From business impediment to business enabler, IT development has come a long way since Agile has become the favored practice. Now empowered with speed and responsiveness, organizations have left the days of slow, cumbersome, inflexible, and unresponsive practices behind in the dust. Instead they’re able to support business needs and experience better alignment with changing business environments better than ever before.
It’s easy to understand why Agile is experiencing a strong increase in adoption; as companies become more nimble to embrace the pressures they’re facing in digital transformation, IT development is able to respond aggressively to evolving competitors and exploit markets more easily. But these benefits rival the frustrations on the management side of Agile teams. The nature of Agile makes it so that IT has lost visibility and scope control while the business has lost predictability. While Agile might make teams fast and responsive, businesses don’t know when projects will be delivered, and quality of delivery is often poor.
This is due to story points. Story points is a relative and subjective effort measurement that allows teams to estimate how much work of a certain item is required compared to a certain reference story with a fixed number of points. Story points can be used as an assessment method within a team. But how do these points happen? In an Agile Scrum environment, productivity is often associated with delivered story points, often expressed in Velocity as an estimation unit. The problem is that story points are not standardized, and productivity based on story points means nothing outside of a team itself. Even within a team, story point deflation is always lurking.
Is it even possible to objectively measure productivity? This blog will show that using a ratio scale is the way to objectively measure productivity as proven by IDC Metri’s years of helping clients turn around this common challenge. Management information can be established through a ‘unit of measurement’, bringing answers to long-sought after questions such as which teams are performing well, which teams are not performing so well and when is which functionality ready at what cost?
If you want to use productivity to compare teams, departments, organizations and/or suppliers, or the market, it’s a necessity to use a standard measure of output. Even when this data is about trends on your teams, this insight creates a unified and common view.
For years IDC Metri has been offering function points to create this factual view to clients. Function point analysis was developed in the 1970s to determine the productivity of development teams when it was impossible to do this by counting lines of code. By making function point analysis independent of the technical implementation (programming language, architecture, etc.) and the development method (Waterfall, Agile, etc.), it’s also relevant today and fits into the solution that Agile teams and management need to resolve the challenges that story points create. In short function points are the de-facto standard to express the amount of functionality in a standardized size unit.
Several manual standards are available and one international ISO standard is available for automated function point analysis: ‘Automated Function Points (AFP)’. IDC Metri prefers to use automated measuring of functional size but also employs certified analysts who can manually measure when automated measuring is not possible for whatever reason.
To measure the size of the output of a team, it is also important to not only look at the added functionality but also at the changed and removed functionality. IDC Metri uses automated measuring of ‘Enhancement Function Points (EFP)’ to measure how much functionality has been added, changed and/or removed during a sprint, release or project. This gives the ‘Project Size’ in EFP, a standardized method to measure the output of a sprint or release.
While Agile is hard to measure and manage for full value, the IDC Metri proven approach of using function points transforms a team-driven, fast-moving, rapid iteration process that evaluates progress on qualitative measures into something that can be quantified and predicted.
