Download Measures of Effectiveness for the Information-Age Army by Richard Darilek, Walter Perry, Jerome Bracken, John Gordon, PDF

By Richard Darilek, Walter Perry, Jerome Bracken, John Gordon, Brian Nichiporuk

The 90s have witnessed the start of what destiny historians could name the knowledge Age. whereas it really is transparent that info can have a far-reaching influence on a bunch of activities--including warfare--how to quantify and degree that influence is much less transparent. the certainty of ways to take action is critical to the military, really at a time whilst it really is spending a large amount of its scarce funding capital to set up Information-Age hyperlinks throughout its forces. because it transforms itself, the military wishes analytic instruments to aid make the simplest offerings attainable. leader between those instruments are sturdy measures of effectiveness (MOEs) which could show the worth of knowledge by way of army results. This record experiences on a small set of Information-Age MOEs constructed in an try and spark the production of many extra such measures. This study demonstrates that improvement of MOEs is possible, not just for wrestle operations yet for balance operations to boot.

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THE LANCHESTER MIXED LAW We now consider adapting the Lanchester laws to account for knowledge. One approach is to consider knowledge to be a subcomponent of the unit’s effectiveness score, M or N, so that M = P(d)P(k|d), where P(d) is the probability that a target will be detected (knowledge) and k is the effectiveness of the weapon system selected to engage the target. In this construct, we take P(d) to be a measure of local knowledge, that is, knowledge of the enemy obtained from sources organic to the unit.

Rewriting the above equation with t = T and solving for b(T), we get b(T )2 = B 2 − Ncr 2 R > 0. Mcb Solving the inequality, we get 2 Mcb  R  >  . Ncr  B  Although this is clearly a square law representation in this form, we can make some interesting observations by examining the nature of the Red and Blue encounters. First we observe that information has a greater effect than the effectiveness scores, in that the encounter values are not fractions, but rather numbers of units. More interesting, however, are the results obtained by examining some extreme values for c r and c b.

18 Measures of Effectiveness for the Information-Age Army This generates the following bounds on Γ: 1+ β 1 ≤ Γ ≤1+ . KR KR A similar calculation can be made to assess the bounds on Γ for Red information dominance. Therefore, given a requisite knowledge gap for information dominance, we can specify conditions on relative knowledge that must be met to ensure that dominance is maintained. Thus we infer a relationship between information superiority and information dominance. It seems logical to discuss information dominance occurring at some point where one or both sides have knowledge that exceeds some threshold.

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