As the world opens up, some people would like to continue to work from home, and some are opposed to it. The right answer may come down to which method is more productive.
Thanks to COVID-19 most IT workers are now approaching two months into a work from home marathon. Many people have become used to lunch with the entire family and the zero-minute commute. As the world opens up but school has not yet started, some people would like to continue to work from home, and some are opposed to it. The right answer may come down to which method is more productive.
TechRepublic interviewed two experts to get to the truth. Edward Blackman is the managing partner at Kelda Consulting, where he focuses on lean continuous improvement and organizational behavior. Matthew Gregory is the CEO and founder of Ockam, which creates an encryption layer on top of the technology stack so companies can use open source tools to build internet of things systems with confidence.
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The balloon effect
Even with a variety of productivity measures, Blackman explains, it is possible to have a “balloon effect.” Measure lines of code and you will get a lot of code, which is likely overly complex. Measure complexity and you’ll get lots of simple code that might have bugs or not handle exceptions well. Just like a balloon, squeezing on one measurement results in an overflow to something else not measured. Add a large number of measures, and the organization will struggle under the weight of the measures, creating mediocre results.
That is, if they even have productivity measures at all.
“Nine times out of 10, when I ask for productivity measures, companies show me financial measures. The leaders either use productivity measures with little value [like lines of code], or they use financial measures as productivity measures.”
In other words, you could be 25% more productive working from home building new features, but if sales are down due an external factor (such as a global pandemic), the argument could be “working from home doesn’t work.”
Measurement problems
I asked Blackman about dysfunction. If, for example, the organization measures “velocity,” but allows the team to determine the size of work in “points,” then velocity will invariably go up, but that might not lead to more software delivered. The same is true for counting bugs. If bugs are bad, technical staff can reclassify them as “anomalies” or “requirements issues,” or simply not record them at all.
Blackman doesn’t disagree with me, but he points out the one thing he sees missing in nearly every metrics program—any tie back to leadership. That is, leadership sets the expectations and incentives. For example, Edward does not recommend any financial incentives around an immature measurement. Many companies, for example, have value statements similar to this one from Tootsie Roll Industries: “We do not jeopardize long-term growth for immediate, short term results.” When he sees people making these tradeoffs to pad metrics, Blackman suggests coaching.
When it comes to those productivity measures, one thing to look at is commits to open source projects. Assuming the rough effort spent between commits does not radically change, more commits from the same people should generally correspond to more time spent at a keyboard developing software. I asked Matthew Gregory for his comments, from his position.
Ockam’s razor
Gregory tells me they are a 100% work from home, 100% open-source company. “We structured our company as open source and remote-first for productivity and efficiency. That is something we had in place from the first, not something we were forced into.”
He points me to a recent virtual keynote from Nat Friedman, the CEO of GitHub, at its recent virtual conference. About five minutes in, Friedman points out that since January, GitHub has seen an increase in collaboration through more issues (with a 25% year over year increase per user), a decrease in the time to merge a pull request (the average is down by four hours per request), and an increase in time on the site, with users spending roughly an extra hour per day on GitHub. Friedman attributes this to a reduction in time spent commuting.
Gregory is optimistic about those numbers. While hobbyists exist, Gregory contends that most open source development is driven by commercial interests. If a company is producing a free/open product and selling services, or trying to get commits back to its core base from the community, or contributing an extension to fill a gap, in all three of these cases more open source software means more value for the business.
Given the predominance of business software for open source contributions, Gregory can only interpret the uptick in GitHub use as evidence of increasing productivity under COVID-19.
“The idea that productivity seems, to me, to be a reasonable conclusion from all this. It explains the data. Perhaps data like this, and a few other data points that come out of this big experiment can help disarm the arguments managers make that they cannot know if people are doing work from home. After a few months of doing this, we can establish trust, and, when you get down to, so much of the problem is a lack of trust.”
Gregory’s company is named Ockam after Ockam’s Razor, the old philosophy of science that in its simplest form, boils down to “The simplest solution is probably the correct one.”
It looks like GitHub contributions are up during COVID-19, and people are using it more effectively.
Perhaps that is because they are getting more things done.
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