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ABSTRACTThis article presents a classroom exercise, centered on a simulation that has been used for 4 years in an MBA program to help students develop an understanding of the trade‐offs involved in managing capital assets in the public sector. Though often ignored in business schools, mission is a key criterion that must be considered when managing such assets, and acts as a surrogate for profit. The case presents a rich environment in which the impact of cost reductions (or additional investments) on mission can be quantified, and trade‐offs can be assessed and discussed. It gives students a chance to develop creative ideas for process improvement, and provides sufficient data for them to analyze the impact of their suggestions in a rigorous way.

This article presents a classroom exercise, centered on a simulation that has been used for 4 years in an MBA program to help students develop an understanding of the trade- offs involved in managing capital assets in the public sector. Though often ignored in business schools, mission is a key criterion that must be considered when managing such assets, and acts as a surrogate for profit. The case presents a rich environment in which the impact of cost reductions (or additional investments) on mission can be quantified, and trade-offs can be assessed and discussed. It gives students a chance to develop creative ideas for process improvement, and provides sufficient data for them to analyze the impact of their suggestions in a rigorous way.

The article of record as published may be located at http://dx.doi.org/10.1016/j.cie.2014.04.009 ; Government and not-for-profit organizations measure success in terms of their ability to promote an organizational mission. Complex assets in such organizations are acquired in a budget-allocation process which reflects mission priorities. So, complex assets in such an environment must be managed so that availability of the asset is sufficient to support mission objectives as planned. Bust cost must also be contained within the budget plan, or other mission objectives may suffer. Hence, an objective in such environments is to simultaneously control (1) the risk that percent-availability will fall below a minimum planning threshold x, and control (2) the risk that cost will exceed the planned budget B. This problem is especially difficult because the two risks are negatively correlated. In this paper we examine the bi-criteria risk minimization problem, for an organization in which the departments (domains) of the organization must compete for scarce resources to achieve organization objectives. We develop a model that can be used to assess bi-criteria risk of single-domain proposals, and a ranking-and-selection procedure which can be used to choose between proposals. We then conduct a limited search of solutions which involve linear combinations of the proposals, in order to investigate the potential benefits of 'breaking silos' and 'cooperation' across domains. Results suggest that for complex systems at least, cross-domain solutions are not always superior to single-domain solutions, and that integrated system models are needed to properly evaluate single-domain or cross-domain solutions.

Acquisition Research Case Study ; Disclaimer: The views represented in this report are those of the author and do not reflect the official policy position of the Navy, the Department of Defense, or the Federal Government. ; This case is intended to illustrate key trade-offs in planning the acquisition of a major weapon system. In particular, the impact of logistics and maintenance decisions on life-cycle costs and readiness are examined. The case provides sufficient data to allow a rich discussion of issues and trade-offs?without being overwhelming. The case raises strategic policy issues but provides an analytical framework and data so that the policy issues can be discussed in detail, and not merely with generalities. Logistics and maintenance issues examined within the case include the critical protection (spare-part) levels and reliability of major components, depot and preventive maintenance turnaround times, as well as planning for exogenous factors such as variability in the price of petroleum, oil, and lubricants. By examining a set of related decisions simultaneously, the case allows students to explore the relative leverage of logistics and maintenance decisions on cost and readiness. By examining endogenous as well as exogenous factors, the case allows students to examine the impact of factors within the control of program managers as well the impact of factors beyond their control on budget and readiness risk. The intent of the case is to move beyond planning simple budget and readiness targets and to encourage students to discuss methods of robust contingency planning. Specific learning objectives include an understanding of the life-cycle cost implications of logistics and maintenance decisions an understanding of the readiness implications of logistics and maintenance decisions an understanding of the trade-offs between life-cycle cost and readiness an understanding of the implications of logistics and maintenance factors on readiness risk, and an understanding of the implications of logistics and maintenance factors on budget risk. The development of this case was supported by the Naval Postgraduate School. This case was prepared by Dr. Keebom Kang and Dr. Kenneth Doerr for use in Dr. Kang?s Logistics Engineering class at the Naval Postgraduate School. A teaching note is available for instructors at educational institutions by requesting a copy from Dr. Kang. ; Naval Postgraduate School Acquisition Research Program ; Approved for public release; distribution is unlimited.

Acquisition Research Sponsored Report Series ; Disclaimer: The views represented in this report are those of the author and do not reflect the official policy position of the Navy, the Department of Defense, or the Federal Government. ; Given an acceptable level of military performance, arguably the two most important criteria for weapon systems performance are readiness (operational availability, or Ao) and life cycle cost (LCC). These two criteria are in conflict: one may maximize Ao by increasing LCC or minimize LCC by degrading Ao. In this paper, we develop a model to analyze risk factors associated with this bi-criterion problem. To analyze the impact of input factors on risk, or variance in the outcome criteria, we conduct Monte Carlo simulation. We then apply design of experiments methodologies to identify risk factors by analyzing quantiles of these criteria in which we examine the probability that cost will exceed a certain threshold dollar amount and the probability that readiness falls below a certain threshold. ; Naval Postgraduate School Acquisition Research Program ; Approved for public release; distribution is unlimited.

Prepared for: U.S. Military Entrance Processing Command (USMEPCOM) 2834 Green Bay Road North Chicago, IL 60064-3091 ; The U.S. Military Entrance Processing Command (USMEPCOM) is charged with screening all applicants for enlistment into the U.S. Armed Forces according to the qualification standards of each of the four services. These applicants are screened and processed at one of 65 Military Entrance Processing Stations (MEPS) distributed throughout the United States, to include Alaska, Hawaii, and Puerto Rico. Archived data exists that describes the daily work each site has experienced in the broad categories such of medical, testing, and processing. The workload between stations can vary widely, as certain sites serve areas with denser populations of applicants. The workload at each station also tends to vary according to time of year, as well as time of month. This workload variability at and between MEPS presents unique challenges for deciding on optimal capacity levels. We develop a short list of candidate locations that exhibit particularly high congestion relative to other MEPS and regions. Namely, 7th Battalion in California and 10th Battalion in Florida each contain several MEPS that rank highly with respect to relative congestion. Another regional area with substantial relative congestion includes MEPS from 4th and 12 Battalions. Finally, individual MEPS such an Minneapolis and Columbus exhibit consistent high relative congestion in the medical technician workflow, while Denver and Montgomery exhibit high congestion in the human resources workflow. ; U.S. Military Entrance Procession Command (2USMEPCOM) 834 Green Bay Road, North Chicago, IL 60064-3091 ; Approved for public release; distribution is unlimited.

ABSTRACTThis study examines the effect of training to reduce biases and heuristics on the consequence of judgments. We demonstrate that untrained subjects' judgments may systematically yield better consequences than judgments of subjects trained to reduce biases and heuristics. This result implies that educators should use caution when interpreting the findings of biases and heuristics research. In establishing the existence of situations in which biases and heuristics produce better consequences than an unbiased, or normative procedure, we open the larger question of the need for an elaboration of the prescriptive uses of the normative procedures.