Using artificial neural networks (ANN) in projects monitoring dashboards’ formulation

Abstract

It has been reported via several researches that the sponsorship involvement is a major factor influencing project success. These projects which may vary in their benefits, types, sizes, and complexity levels; generate some sort of difficulty for many government organizations managing hundreds of projects in selecting projects to be monitored. The initial selection of those projects which are being monitored through organization’s dashboards is usually drafted via some criteria that comprise a meaningful group (s) to the top management; and then this selection is altered by forcing few projects in and out. This study aim is to replace the initial existing manual selection process by an intelligent model. The proposed model is based on ANN (Artificial Neural Networks) that uses the databases of more than 300 projects out of which are 48 projects that were actually selected to be in the top management monitoring dashboards. The ANN model was built and tested for accuracy via examining the deviation between the model results and the actual selection. The test results showed acceptable confidence level in the model results where accuracy was proven to be initially accepted. The ANN model is expected to evolve and gains more maturity by including more projects that will be introduced in the coming years plans.