Minimising engineering delivery cycle time variability on similar projects: An Eskom Case Study

Abstract

Eskom Generation is experiencing high levels of cycle times variabilities on the delivery of similar engineering deliverables within similar project phases and similar plant areas across different power stations. These variabilities of cycle times deprive Eskom power stations the benefit of effective utilisation of information from previous and current similar projects for the purpose of similar projects schedules estimations and reduction of similar projects engineering deliverables delivery risk. This research investigates factors contributing to cycle time variability on similar engineering deliverables focusing on the impact of variability of both activities and activities durations for similar engineering deliverables, application of engineering processes and, intra-organisational knowledge transfer on cycle time variability. The ultimate deliverable of the research is the framework model for minimising cycle time variability on similar projects. The research is a progressive development of the framework model for minimising cycle time variability on similar projects in which the initial conceptual framework is further developed and updated as the research progresses up to the development of the framework model. Both primary and secondary data were used for the research. The primary data was obtained by means of questionnaire surveys consisting of 20 different questions while the secondary data was obtained from a combination of sampled power stations’ projects schedules with similar engineering deliverables. The research revealed that inconsistent and inadequete intra-organisational knowledge transfer, inconsistent application of engineering processes, variability of activities, and variability of activities durations result in increased project cycle time variability. Evidence of the mediation role played by both variability of activities and variability of activities duration on (1) intra-organisational knowledge transfer and cycle time variability and (2) application of engineering processes and cycle time variability was observed. Consistent knowledge transfer and consistent utilisation of engineering processes were identified as the leading variables while clearly defined consistent activities and consistent activities durations were identified as the lagging variables for minimising cycle time variability. The research is concluded by the development of a framework model for minimising cycle time variability for similar engineering deliverables. The model can serve as a building block for minimising cycle time variability for similar projects in related industries and academic research.