This post was inspired by Christian and Griffiths Algorithms to live by. Unlike other self-help books, it argues that the optimal scheduling strategy depends on your goals. If you want to minimize lateness of your single latest output, you should use Earliest Due Date. If you want to minimize the number of late items, use Moore's Algorithm. If you want to maximize value for time, select by value-weighted processing time (value/processing time). And so on and so forth. Based on their work, here is my scheduling plan for different items.
As a phd student, I cannot afford to submit any coursework late. A high maximum lateness is bad for my reputation. Therefore, for coursework I want to use Earliest Due Date. However, I only want to devote a portion of my time to coursework: my primary goal is to become a producer of research, not a consumer. Therefore I should limit the amount of time I spend on each assignment (this also helps w/ focus). I have devised the following heuristics (and usually set timers for each activity)
- Reading an article: 20 min
- Reading an article relevant to my interests: 40 min
- Reading a book: 2 hrs 
- Reading a book relevant to my interests: 4 hrs (in two sessions)
- A problem set: until completion
- A coding problem: until completion
- Writing a reading response: 20 min
After coursework is done, I switch immediately to career development.
These tasks include every behavior that increase my chance of becoming a professor, producing good research, and producing juicey QALY's. The most common tasks are pitching articles, analysing data, writing, editing, writing, communicating w/ coauthors, and writing more.
These tasks should be ordered by value per weight. I have more ideas than I have instrumentalized time to explore them. Any tasks which will take a long time to complete but give only marginal academic value can be thrown out.
The real problem is assigning values to the different tasks. How valuable is planning out my course schedule for the next year? Evaluating a specific research agenda? Exploring the papers in a new field? Unfortunately, I lack good answers for these questions. I'm vaguely aware that I should have >5 articles published when I enter the job market. But the weightings for quality, quantity, prestige and coherence of these publications are unclear. This is a vital area for further research.
This is the one task for which I drop any activity to write it down. If I am reading a paper and I come across a new question or if the authors assumption lacks depth, I go straigth to markdown and write a description on my github. It's okay if the description but refers to the literture that gave the intuition.
I know this sounds crazy, but in my discipline you summarize lots of info fast. ↩︎