This was a very useful and timely post for me. I was on the lookout for a tool to use to evaluate the quality of my predictions, and the Brier score was a concept I didn’t know before now. I will try to incorporate this in my daily routine. Thank you!
One additional variable one could also keep track of is something like a “correction” factor. If I predict a given task will take me 1 week to complete, and it ends up taking 2 weeks instead, then next time I am faced with a task of a similar nature I should remember that last time I was wrong by a factor 2. This “correction” factor should be taken into account when making the next prediction.
The caveat of this approach is that it’s too simplistic and might not fully grasp say the factors that lead to the delay from (predicted) 1 week to (reality) 2 weeks, which might be caused by external factors. Additionally, I now have better knowledge of the factors that lead me to make a wrong prediction in the first place, and I should (maybe) be better at making predictions.
But I think that the best strategy is keeping the “correction” factor simple and not starting to account for all of these factors. I would rather update the “correction” factor in the next iteration.
If you want to get more specific with single outcomes you could also consider making predictions with a normal distribution to get more information, but as far as I know there isn’t a tracker for it and I’m not sure it’s worth the effort
This was a very useful and timely post for me. I was on the lookout for a tool to use to evaluate the quality of my predictions, and the Brier score was a concept I didn’t know before now. I will try to incorporate this in my daily routine. Thank you!
One additional variable one could also keep track of is something like a “correction” factor. If I predict a given task will take me 1 week to complete, and it ends up taking 2 weeks instead, then next time I am faced with a task of a similar nature I should remember that last time I was wrong by a factor 2. This “correction” factor should be taken into account when making the next prediction.
The caveat of this approach is that it’s too simplistic and might not fully grasp say the factors that lead to the delay from (predicted) 1 week to (reality) 2 weeks, which might be caused by external factors. Additionally, I now have better knowledge of the factors that lead me to make a wrong prediction in the first place, and I should (maybe) be better at making predictions.
But I think that the best strategy is keeping the “correction” factor simple and not starting to account for all of these factors. I would rather update the “correction” factor in the next iteration.
If you want to get more specific with single outcomes you could also consider making predictions with a normal distribution to get more information, but as far as I know there isn’t a tracker for it and I’m not sure it’s worth the effort