A better way to think about developer productivity metrics

developer experience   success triangle   fast flow  

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These days, there’s a lot of talk about ‘developer productivity metrics’. The term suggests that each developer has a productivity metric (or metrics), which can be measured, just like their height or weight. This is an appealing idea since these metrics would be a handy way to compare developers and teams, identify areas for improvement, and identify candidates for promotion or firing. But in reality, these metrics mostly measure something other than the developers. Keep reading to find out more.

Examples of developer productivity metrics

The most well known developer productivity metrics are the DORA metrics:

• Deployment frequency - the frequency with which software changes are deployed to production.
• Lead time for changes - the time it takes to go from commit to deploy.
• Time to restore service - the time it takes to restore service after a production incident or outage.
• Change failure rate - the percentage of production deployments that result in a failure or require remediation.

But there are also DevEx metrics, which measure the developer experience, which concerned with “how developers feel about, think about, and value their work”. The DevEx metrics measure three core dimensions: feedback loop, cognitive load, and flow state. They are both quantitative metrics, such as the time it takes to get feedback from a code review, and qualitative metrics, such as how developers feel about their work.

What these metrics actually measure

While these metrics can be part be traced back to the actions or perceptions of individual developers, they are mostly not a measure of the developers themselves. They are a measure of the productivity of the socio-technical system, of, which, the developers are just one element. The other elements of the system include

• Engineering principles and practices
• Company culture, e.g. Westrum typology: pathological, bureaucratic, or generative
• Engineering organization’s structure
• The application: architecture and codebase
• Tooling including the developer laptops and their software, and infrastructure services like CI/CD, issue trackers, monitoring, ….
• Other members of the company that have influence over the above

Developers control over some of these elements, but not all of them. For example, developers can’t control the company culture, or the engineering organization’s structure. Moreover, the application’s architecture and codebase are the result of past design decisions, perhaps by developers who are no longer with the organization.

Socio-technical system productivity metrics?

Ultimately, an organization’s leaders have the greatest influence on the system’s productivity. In many ways, therefore, the developer metrics actually measure the effectiveness of the leaders, not the developers themselves. It’s tempting to use the term ‘engineering leadership effectiveness metrics’ (ELE metrics). But in reality, productivity is the responsibility of the entire organization so ‘socio-technical system productivity metrics’ (STSP metrics) is a better term.

What do you think?

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