June 16th was a great day — I have a mathematical model to prove it. It was an unremarkable Tuesday: not too busy, a light run in the middle of the day, and a scattering of Zoom calls for work. And yet I ranked it 5 out of 5 — the only one I have on record.
Models are powerful tools for simplifying and explaining complexity. And what is more complex than ourselves? Thanks to some additional alone time provided by COVID-induced lockdown, I recently went back through years of data I’ve collected on myself, and the crude models I’ve built to explain my own patterns and complexity. At the risk of being outed as an epic nerd, I thought I would share some learnings.
About two years ago I became interested in tracking my time more carefully, and began to track a collection of variables I thought relevant for evaluating how my time is used. This first “model” of myself was very basic, and focused on the professional. The inputs were biological staples — sleep, exercise, alcohol — and time. The outputs were my goals (daily and weekly). Here’s a typical day:
Time allocation — 2.5h work block, 2h product review, 2h XFN syncs, 0.5 coaching 1:1, 0.5 metrics review, 1hr design/ideation
Inputs — light weights / run, 2 drinks, 7 hours low quality sleep
Goals — kick-off performance reviews, staffing for new team, agree roll-out plan for [Project x]
As meetings added up, I developed a basic system of colors for my time allocation (Google Calendar has 12 colors, with intuitive names like “Sage” and “Tomato”), and wrote a short script to pull the total hours by color from the Google Calendar API (script below — fun fact, there is a now a company called Clockwise that has expanded on this theme). For the other data points, I would manually record them in Google Keep.
My initial wins from this system were significant, albeit short-lived. Time tracking yields great insights about how fractured your days are and potential mismatches between priorities and time allocation (much has been written on this subject, such as Flow, the maker/manager schedule and The One Thing to name a couple). And writing down goals is in itself helpful both for clarity as well as a sense of accomplishment at the end of the day.
While this early model helped to set my body and my schedule up for success, I found that the quality of my time spent remained variable. Some days, with similar biological baselines and schedules, were simply better than others. And on these days I would fly through priorities, have extra clarity in meetings, and generally feel better about everything happening. How could I get all days to feel like that?
My first instinct was to go deeper on physical inputs — to measure sleep in more granularity (REM, deep, getting up to go to the bathroom), and to measure type of and time of day for exercise. But I soon realised this focus on physical inputs was exactly the issue — they were easier to measure, but not necessarily the factors that mattered most. In other words, I was focusing on the wrong things.
More recently, I decided to try to measure directly what was going on in my own head: my mood. I used a simple scale of 1 to 5, taking the average of the day, a 5 being extremely positive and a 1 extremely negative. My thinking was that better moods would correlate closely with these occasional “great days” I’d experienced — days with more clarity of thought, more energy, more empathy. And if the quality of time spent on those days was higher, I would accomplish more. All I had to figure out was how to manufacture more of those days.
I compiled the results of these observations, along with the additional physical metrics, on a chart and looked for correlations (see below — physical inputs are indexed). My initial reaction was frustration. The only conclusions were glaringly obvious: a day of heavy drinking tended to correlate with low mood the following (note the grey valleys following red peaks); and steady exercise and low drinking during the week tended to correlate with low mood volatility. Had I done all this work to conclude I shouldn’t drink too much and should have a stable weekly routine?
But the data told only part of the story. Pouring through the daily notes I had written alongside the data, looking at the drivers beneath the daily results and the trends between days, there were more subtle conclusions to be made.
The first observation was that mood was driving output, but output was also driving mood. A day that began poorly could become a great day if something important was accomplished, something new was learned, or both. No wonder I was seeing such a strong correlation between how I felt and what I was getting done, the relationship seemed to be mutually reinforcing. It also meant that negative trends had the potential to be reversed; I could manipulate my days into becoming productive or stimulating, and in the process feel better about them.
A second observation is that the body is self-regulating and naturally fluctuating. It was rare to experience more than a couple 4s in a row and rarer still to experience multiple 1s or 2s. Similarly a streak of 3s would eventually be broken, sometimes for no obvious reason at all. The body’s homeostasis was both my enemy in an upswing but my friend in a downswing. But knowing is powerful — it reminds me not to become too rooted in routine, as that routine will get folded into a new baseline (one example — my longest streak of 3s and 4s came not from strict adherence to routine but from a stretch when I went on a “try new things” binge). This realisation also provides a powerful tool in the downtimes: just wait. Rough times will pass as great times will (and just thinking this way can help rough times pass more quickly).
A last observation is that days are filled with triggers — thoughts or events that can move the self in positive or negatives directions. Reinforcing positive triggers, or shutting down negatives ones, can be the key to stabilising or improving a day as it unfolds. I noticed a particularly prominent negative trigger of mine to be projection: when in a negative state of mind, I would generate anxiety and uncertainty about the future. Shutting this down turned out to be akin to exercising a new muscle; I simply had to force myself, in those moments, to think only of the present. Working out is one effective method I use; short breathing exercises is another.
The more I began to understand these findings, the more I found myself incorporating these subtle tricks into my life. The importance of finding a few things to accomplish in a day. The importance of finding novelty and the stimulation that comes from breaking routine. The value of patience and perspective. And the calming effect of bringing oneself back to the present. These learnings, while less concrete and tangible than my earlier productivity “hacks”, have had far greater impact.
Over the last few months, and with some practice, I’ve noticed a marked improvement in results. My output, measured by goals, is generally higher and less volatile. On mood, I’m now more able not just to hit 3s and 4s consistently but to manufacture 3s out of 2s and even 1s (5s, however, remain frustratingly elusive). But I’m also aware of how easily this new normal can become part of a new baseline: our self-regulating nature can never be escaped.
Today I’m far less diligent with all this data collection. I have my calendar system and my goals for work, but I’ve scaled back the daily journaling, the mood scoring, the other inputs. It is not because I do not think it’s useful data. I would rather, however, focus on actually practicing what I’ve learned, making more “great” days, and inevitably finding more internal complexity that I will struggle to understand.