Publication:
SHOOT THE HORSE AND BUILD A BETTER BARN DOOR: EXPLORING THE POTENTIAL FOR A SUPERFORECASTING METHODOLOGY TO STRENGTHEN THE DHS LEADERSHIP SELECTION PROCESS

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Authors
Dorman, Ronald
Subjects
superforecasting
leadership
prediction
intuition
accountability
recognition
flow state
closed data loop
heuristics
cognitive bias
judgment
decision making
diversity
crowdsourcing
groupthink
Tversky
Kahneman
Tetlock
homeland security
viewpoint survey
DHS
Advisors
MacKinnon, Douglas J.
Wollman, Lauren
Date of Issue
2018-12
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
Over the course of several years, the Department of Homeland Security (DHS) has worked diligently to improve the quality of its leaders. Such efforts have focused almost exclusively on initiating or expanding programs related to leadership development. To date, the impact of that exertion might be charitably described as tepid. While the issues associated with existing leaders have received ample attention, the selection process that precipitated them has not. This gap represents an opportunity to explore a nascent space and suggest new solutions that target the problem at the source. This thesis examines the process of leadership selection at a network level and finds several systemic problems related to measurement, structure, and decision-making. These problems bear a striking resemblance to those observed in the intelligence community and its ability to accurately predict complex future geopolitical events. One method that has dramatically improved the accuracy of geopolitical predictions is superforecasting. At its core, leadership selection is a prediction or a forecast. It is an educated but nonetheless imperfect best guess about how a candidate observed today will perform tomorrow. These features collectively suggest a novel question. Could DHS use a superforecasting methodology to improve its leadership selection process? This thesis follows the progression of that question to an unexpected destination and offers several concrete recommendations.
Type
Thesis
Description
Department
National Security Affairs (NSA)
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Distribution Statement
Approved for public release; distribution is unlimited.
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