I realized that people often exhibit planning fallacies. In other words, when it comes to estimating the amount of time it takes to finish Work X, we're often optimistic and allot too little of time. This would be relatively harmless if not for the fact that as Time T grows, the differentials between expected and actual time grows as well. So we plan too little time and the work goes into the backlog.
I thought of a cool little hack for solving this problem. It runs very similarly to how a startup should run: leanly and iteratively. The hack will take your Google Calendar events that you entered for how long it takes you to do X and calibrate a suggested time for you. Better yet, because the data keeps growing, it becomes more and more accurate for time.
So the process is like this:
(1) Say I finish Problem Set 1. I planned that it would take me 3 hours, but it actually took me 6 hours. Well, I record that onto my Google Calendar (the 6 hours it took me)
(2) Next time, with Problem Set 2, the app will note that it took 6 hours to complete the Problem Set and suggest 6 hours.
(3) As more data comes in, I can create a more and more accurate algorithm to parse the input and output a calibrated suggested value
https://developers.google.com/apps-script/service_calendar
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