January felt long and slow. But I ran more miles than I did all of last year. And I read more books than I usually do in a month.
Those were pretty easy things to track.
February, on the other hand, needs to be less about miles though and more about avoiding injury. I’ve noticed a pattern—every January I run is consistently followed by a steep drop-off in February. Injuries.
A lot of factors contribute to injury: mileage, weight, form, diet. But for me, the one I’ve historically ignored is strength training. You know, the 20-30 minutes of cross-training or weight lifting after a run or on a non-running day. The thing I know I’m supposed to do but always find a way to justify skipping—because I follow a training plan, warm up properly, and stick to the golden 10% mileage rule (don’t increase miles week to week by more than 10%).
So, this weekend, as I felt good about logging miles in January, I caught myself. I was this close to finding an intermediate training plan that would put me right back into long-distance mode (8-12 mile long runs once a week).
I caught myself and looked for a shorter race instead, asked a couple of cousins and friends to join me for that accountability factor. Then I started looking for a better suited training plan.
It felt too easy.
So I paused. What reason do I have to think I’ll avoid injury this time without strength training?
I love a good data visualization. But what if I’m tracking the wrong things? Nike and Strava collect my mileage and pace, but they don’t track whether I actually do strength training—or whether skipping it is what causes my February drop-off.
For the past couple of years, I’ve been mindful of a few key areas and actually track them in spread sheets: Sweat, Read, Write, Connect, Extend the Window of Tolerance, Remove, and Plan. These are the main buckets I try to track to keep me operating at my best. Sometimes I’m not as consistent as I should be, but they keep me honest.
I don’t have a way to get one of those data visualization “aha!” views just yet though.
But I’m wary of tracking just for the sake of it. I love my PMO (Project Management Office) people, but I spent enough time in my corporate life entering endless data into tickets because someone with a higher title than I thought it was important data that would lead to powerful insights. That person always left. Priorities always shifted, JIRA schemas always shifted. And the data always became irrelevant.
Avoidance/procrastination, people-pleasing/avoiding conflict, hyper-vigilance/overthinking—these are patterns I help others recognize. But they can apply to me, too.
Did my January spike in books read actually spark new ideas to write about or connections made, or was it just procrastination in disguise? Is there a correlation between new clients and books read in a month? I don’t have enough historical data to say for sure. But I come from the product management school of thought, which believes decisions still have to be made, even without perfect data.
So I’m making a decision: I’ll experiment with this one for a couple months, tracking just enough to be useful—without adding unnecessary admin overhead for myself.
I’m thinking I can make tweaks to my Extend the Window of Tolerance, Remove, and Plan tabs for a couple weeks to months to see if there are any wins gained in the short term.
🎵 Now Streaming 🎵
Ladies & Gentlemen… 50 Years of SNL Music
I could watch SNL anything, all day, every day (see, procrastinator). Produced by Questlove, this anniversary special (ie. jawn) is awesome. Fifty years of incredible performances, weird performances, dud performances, and TV defining performances.
Roughly 2,000 throughout the years I’m guessing 🤔 (50 years x ~20 episodes per season x ~2 performances per episode = 2,0000). That’s not even including the cast originals from Lonely Island and the gang. If this full playlist doesn’t exist yet, it should.
I would skip the Grammys all over again to watch this instead.