I guess you will have several recurrent tasks and some short/medium-term goals, then i’d recommend using something like this to track how calibrated your predictions/estimations are:
It helps you not only to organize what you are doing and how are you progressing, but also to cultivate a better sense of how to estimate what you can do and get used to develop a quantified way to make predictions using the shorter feedback of your tasks.
It doesn’t automatically translate to other domains, but at least you will already have a better framework to make predictions about other things, e.g., you will have a clearer idea what it means to say that “something should happen with a x % chance.”
It doesn’t takes much effort after you get used to it, and if you are going to keep a to-do list, the predictions add almost no extra burden.
Checking the results is mostly automatic (you can experiment with other ways to look at the data, ex. based on how long are the predictions or for a specific project of kind of task), and it gives you good feedback on how to adjust the predictions you will make next.
And, it helps you to get a better view of what is possible to do each day and prioritize what is more important.
For example, after i automatically predict what i have to do one day, i can review the predictions based on the load i know i can handle and some other past information to have a better estimation of what i expect to accomplish that day.
Additionally, there is no guilt after failing to do everything, because the idea is to push yourself and correct until you can finish the expected number of tasks.
I noticed i could push myself to more thing this way than if i had just a common to-do list to complete and i could just balance how much i need to work and how much i can just procrastinate to finish what i’ve set.
I could also set some goals or have more abstract tasks, e.g. “finish a big project,” and then start breaking it into smaller goals/tasks to track how i was progressing and to distribute the load until the deadline, instead of just work in small bursts and eventually try to do too much when the deadline was getting closer.
The only caveat is that you will game your predictions, as focusing on the ones with a higher prediction because you are expected to complete them more often and don’t mess with your calibration curve, but soon you will learn to incorporate this kind of information to make your predictions.
And, it is also possible to use this to your advantage later, for example, by picking a tasks that repulses you, and keep getting postponed, and assign a higher chance that you you do it, and then just do it because you said you were going to do it.
I guess you will have several recurrent tasks and some short/medium-term goals, then i’d recommend using something like this to track how calibrated your predictions/estimations are:
https://www.lesswrong.com/posts/8JEHPAcJ6ppywtkqK/calibrated-estimation-of-workload
It helps you not only to organize what you are doing and how are you progressing, but also to cultivate a better sense of how to estimate what you can do and get used to develop a quantified way to make predictions using the shorter feedback of your tasks. It doesn’t automatically translate to other domains, but at least you will already have a better framework to make predictions about other things, e.g., you will have a clearer idea what it means to say that “something should happen with a x % chance.”
It doesn’t takes much effort after you get used to it, and if you are going to keep a to-do list, the predictions add almost no extra burden. Checking the results is mostly automatic (you can experiment with other ways to look at the data, ex. based on how long are the predictions or for a specific project of kind of task), and it gives you good feedback on how to adjust the predictions you will make next. And, it helps you to get a better view of what is possible to do each day and prioritize what is more important. For example, after i automatically predict what i have to do one day, i can review the predictions based on the load i know i can handle and some other past information to have a better estimation of what i expect to accomplish that day.
Additionally, there is no guilt after failing to do everything, because the idea is to push yourself and correct until you can finish the expected number of tasks.
I noticed i could push myself to more thing this way than if i had just a common to-do list to complete and i could just balance how much i need to work and how much i can just procrastinate to finish what i’ve set. I could also set some goals or have more abstract tasks, e.g. “finish a big project,” and then start breaking it into smaller goals/tasks to track how i was progressing and to distribute the load until the deadline, instead of just work in small bursts and eventually try to do too much when the deadline was getting closer.
The only caveat is that you will game your predictions, as focusing on the ones with a higher prediction because you are expected to complete them more often and don’t mess with your calibration curve, but soon you will learn to incorporate this kind of information to make your predictions. And, it is also possible to use this to your advantage later, for example, by picking a tasks that repulses you, and keep getting postponed, and assign a higher chance that you you do it, and then just do it because you said you were going to do it.