Use of a risk matrix as selector of activity priority execution based on project history

Abstract

The biggest enemy of project management is variability. One way to measure variability in plan execution is using an indicator proposed in the Last Planner System (LPS), Percent Plan Complete (PPC) (Ballard 2000). Regrettably, many issues of different nature affect project execution, causing the completion of all scheduled activities to be difficult to reach. Theoretically, we have to control all activities involved in short-term periods, but the resources are not always enough to do this (Wembeke 2012). In order to make best use of the limited resources it is important to understand what activities should have priority in a project schedule.This paper proposes the use of LPS metrics to build a Risk Matrix which organizes activities in order of importance, through calculations made by algorithms fed by historical project information. The activity importance is determined by the level of impact. This level is defined combining criticality and probability levels that are calculated through the analysis of selected variables: numbers of links between activities, assignment of resources, constraint release history, causes for non-completion, PPC, etc. Identification and prioritization of activities which have a bigger impact on a project is a useful way to reduce variability, considering that it may decrease the triggering of chains of delays. Along with this, the mere fact of establishing the most significant activities in front of all participants of planning meetings, generate a psychological effect on all those responsible for tasks, which should allign efforts accordingly. This tool is consistent with the LPS philosophy, it doesn’t focus on individual performance, it takes the team members behavioral history and includes it in the algorithm, producing a warning that indicates that an activity must be followed closely, without assigning responsibility to any team member.