Abstract
As for the solution approach, you want to calculate the VOI for the problem displayed in our last influence diagram. To do so, we take the following algorithm approach.
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The values you observe could vary due to the simulation error that arises from R’s simple Monte Carlo engine. Simple Monte Carlo can be somewhat “noisy.”
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E.K. Godunova (originator), “Jensen inequality.” In Encyclopedia of Mathematics. http://www.encyclopediaofmath.org/index.php?title=Jensen_inequality&oldid=16975
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Jensen’s inequality, stated as E(f( X ))) ≥ f(E( X )), demonstrates that it is not necessarily the case that the expected value of a function of descriptor variables X is equal to the function of the expected values of its descriptor variables. The equality holds true for linear systems of equations, but usually not for nonlinear ones. Our model has a nonlinearity in it due to the inclusion of the time value of money effects on the cash flow. The skewness in many of the underlying uncertainties compounds the problem of this distortion.
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See, for example, Eric Almquist, John Senior, and Tom Springer, “Three Promises and Perils of Big Data,” Bain Brief, April 8, 2015: “Through 2017, 60% of Big Data projects will fail to go beyond piloting and experimentation and will be abandoned.” Although I can’t prove it here, I suspect that most of these failures occur for the same reasons all projects fail, the most frequent and pernicious one being the failure to properly frame the reason for the project anyway.
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© 2018 Robert D. Brown III
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Brown III, R.D. (2018). Building the Simulation in R. In: Business Case Analysis with R. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-3495-2_15
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DOI: https://doi.org/10.1007/978-1-4842-3495-2_15
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