I admit: I have a hard time estimating the time required to do research. On a given week, despite hard work and steady progress, I may think I only completed 25% of what I should have done. This evergreen feeling is stressful and discouraging, and stems from unrealistic goals. I often don’t even enjoy significant successes because of all those other things I didn’t finish. I’m sure a lot of graduate students feel this weight.
I suspect I would feel more satisfied if I made realistic plans for a week.
To make some headway, I decided to start an experiment to learn to make better plans. This is not a motivational or time management exercise (my work ethic is not the problem). The point is to learn what reasonable expectations look like.
I’m a loose Getting Things Done (GTD) follower, and one of the practices I implement is the weekly review. During my weekly review, I tie off all the loose ends from the past week and line up everything for the next. I recently read about Cal Newport’s plan.txt file, which inspired me to add a new twist. Here is the exercise, which will take place during the weekly review:
Write a paragraph which states, in broad terms, what I hope to accomplish the following week. “I want to advance to point xyz in this simulation,” “write section 2.4 of my dissertation,” and “create exam 2 and plan next week’s lectures for my statics course.” (This is not my task list – that lives in OmniFocus.)
Get things done for 6 days.
During the following week’s review, compare what I actually did with the previous week’s plans, and try to objectively assign a ratio to that. “Last week I overestimated what I could get done by 2.0x.”
Add that week’s ratio to a simple graph where I can visually track my progress.
Ask: What can I learn from this past week? Using these observations, repeat the process (i.e. go back to step 1).
The point is not focusing on what I should have done, just an unemotional evaluation of what I actually did. If this works, the estimates will converge toward 1.0 and I will be ending my weeks feeling, at a minimum, that my work output matched my expectation.
I still know there many unknowns in research; you don’t always know if an idea will bear fruit or what problems may arise. But by measuring this type of data over time, I hope my intuition will improve.
I’m going to report back with data and observations in a few months here on the blog.
To those prolific researchers in the audience, how did you learn to manage personal research expectations?