How tracking a few key metrics can have a variety of higher order effects on your incentives and behavior
This article relies on familiarity with Beeminder. It’s a service that enables you to set up incentive structures — in other words, it’s a motivation multiplier. If you haven’t encountered it before — you should learn about it now — it’s brilliant 😉.
Is there anything you want to do, that you can do, that historically you haven’t actually done? Maybe you want to start…help.beeminder.com
What I want to talk about is a specific application of it I found particularly useful — beeminding the number of Pomodoros 🍅 completed per day.
Why is it interesting
I’ve started beeminding Pomodoros last November. The first consequence of that was that the average time I’ve spent doing focused work has increased by around 15%. And that is remarkable on its own.
But I’ve also found that over time this had a variety of curious unintended consequences.
It forced me to restructure the way I do small recurring tasks
They don’t fit this style of work well, but I still wanted to get points for doing them 😊. So I’ve designated a regular Pomodoro to deal with these tasks. This allows me to give them more love on average but also prevents me from spending too much time here. Some examples of tasks in this category:
- Reviewing Anki cards;
- Reading and replying to peoples emails/messages;
- Making appointments.
I use Pomdoros as an estimation unit for task complexity
Tracking them over time gave me some baseline numbers for how many Pomodoros I can expect to complete for any given unit of time. As a consequence, I can use those baselines to plan my activities for the day or a week.
On a side note: I use a free version of Asana for tracking my tasks, so I needed to reserve to a fairly hacky way to do the estimation.
Visualizing completed Pomodoros gives me insight into how I work
I have an automation task that adds completed Pomodoros to a dedicated Google Calendar. The header image is an example of the entries for one week. This allows me to infer a variety of things about the character of my performance during the day or a week.
What have I learned from doing this:
- I was able to reclaim half an hour of personal time in the evening. I achieved this by shifting my sleep schedule by 10 minutes. Which allowed me to fit an extra unit of focused work in the mornings.
Examples of other things I looked at and learned from:
- How close are the tracked Pomodoros to each other? The large pauses between Pomodoros are indicative of something detrimentally impacting my performance.
- What part of my day is the most productive?
- What are the common interruptions in my flow and when do they happen?
Remember Goodhart’s law
The importance of using the right metricstowardsdatascience.com
When you strive to optimize a metric you should always be conscious of how well that metric matches what you actually want to achieve
And you need to be wary of fooling yourself.
The first principle is that you must not fool yourself and you are the easiest person to fool.
Richard P. Feynman
There are two broad avenues for getting fooled by the outlined approach:
- Tracking Pomodoros while you’re doing something irrelevant. I describe my approach for dealing with this below.
- Not actually being focused during the Pomodoro and still counting it towards the goal. I have nothing explicit in my system to control for this. But I’ve seen an interesting approach suggested here — using TagTime to check yourself.
Tracking relevant things
The Pomodoro tracking does not discriminate between the types of work you’re doing. You can be shopping for a toothbrush or working on the Theory of everything — you will get points for either.
That’s why a few months ago I’ve introduced an “Important work” tracking.
I use the following formula to count points for this goal:
items - Pomodoros with a designated tag completed today
important work for current day = min(1, items/2)
The idea here is to incentivize a sustained, regular work on the projects you deem most valuable. It rewards you for working towards your goal. But it also shifts incentives from doing sporadic bursts of activity to performing regular work.
I had some initial friction with this goal, but now, after a few months, I can declare it a success. It achieved the stated goals of encouraging gradual sustained work on important things. It also had a side effect of making me think about what is important more often and more explicitly.
How does it work
This goal has a large volume of the data points. So implementing comprehensive tracking automation was one of my objectives from the outset.
I use Toggl time tracking service as a foundation. The two main reasons for that is that it integrates with pretty much anything and that their clients have Pomodoro functionality (that’s partially my fault 😛).
My workflow looks like this:
- Add a task to Asana/OmniFocus and estimate it’s completion time in Pomodoros;
- When it’s time to work on the task — I use the Toggl to create an initial time entry for tracking what I’m working on;
- For the later entries, I use Toggl Alfred workflow — it allows me to find and resume work on one of my previous entries in just a few shortcuts.
- Every 6 hours an Integromat task runs and creates a Google Calendar events for the Toggl entries that fit the criteria;
- IFTTT task then triggered and it converts the calendar events to Beeminder entries.
This workflow has evolved to its current state for historical reasons. You can certainly achieve the same goals with a simpler approach.
The metrics can often be dangerous and mislead you in your quest of pursuing your goals. But if you stay vigilant and control for that — they can bring you a lot of value. This is an account of one successful application. I hope you found it useful.