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Project Management Decisions With Uncertain Targets, Jeffrey Keisler, Robert Bordley
Project Management Decisions With Uncertain Targets, Jeffrey Keisler, Robert Bordley
Jeffrey Keisler
Project management decision rules presume that fixed and inflexible targets have been defined for the project. If a project's slack is defined as the difference between actual project performance and these targets, then these decision rules can be characterized as maximizing the probability that slack is non-negative (i.e., maximizing the probability of meeting the targets). These rules rely on z-scores to compare uncertain performance to target levels. Following these decision rules will not always suffice for the project manager to act consistently with customer preferences. In particular, actual requirements may be uncertain or subject to change, and customers may have …
Value Of Information Analysis: The State Of Application. Environment Systems & Decisions, Jeffrey Keisler, Eric Chu, Zachary Collier, Nina Sinatra, Igor Linkov
Value Of Information Analysis: The State Of Application. Environment Systems & Decisions, Jeffrey Keisler, Eric Chu, Zachary Collier, Nina Sinatra, Igor Linkov
Jeffrey Keisler
The value of information (VoI) is a decision analytic method for quantifying the potential benefit of additional information in the face of uncertainty. This paper reviews the prevalence of VoI applications reported in the peer-reviewed literature from the years 1990–2011. We categorize papers’ applications across the types of uncertainties considered, modeling choices, and contexts of social importance (such as health care and environmental science). We obtain and analyze statistics on the range of applications and identify trends and patterns in them, and conclude with an interpretation of what these mean for researchers and practitioners as they pursue new efforts. Key …
Technical Note: Comparative Static Analysis Of Information Value In A Canonical Decision Problem, Jeffrey Keisler
Technical Note: Comparative Static Analysis Of Information Value In A Canonical Decision Problem, Jeffrey Keisler
Jeffrey Keisler
To gain insight into the behavior of the value of information, this paper identifies specific rules for a canonical decision problem: the two-act linear loss decision with normal prior probability distributions. Conditions are derived for which the expected value of perfect information increases when mean and standard deviation are both linear functions of an exogenous variable. A variety of richer decision problems can be adapted to the problem, so that the general results obtained here can be immediately applied to understand drivers of information value.
Allocating Contractor Risks In The Hanford Waste Cleanup, Jeffrey M. Keisler, William A. Buehring, Peter D. Mclaughlin, Mark A. Robershotte, Ronald G. Whitfield
Allocating Contractor Risks In The Hanford Waste Cleanup, Jeffrey M. Keisler, William A. Buehring, Peter D. Mclaughlin, Mark A. Robershotte, Ronald G. Whitfield
Jeffrey Keisler
Organizations may view outsourcing as a way to manage risk. We developed a decision-analytic approach to determine which risks the buyer can share or shift to vendors and which ones it should bear. We found that allocating risks incorrectly could increase costs dramatically. Between 1995 and 1998, we used this approach to develop the request for proposals (RFP) for the US Department of Energy’s (DOE’s) privatization initiative for the Hanford tank waste remediation system (TWRS). In the model, we used an assessment protocol to predict how vendors would react to proposed risk allocations in terms of their actions and their …