One of the questions we often get asked at Essilen Research is “How do I know if my staff is the right size?”. Companies of all sizes struggle with this. Young companies need guidance on when to slow their rapid early growth. Mature companies wonder if a reduction in workforce would be warranted, and if so, how much is right?
One client in particular was an executive at a ~100 person software company. The technical staff was arguing that they desperately needed to add 10 new engineers, while their finance staff was arguing that the financials didn’t justify it. The executive suspected the technical staff could probably survive without 10 more people, but couldn’t shake the feeling that perhaps there was some validity to their arguments. What to do?
Essilen assisted this client by getting at the root of why this decision was so difficult: the two sides weren’t talking in common terms. Finance was arguing in dollars, whereas the technical team was talking about architecture, bug counts and man-month efforts.
The first step to untangling this decision was to work on getting a measure of engineering efficiency. This meant working with their technical staff to measure its efficiency and (in the case of software) measure the debt and depreciation of the software asset. This may sound tedious, but most clients find this process liberating both for the technical staff and for executives. That’s because the technical team is given the tools to express their workload precisely, and finance and executives actually get to see technical work expressed in dollars. The result of these efficiency discussions is to align teams and get them speaking the same language.
In the case of our 100 person company, there were two specific and interesting outcomes. First, by actually measuring engineering efficiency, the team uncovered a big source of inefficiency: their test team and development teams were not well integrated and caused big delays.They decided to do a reorganization. Second, after they reconfigured their teams, the technical leadership thought they could drop their request from 10 new hires to 4, and finance agreed it made sense.
This kind of outcome was possible because a systematic process was applied to a difficult problem. Tech teams learned the tools they needed to understand their operation better, and to better communicate with the rest of the firm. In the end they still had to apply their best judgement, but the analysis work enabled a decision that was based on an agreed-upon set of facts. Intuition was expressed systematically and the organization made a better decision.
The best part is, the company put in place a system to measure efficiency going forward and created a forum to discuss challenges. They both systematically improved their operation and their decision-making culture.
