Overview
From October through February, the Escalation team closed out an average of 33 issues per month.
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In February, we realized that we were were triaging bugs at a faster rate than they were being resolved. That meant that much of the work we were doing in the triage phase was “waste”, since it might never translate into value for our customers.
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Our insight was that any work that we could defer from the triage phase to the resolution phase would—theoretically—result in a performance gain without any additional effort on our end. Since only a fraction of bugs that completed the triage phase would be resolved, but all bugs in the resolution phase would be, we realized the value of a unit of effort in the resolution phase is greater than the value of a unit of effort in the triage phase.
When looking closer, we determined that the costliest part of triage was finding the root cause. In some cases, we even found the necessary fix for someone to pick up later. We went through our costly triage process because we wanted bugs to be as easy as possible for engineers to fix once they picked them up. The problem was that bugs weren’t being picked up fast enough to justify that investment.
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Crucially, this improvement was only possible because of the Performance Review work that the team did. We had good intentions for our costly triage process: we wanted a ticket to be in an optimal state for a developer to pick it up and fix it. In retrospect, the problem was that tickets weren’t being picked up fast enough to justify that cost. But, since we weren’t measuring the work we were doing triaging, that burden stole upon us silently. Once we started measuring that work, we started seeing exactly how it affected our productivity, and, consequently, which modes of actions would be useful. Our improvement could only work because of the disparity in the rates of triage and resolution; had the data told us something different, we would have had to do something else.
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For more information, I highly encourage you to peruse our dashboard that keeps track of these statistics.
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This process introduced some ideas that the team is excited about running with. Everyone is thinking more about process improvement and how we can tangibly measure the impact of our process experiments. While we don’t expect there to be many more easy wins like this one was, we do expect to continue the cycle of experimentation!
