Development of a Project Management Evaluation Model for the Construction Industry in Kenya

Abstract

There is a problem in the construction industry in Kenya in terms of ineffective monitoring and evaluation of construction projects. Previous researchers have argued for different approaches to the way activities in the construction industry should be treated for efficiency to be realized in the of construction projects. However, none of these researchers has undertaken an exhaustive and eclectic modeling of project management evaluation as a solution to the challenges facing the construction industry. Low efficiency and effectiveness in terms of frequent delays, cost overruns, deficient quality and inadequate safety are still serious challenges to the construction process and execution of projects in Kenya. These challenges could be addressed by use of models. This study therefore, addresses the challenges by developing a project management evaluation model for a more effective and efficient construction industry in Kenya.

From review of the related literature, three key observations were made regarding the practice of project evaluation. Firstly, projects should ideally produce project health reports with leading performance measures, instead of producing project autopsy reports with lagging performance measures. However, most of the existing project management models emphasize the use of lagging measures of project performance. Secondly, the models do not emphasize continual assessment of the project performance from the very onset of the project execution. Finally, the models do not pay attention to needs of the clients as initiators of the project. These practices render the project management function rather inefficient in the delivery of construction projects. For that reason, this research study was undertaken.

A multi-strategy research approach involving a survey research design was adopted to actualize the research objectives. A sample size of 580 members was selected, out of which 344 member were responsive. The variables in the study and their relationships were conceptualized from literature review. They comprise the traditional measures of project cost, project quality and project time, and were observed to account for only 57% of projects’ performance. Consequently, another set of three variables - human resource management, scope management, and project performance management - was added, and was observed to account for 42% of the performance of projects. The data analysis procedures adopted were: statistical descriptives, frequencies, correlation analysis, principal component analysis (PCA), analysis of variance (ANOVA) and multiple regression analysis. They were done using the Statistical Program for Social Sciences (SPSS for Windows, Version 20).

From the data analysis results, a project evaluation model was synthesized and validated. In the model, 82% of a project’s performance is attributed to consultants and contractors together, while 18% of the performance is attributed to clients, making e a total of 100%. The project evaluation model is stated as follows: -

Pe = 82% PMECs&Cr + 18% PMECt + e

Where:-

Pe is the overall project execution efficiency.

PMECs&Cr is the consultant and contractor contribution component.

PMECt is the Client’s contribution to project performance.

e is an error which is a function of the operating environment, political situation and any other external factors that can influence the project.

The model was reduced to a software model which is can predict performance of a project within an error margin of 0.5%. It received an acceptance rating of 88% from the field.

The model can be applied to any project situation irrespective of procurement method used, and it encourages measurements to be done using a shared perspective between a client and his project team, regarding the performance of a project. It also encourages coordination between the client, consultants and contractors, with elimination of conflicts amongst them. Use of the model should make monitoring and evaluation of construction projects, which have hitherto been rather elusive in the construction industry in Kenya, to be more proactive and effective.

Finally, it is concluded that continual project evaluation during the project execution process improves project performance, and recommended that the project management evaluation model developed in this study be adopted in the mainstream construction industry in Kenya, to foster delivery of construction projects.