They didn't measure when work got done. They measured when people chose to update their project management software. That doesn't necessarily correlate in any way with when the work is actually getting done. So all of their conclusions are based on flawed assumptions and a bad data set.
Anecdotally, I am an active user of multiple project management platforms and do my best to keep them actively up to date. When I am in a state of flow and being productive I almost never break it to update the project management platform.
I'm honestly not sure there's much of a pattern to when it gets updated. Sometimes it's when I'm trying to get into a work mindset and remember what I did the day before. Sometimes it's when I'm winding down at the end of the day and making note of what I did. Sometimes it's in between tasks.
A better measure might be when git commits were made to repositories, but even that is a pretty imperfect measure. I often don't made small commits as a I work, but large ones once a cohesive portion of the task is complete (or several small ones as the same time using git add -p).
Thank you for pointing this out. I know that for myself, Jira updates and high productivity work are anticorrelated. I'm not going to update a ticket while I'm focused on code, and large blocks of flow-requiring work often don't even justify ticket updates until they're done.
Fundamentally, this data just looks like "people update tickets before lunch and before the end of the day", which is hardly interesting.
In fact, I think any quantitative measure of tangible results would be flawed, at least when it comes to open-ended and creative work (research, exploratory data analysis, software design, ...). In my work as a PhD student I often have a full day, damn, even a full week without any tangible result. But when the results eventually do arrive I usually realize that those seemingly unproductive hours actually were valuable, perhaps even necessary.
This is a really good analysis. I wonder if the best measure of productivity might be the number of times someone saves a file in their text editor?
Or if you took git commits, but also measured their size, and came up with an average size of commit per hour of work. That way you could use the size of the commit to roll the clock back and determine when most of that work was done?
Anecdotally, I am an active user of multiple project management platforms and do my best to keep them actively up to date. When I am in a state of flow and being productive I almost never break it to update the project management platform.
I'm honestly not sure there's much of a pattern to when it gets updated. Sometimes it's when I'm trying to get into a work mindset and remember what I did the day before. Sometimes it's when I'm winding down at the end of the day and making note of what I did. Sometimes it's in between tasks.
A better measure might be when git commits were made to repositories, but even that is a pretty imperfect measure. I often don't made small commits as a I work, but large ones once a cohesive portion of the task is complete (or several small ones as the same time using git add -p).