IMPROVING SCRUM-MANAGED PROJECT PLANNING THROUGH PRODUCTIVITY ANALYSIS

In projects managed under the SCRUM framework, planning involves estimating the time and effort required to complete the user stories and optimizing the resources' workload. Hence, it is necessary to assess not only the affinity between user stories and those of completed projects but also the deviations in productivity through the project sprints. However, balancing the estimated SCRUM team workload across multiple projects is generally difficult. This study proposes a planning and monitoring tool for projects managed with SCRUM: the SCRUM productivity curve. This productivity curve is calculated by comparing the planned and actual amounts of person-hours from planned and completed user stories. To achieve this, we employ non-linear regression comparing actual productivity data with a theoretical model. The most relevant calculations are developed using a real case study implementing the SCRUM framework. It shows how the proposed SCRUM productivity curve can help project managers balance the resource workload at the project and portfolio levels.