Decision support system for project cost control strategy and planning
Abstract
In the existing methods of cost control, control is determined only after a line item has faced a cost escalation. That is, efforts are made to identify and control the symptoms rather than making efforts to identify and control the cause. The existing methods of cost control do not consider at a macro level the influence of many important attributes such as waste, project management practices, change orders, and error/rework on the line items and thus on the project cost. Furthermore, existing methods of cost control do not assist management in developing a cost control strategy to minimize the cost impact of all such attributes; a strategy which would entail controlling a set of attributes to minimize the probable project cost escalation. To help management in this aspect a prototype Decision Support System (DSS) called COMPASS (COst Management PlAnning Support System) has been developed. This computerized Decision Support System assists management, before and after the project has started, in identifying attributes which might cause potential project cost escalation and in formulating a project cost control strategy. The attributes identified on the cost control strategy, if controlled, would minimize the expected loss (i.e., project cost escalation). To evaluate the probable cost escalation in the new project and to formulate a cost control strategy, the system allows the constructors to utilize their experience and past project performance data. The method presented in this thesis not only assists management in identifying potential risk attributes before the project has started, but it also assists in computing the active state probability of risk attributes and the cost escalation associated with them. The COMPASS methodology provides the user with six main outputs with respect to a new project: (1) identification of potential risk attributes, (2) the active state probability of attributes, (3) probability of project cost escalation, (4) the cost influence due to the active state of attributes, (5) the probable project cost escalation, and (6) the project cost control strategy.
Degree
Ph.D.
Advisors
Halpin, Purdue University.
Subject Area
Civil engineering
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