Conventionally, enterprises have measured the success of their software development with a set of objective metrics that are usually defined at the start of a project. Such metrics helped the project managers and business teams track the timelines and costs associated with the various project milestones against the respective targets defined at the outset. In doing so, managers were reasonably assured of delivering the software within time and budget. However, there was not much emphasis on the actual success of the software post deployment.
Critical questions such as whether the end users were happy with the way the software functioned, and what kind of impact it had on business results were left largely unanswered. This is where modern software development services have transformed the way metrics are used to gauge a project’s success.
With the evolution of software development from single, large releases to rapid, customer-focused iterative methodologies such as Agile, DevOps, Continuous Delivery and automated development, the project management metrics need to evolve as well. Historical software quality parameters are, therefore, no longer relevant. They could even be considered misleading, if used inappropriately or used to compare multiple projects for merely tracking their efficiency and throughput.
For modern product development processes, quality is an essential part of every build release. Hence, project managers must use both subjective and objective metrics that are designed around the business value the product delivers to the end customer. That way, the business can monitor all key performance indicators (KPIs) to see if the software is delivering on its intended results with regard to performance improvement and other aspects. The new-age metrics must, thus, focus on tracking the software’s effectiveness rather than merely charting the efficiency of development.
Here are some of the important value-based metrics you should consider tracking to ensure your projects deliver on their pre-defined business goals:
- Team Productivity or Velocity: Here, the number of user story points delivered by the team per sprint is recorded. However, this should not be used as a comparative parameter between teams. Rather, team velocity will help managers ascertain the typical productivity of the team per sprint so that this knowledge can be used to plan future iterations better.
- Individual Productivity: This KPI quantifies the productivity of individual team members as the number of user story points per developer per sprint. Again, the goal is to simply assess the capabilities of each team member, and not use the data as a performance evaluation criterion.
- Defect Density: This is a true software performance measure that captures the number of confirmed defects identified in a software during a defined period of operation, divided by the number of user story points, i.e. the size of the software. By tracking this metric, the actual performance of the application in production can be improved.
- Production Incidents: Another related performance improvement metric is the number of production incidents or software crash rate. This is defined as the number of times the software crashed versus the number of times it performed as per plan. Using this metric and incident root cause analysis, organizations can improve application performance over time.
- Defect Leakage/Seepage: Here, the ratio of total defects identified in a defined phase divided by the number of defects identified during formal testing is measured. This way, both development and testing effectiveness can be improved.
While the above are some specific metrics used in Agile processes, other common ones include the cycle time, lead time, number of customer issues and number of committed stories versus delivered stories. Whatever metrics a business decides to track across its software development lifecycle (SDLC), it’s important to remember that the fundamental objective of a metric is to help the business make better decisions. So, you should customize your KPIs based on your software development requirements and user expectations, rather than tracking standard metrics.