I’ve often wondered whether how hard people work impacts their overall performance. Do people who work longer hours tend to do better? How about people who start work really early? Work a lot of weekends?
Here at Worklytics, we partnered with the CTO of a high-growth, multinational telecom company to pinpoint what sets top-performing engineers apart from the rest.
The Question: What do top-performers do differently?
By analyzing data from the digital collaboration tools,* Worklytics is able to return objective insights on how people are getting work done. Including things like:
We then marry those behavioral insights with performance review scores to understand how top-performers work differently.
Here’s an example of what that looks like for a team of 217 IC-level engineers.
*For this analysis, we pulled anonymized metadata from work email & calendar, Slack, GitHub, and Zoom.
Key Finding #1: Working longer hours does not lead to better performance.
The total amount of time spent working was very weakly correlated to performance scores, as was the amount of overtime that individuals worked.
Somewhat surprisingly, we found that regularly working on the weekend had a slightly negative correlation with performance scores. Ditto for regularly working late evenings.
For this team, the early bird gets the worm. We saw that engineers who started work early in the morning were more likely to have top performance scores than those who logged on later in the day.
Key Finding #2: Work intensity is our best predictor of performance review scores.
The strongest predictor of performance was work intensity, which we measured as:
Work Intensity = (amount of work done) / (time spent working)
As you’d expect, people who did more with their time at work tended to score better – and, interestingly, that held true regardless of the total number of hours they put in each day.
Here, we measured the amount of work done by looking at the units of active collaboration that a person logged each day. For instance, we’d count the number of emails sent, comments entered into a shared doc or code commits made. Engineers with high performance review scores tended to push more frequent code commits than those with lower scores.
One of the strongest predictors of a low performance score was the amount of time spent in meetings each week. The more meetings that an engineer attended, the lower their performance score was likely to be.
As always, we have to be mindful of confounding factors. For example, in the excerpt of the analysis above, we did not take into consideration people’s seniority within the organization. More tenured team members may feel more comfortable declining meeting invites than those who are newer to the organization.
This analysis was focused on Individual Contributors, but you’d expect the picture might look quite different if we added in Team Managers and Directors. By nature of their role, Managers typically have more meetings than Individual Contributors; Managers with highly distributed teams may be required to work longer hours to cover multiple time zones.
Another critical thing to keep in mind is that performance review scores are a subjective measure of performance. Ratings can be heavily influenced by how managers and peers perceive a person has performed and those perceptions may be skewed by different biases.
The biggest takeaway for this team’s CTO was that top-performing engineers weren’t working longer, but they were working smarter. And, for this team, working smarter meant spending less time in meetings.
As a result of this analysis, the company embarked on a Meeting Effectiveness project with an eye toward culling 25% of meetings from engineers’ calendars by the next quarter. Stay tuned for the results.