CPM Schedule Density: A New Predictor for Productivity Loss

Abstract

This dissertation addresses construction labor trade stacking, which oftentimes creates adverse labor inefficiencies, delay and cost overruns on construction projects. Present industry practice holds that Critical Path Methodology (CPM) scheduling is more accurate with resource loading assigned to construction activities, and that likelihood for trade stacking is reduced when managing a resource-loaded schedule. However, despite the potential benefits, and for many reasons, most contractors choose not to resource load their schedules. This research sought to create a predictive model for construction labor productivity loss using non-resource loaded CPM schedules as the primary input. This research advanced under a primary assumption that regardless of whether a contractor utilizes resource loading or not, the contractor will allocate enough daily resources to a scheduled activity so that that activity will be completed within its planned duration. This assumption is captured in a new metric called a Crew Day Resource (CDR). When planned schedule activities overlap in time, trade stacking occurs and the number of CDR’s for that day likewise increases. Schedule density refers to the increasing degree of overlapping activities in a CPM schedule. How that density measure changes from schedule update to update allowed a predictive mathematical model to be created with strong correlation between the schedule density and actual observed labor productivity. Five construction projects were evaluated with emphasis on specific trades including mechanical and electrical work on three high rise buildings, large bore piping on a power plant, and structural steel work on a marine maintenance structure. Results of this research are encouraging and justify expansion of the project sample size, particularly for mechanical and electrical trades in high rise building projects. Additionally, this study provides the basis for development of a project management tool that may alert managers of potential construction labor inefficiencies before they occur.