A topic that often results in great debate is “how to measure engineers?” I’m a pretty data driven guy so I’m a fan of metrics as long as they are 1) measured correctly 2) used properly and 3) not taken in isolation. I’ll touch on these issues with metrics later in the post, let’s first discuss a few possible metrics that you might consider using. Three of my favorite are: velocity, efficiency, and cost.
- Velocity – This is a measurement that comes from the Agile development methodology. Velocity is the aggregate of story points (or any other unit of estimate that you use e.g. ideal days) that engineers on a team complete in a sprint. As we will discuss later, there is no standard good or bad for this metric and it is not intended to be used to compare one engineer to another. This metric should be used to help the engineer get better at estimating, that’s it. No pushing for more story points or comparing one team to another, just use it as feedback to the engineers and team so they can get more predictable in their work.
- Efficiency – The amount of time a software developer spends doing development related activities (e.g. coding, designing, discussing with the product manager, etc) divided by their total time available (assume 8 – 10 hours per day) provides the Engineering Efficiency. This is a metric designed to see how much time software developers are actually spending on developing software. This metric often surprises people. Achieving 60% or more is exceptional. We often see dev groups below 40% efficiency. This metric is useful for identifying where else engineers are spending their time. Are there too many company meetings not directly related to getting products out the door? Are you doing too many HR training sessions, etc? This metric is really for the management team to then identify what is eating up the nondevelopment time and get rid of it.
- Cost – Tech cost as a percentage of revenue is a good cost based metric to see how much you are spending on technology. This is very useful as it can be compared to other tech (SaaS or other webbased companies) and you can watch this metric change over time. Most startups begin with their total tech cost (engineers, hosting, etc) at well over 50% of revenue but this should quickly reduce as revenue grows and the business scales. Yes, scaling a business involves growing it cost effectively. Established companies with revenues in the tens of millions range usually have this percentage below 10%. Very large companies in the hundreds of millions in revenue often drive this down to 57%.
Now that we know about some of the most common metrics, how should they be used? The most common way managers and executives want to use metrics is to compare engineers to each other or compare a team over time. This works for the Efficiency and the Cost metrics, which by the way are primarily measurements of management effectiveness. Managers make most of the cost decisions including staffing, vendor contracts, etc. so they should be on the hook to improve these metrics. In terms of product out the door as measured by story points completed each sprint a.k.a. Velocity, as mentioned above, is to be used to improve estimates, not try to speed up developers. Using this metric incorrectly will just result in bloated estimates, not faster development.
An interesting comparison of developers comes from a 1967 article by Grant and Sackman in which they stated a ratio of 28:1 for the time required by the slowest versus the fastest programmer to complete a task. This has been a widely cited ratio but a paper from 2000 revised this number to 4:1 at the most and more likely 2:1. While a 2x difference in speed is still impressive it doesn’t optimize for the overall quality of the product. An engineer who is very fast and with high quality but doesn’t interact with the product managers isn’t necessarily the overall most effective. My point is that there are many other factors to be considered than just story points per release when comparing engineers.