Lone Star White Paper on “Modeling the Randomness of Humans” Explains The Accuracy of Predictive Models

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Integrating the real-world factors that affect performance variation. In the past, accommodating the randomness of human performance and behavior has often seemed to be an insurmountable challenge.

We have found that impressive models can be constructed with limited data, or with data of limited fidelity.

Dallas, TX -- Lone Star, internationally recognized in decision analysis and business modeling, has overcome the challenge of modeling human-based sources of uncertainty by understanding and integrating the real-world factors that affect performance variation. Accurate models in economics, learning, productivity, error rate estimation and decision-making require integrating the variability of human performance. In the past, accommodating the randomness of human performance and behavior has often seemed to be an insurmountable challenge.

Lone Star’s experience shows human sources of uncertainty need not pose a serious challenge to creating accurate predictive models. As a provider of analysis and advisory services addressing highly complex client issues and problems, Lone Star has just released “Modeling the Randomness of Humans” a white paper detailing its approach to developing models that predict the performance of human organizations with a high level of accuracy.

The paper describes the developing understanding of human performance and variability, presented using illustrations from corporate operations, economics and sports, including the emerging field of sabermetrics. Late 20th century professional sports employed statisticians and inspired a number of amateur number crunchers.

Steve Roemerman, CEO of Lone Star noted, “Since humans are bandwidth limited, the data describing their span of behavior is also limited. We have found that impressive models can be constructed with limited data, or with data of limited fidelity. This was made easier when groups are modeled and even easier yet when organizations with norms and rules are modeled.”

Using these principles, Lone Star has predicted the performance of human organizations with surprising accuracy. In practice, it was found that the messy randomness of human institutions can be modeled with as much fidelity as most other modeling domains. Lone Star can do this because its modeling and simulation tools, TruNavigator, StraTable, and IRIS have accommodated for human variability.

About Lone Star
Lone Star, internationally recognized for its decision analysis and business modeling, is headquartered in Dallas, Texas. Lone Star provides business and technical analysis and advisory services that address a client’s most complex, mission critical challenges. Lone Star has built a strong reputation with its clients for delivering insightful analysis, advice and support that leads to improved operational performance, monetary savings and risk reduction. Lone Star’s roots lie in the development, fielding and support of complex technologies and programs for the Department of Defense and commercial enterprises in the telecommunications and technology markets.

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Matthew Bowers
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