Performance measurement in military operations: information versus incentives

Blanken, Leo J.; Lepore, Jason J.

doi:10.1080/10242694.2014.949548

Cited by 4 publications

(1 citation statement)

References 31 publications

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“…Commanders may examine battlefield outcomes and feedback from subordinates to make personnel decisions. Commanders often use some metric of combat outcomes to determine whether subordinates are performing adequately (Blanken and Lepore, 2014; Gartner, 1997; Gartner and Myers, 1995). These metrics may contain limited information, leaving commanders relatively uncertain as to how individual subordinates contributed to the outcome; or they may contain so much information that commanders are overwhelmed (see Murray, 2011).…”

Section: Introductionmentioning

confidence: 99%

Organizing evaluation: Assessing combat leadership quality

Wagstaff¹

2019

Journal of Theoretical Politics

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What determines military effectiveness? Previous literature has examined factors such as military doctrine, culture, and capabilities, as well as regime type and civil–military relations, but has largely ignored military leadership quality. Competent military leaders positively influence battle outcomes by ensuring proper implementation of battleplans and quick reaction to an increasingly dynamic battlefield. This paper formally models the relationship between high-ranking military commanders and their immediate subordinates to examine the commander’s ability to evaluate her personnel. I vary the ability of the subordinates to signal their commander to determine how different signaling structures influence what commanders may learn. This analysis reveals that commanders opt for less informative signals from subordinates as the military professionalizes, potentially impeding their ability to identify and remove incompetent subordinates. Leaving incompetent subordinates in command reduces the ability of the military to improve. Evidence from the US Army’s leadership decisions after the Battle of Kasserine Pass and Operation Avalanche illustrates these results.

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Section: Introductionmentioning

confidence: 99%