Where to Get Them and What to Do about Them
Software development is more than just writing code. The way a development project is managed matters quite a bit. The tools used by developers as well as project managers and engineering team leads, and the organization itself affects much more than just productivity.
Requirements gathering, prototype design, project management, writing the actual code, testing, in-team collaboration, integration and deployment – all are affected if teams and organizations do not focus on process management and improvement. It can also affect the long-term viability of the development efforts.
This focus on the process, team and individual productivity helps not only on the programmers’ productivity or efficiency but also on the coordination level between the various teams working together.
Software productivity is a ratio between the actual functional values of the targets delivered to the estimated resources requirement.
Many organizations have always focused on gathering data and analyzing them over a period not only as a research exercise but also to improve processes, ensure the productivity and satisfaction of individual developers, improve team collaboration and much more.
Focusing on collecting this data, compiling and studying it and testing hypothesis’ leads to faster release cycles, faster time to the market, higher quality code, satisfied customers and clients, and more importantly better reaction to market changes, the recent pandemic being a good example.
A software development productivity metric is data obtained from the development cycle, either from single or multiple sources, which help in identifying measures to improve the efficiency and effectiveness of software development processes. These metrics, when used either individually or collectively, help measure software productivity.
The key point in identifying the right metrics to be tracked depends on whether the particular data/metric is:
Software development productivity metrics can either indicate the quality of the process of software development lifecycle or product quality post-deployment.
Some of the elements indicating software productivity are:
A clearly defined software development lifecycle with a structured scope for the development team, clear-cut definition of deadlines, and budget constraints avoids conflicting project requirements and predicts the occurrence of bottlenecks.
A few data-driven decisions that can improve software productivity are:
A healthy software productivity approach driven by the right kind of metrics will have a high deployment frequency, deliver good ROI, reduce overshooting of budgets and deadlines, and manage workload efficiently by continually identifying development areas. When continuously integrated with the day-to-day routine of a team, data-driven decisions will help build a good work culture with increased predictability and quality delivery of targets.