The Effectiveness of the IpOp Model Decision Tree to Calibrate Projects at the Pre-Project Stage
by Nadina Muller, Mark Moses, Raphaël H. Cohen
Abstract: Literature supports the idea that projects delivering the target objective on time and within the anticipated budget represent less than 30% of all projects. Even though failure advances the learning curve, this low success rate equals a vast waste of resources. Based on practical experience, the authors hypothesise that: 1) low project success rates are linked to inadequate project selection methodologies or their inconsistent application; 2) the IpOp model decision tree could improve the selection of worthy projects. An online survey was carried out to determine: 1) project success rate; 2) links between project performance and selection parameters. Results show the importance of rigour in project selection in order to reduce waste of resources, while no clear correlation between the number of selection criteria could be proven. Further, the results indicate that practitioners consider the IpOp model decision tree to evaluate projects at pre-project stage an improvement over current practice.
Keywords: pre-project calibration; project success; project selection criteria; decision tree; target objectives; resource savings; online survey; IpOp model; allocation of resources; project governance.
DOI: 10.1504/IJBG.2020.10038787
https://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=IJBG
