Today's typical probabilistic cost analysis assumes an "ideal" project that is devoid of the human and organizational considerations that heavily influence the success and cost of real-world projects. In the real world "Money Allocated Is Money Spent" (MAIMS principle); cost underruns are rarely available to protect against cost overruns while task overruns are passed on to the total project cost. Realistic cost estimates therefore require a modified probabilistic cost analysis that simultaneously models the cost management strategy including budget allocation. Psychological influences such as overconfidence in assessing uncertainties and dependencies among cost elements and risks are other important considerations that are generally not addressed. It should then be no surprise that actual project costs often exceed the initial estimates and are delivered late and/or with a reduced scope. This paper presents a practical probabilistic cost analysis model that incorporates recent findings in human behavior and judgment under uncertainty, dependencies among cost elements, the MAIMS principle, and project management practices. Uncertain cost elements are elicited from experts using the direct fractile assessment method and fitted with three-parameter Weibull distributions. The full correlation matrix is specified in terms of two parameters that characterize correlations among cost elements in the same and in different subsystems. The analysis is readily implemented using standard Monte Carlo simulation tools such as @Risk and Crystal Ball. The analysis of a representative design and engineering project substantiates that today's typical probabilistic cost analysis is likely to severely underestimate project cost for probability of success values of importance to contractors and procuring activities. The proposed approach provides a framework for developing a viable cost management strategy for allocating baseline budgets and contingencies. Given the scope and magnitude of the cost-overrun problem, the benefits are likely to be significant.
The environment that engineers encounter upon graduation has changed dramatically in recent years, with technical skills being necessary but no longer sufficient for today's conditions. Industry practitioners, followed closely by deans of engineering schools and by ABET, have identified nontechnical skills that are of paramount importance for engineering graduates. Chief among these is the ability to work in interdisciplinary teams.Given the historical lack of emphasis that engineering schools have placed on creating and improving team skills in students, it is natural that industry practitioners have created their own practices aimed at creating and improving those skills. In this paper, we report some of the practices identified in interviews with industry practitioners, and discuss the feasibility of transferring and implications for utilizing such practices in academic settings. Interviews & IntervieweesPractitioners with extensive experience supervising engineers working in teams were identified through our Industrial Advisory Board members, through faculty members, through conference contacts, and through contacting targeted organizations and asking for a person with such experience. By this method, we were able to interview practitioners in manufacturing, service, transportation and government organizations. Interviewees hailed from relatively small manufacturing organizations (approximately $6 million in annual sales), to some of the largest and well known (UPS, FEDEX), and most respected engineering companies (e.g.
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