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Risk Management


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AIE Analysis of the Desktop Replacement Policy

Applied Information Economics can be used to compute the value of this analysis with standard, proven methods. The most conservative application of this approach assumes that only the decision to change the desktop replacement policy was a direct function of the AIE analysis. The expected Net Present Value (NPV) of the recommended policy changes is $12.8 million over 7 years. Since this AIE analysis project cost was under $100,000 including EPA staff time, then the payback is at least 128:1. This also excludes the potential benefits of the improved metrics and risk mitigation strategies resulting from the AIE analysis. The cost of the AIE analysis was less than 1% of the investment analyzed, well within typical AIE cost guidelines.

Applied Information Economics:A New Method for Quantifying IT Value

Applied Information Economics (AIE) is a powerful new method for quantifying the value of IT investments. This overview document of AIE is targeted toward executives who make decisions about approving IT projects. The issues covered are the nature of the current IT decision problem, how AIE solves them and how AIE is different from other methods.

Case Study of the Applied Information Economics Methodology for an Infrastructure IT Investment

Federal executive agencies face significant management and technical challenges when measuring the contribution of information technology investments to mission results as required by the Clinger-Cohen Act. There is a shortage of knowledge and examples of how to measure IT’s contribution to mission results for government agencies with complex missions such as providing for the health and welfare of the citizens of the United States.

Problems with Scoring Methods and Ordinal Scales in Risk Management

Common scoring methods currently used to assess risk in a variety of different domains.

Pushing the Boundary

This volume takes a pragmatic approach to decision-making in states of the world characterized by risk and uncertainty. It starts with a pragmatic defi nition of risk as a state of uncertainty where some of the possibilities involve undesirable outcomes. At fi rst blush it would appear to be very diffi cult, if not to say impossible, to tackle the challenges caused by such uncertainty. However, it is the explicit purpose of this volume to push the boundary and provide practical guidelines for risk management under high doses of uncertainty. Here are five insights for implementation.


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