Measurement is difficult to carry out in the agile engineering and management process. However, in practical activities, developers have been trying to use measurement to manage and monitor their own projects.
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Measurement of software features helps developers to understand the software requirements consistently and completely, to know the actual quality extent and to make sure that the code is tested; For PMs, measurement process and product characteristics help them to understand whether the project schedule and cost is within the scope of the release time and budget projections; of course, customers have to go through the measurement, to test whether the final product meets demand with high quality. Maintenance personnel need the metrics to evaluate the current product, so that they can know how many efforts are needed in upgrades and improvement.
Some Scrum teams don’t agree that having metrics is an important factor in agile project management, but whether they agree or not, the metrics in agile projects is everywhere. On the other side, although a growing number of Scrum project teams recognize the historical data will help the project a lot, they wants to use the historical data to estimate and predict, most projects team don’t know what kind of metrics should be collected, or don’t know how to analyze the collected metrics, and how to use these metrics to guide their work.
In order to correct the misunderstanding about the metrics, and to help those who have realized the importance of historical data and want to use metrics to identify the problems, and find the root cause of the problem, improve the visibility of product and process performance, we should introduce the SPC – statistical process control to our Scrum project team.