Time spent on inner/outer loop. The inner loop includes activities directly related to creating the software product: coding, building, and unit testing. The outer loop includes activities related to putting the code into production: integration, testing, release, and deployment. When developers spend more of their time in the inner loop, they are more productive; in top performers it is around 70%.
Benchmarking the Developer Speed Index. By comparing a company’s practices with its peers, it is possible to uncover specific areas for improvement, whether in backlog management, testing or security and compliance. Greater maturity in development practices is associated with better business performance.
Contribution analysis. This refers to assessing contributions to a team’s backlog. Using tools like Jira that measure backlog management, it is possible to spot trends that are detrimental to optimization. The process can also reveal opportunities, such as improving the work environment, increasing automation, or improving individual skills, to address issues that may be harming performance. For example, one company found that the developers who made the biggest contributions were spending too much time on non-coding activities. The company changed its operating model to ensure they focused on what they did best.
Talent capacity. The idea here is to be sure that the right people are in the right place. By implementing industry-standard capability maps, it is possible to create a score that summarizes the individual knowledge, skills and abilities in a specific organization. This can reveal both holes and dents. For example, one company found that it had too many inexperienced developers. In response, it took action, including providing personalized learning journeys, and moved 30% of its developers to the next level of expertise within six months.
Combined with DORA and SHAPE, these tools effectively create a sophisticated view of software productivity. The insight revealed is interesting in itself. The value comes from using them to figure out how to keep developers motivated; whether they have the right tools and expertise; how they spend their time; and whether the staffing level is correct.
Improving an imperfect model
Like the Holy Grail, there are those who believe that measuring developer productivity is a myth and that we are off base. But the 20 companies we work with disagree.