A decision support system framework to improve design-construction integration and project performance on public sector underground utility projects

Abstract

One of the noted difficulties with the traditional public works project development process is the lack of integration and sharing of information between engineering and construction entities that results in a decrease in project performance. To improve project performance on public sector underground utility projects, the research develops a decision support system framework that enhances the exchange and integration of relevant information and knowledge between entities on such projects by incorporating a lessons-learned database to document, organize and disseminate lessons-learned on a project. To identify the critical activities within the project development process that could be linked to the decision support system, the Integration Definition for Functioning Modeling (IDEFO) technique was used to create a representative model of the public works project development process. The resultant model demonstrated the repeatable nature of the process both across project phases and from project-to-project and identified the decision-making activities of generating and evaluating alternatives as key opportunities for construction-related input that could be linked to a decision support system. An inspection of current industry practices was conducted through interviews with knowledgeable industry sources to determine the scope of the decision support system framework. Results revealed the type of critical decisions on underground utility projects that could benefit from construction-related input and identified the documentation of lessons-learned as a major industry weakness. A prototype decision support system incorporating a lessons-learned database was developed and the framework integrated into common project management reporting mechanisms found in the industry. The actual decision-maker can retrieve lessons-learned according to predetermined categories of critical decisions, compare and evaluated retrieved alternatives, and document the rationale behind the ultimate decision made. The framework for the decision support system was evaluated by knowledgeable industry sources and through the use of a hypothetical case study. Evaluations determined the proposed system would improve design and construction integration and project performance on public sector underground utility projects. However, additional research is required into determining both the most suitable lessons-learned database structure and ways to increase the incentive for project participants to fully participate in the methodology.