avoid plane crashes. The consequences of failure are high, so the optimum failure rate is low.
