Abstract

Schedule performance index of earned value method has been reported to generate misleading results at times because of its failure to account for criticality of activities involved, as well as its consideration of monetary values for status reporting. Material can be seen as the fuel needed to execute projects from inception to completion. Material installed provides good indicators of progress achieved onsite vis-a-vis project schedule performance. It correlates well with the role of the schedule performance index (SPI) of the earned value method (EVM). Material is recognized to have a significant impact on achieved progress for physical completion of project activities. This research project is geared towards circumventing the reported limitations of SPI. It presents a study on the development of material status index (MSI) in support of the EVM. Unlike the SPI, the newly developed index accounts for the criticality of project activities. The proposed method is composed of two modules: current status reporting and forecasting. The two modules include selection procedures that allow for engaging only (near) critical activities and by extension materials that impact project duration. Consideration of criticality is carried out via the total float of each activity and percent float (i.e. the ratio of float to activity duration). The MSI current status reporting and also the forecasting module utilize seventy-eight material based factors recognized to cause schedule delays. These factors were reported in a number of studies, primarily the CII 2011 publication on “Global Procurement and Materials Management” and are refined by means of a structured interview with an experienced practitioner in industry. They cover the supply chain material management before material reaches the site, once material is at the gate prior to acceptance and finally onsite. A simulation model is run utilizing users’ judgment on the applicability of these probable causes to the project at hand in the forecasting module. The simulated model serves as input to the forecasting function, which generates probability distribution of forecasted project duration. MSI, can independently and jointly with SPI provide root causes behind problems encountered during project execution. MSI serves to provide added value in alerting management to take corrective actions. A software application is developed to automate the process of MSI method. To validate and demonstrate capabilities of the developed method, it is implemented on two case studies in which the introduced enhancements are clearly portrayed. Forecasting duration and reporting on schedule performance of project using MSI as a supplementary index is more accurate because of its consideration of level of criticality of project activities and capturing actual progress represented by quantity of material installed.