Enlisted Detailing Market Place Analysis and Pilot
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Authors
Gates, William R.
Subjects
Enlisted Detailing
Enlisted Assignment
Retention Marketplace
Market-Based Compensation
Enlisted Assignment
Retention Marketplace
Market-Based Compensation
Advisors
Date of Issue
2019-12
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
The Naval Postgraduate School has conducted extensive research on the enlisted assignment and retention processes within the Navy and across the other services. Research in 2018 updated earlier work on the enlisted assignment and retention processes, including two-sided matching, optimization and the Navy's current auction-based Assignment Incentive Pay program, and developed market-based courses of action (COAs). Implementing these COAs requires collecting, consolidating, mining, and protecting the data needed to implement the detailing marketplace, potentially leveraging machine learning (ML) platforms against manpower data sets, and encoding sailor record data using "blockchain" structure. The command’s value will likely be algorithm-driven, and based on billet requirements compared to sailor training records, performance data, and demographic data. This research effort will examine algorithmic approaches to combining diverse data elements into a single metric by which commands can rank sailors. In addition, to reduce the total cost of voluntarily placing the right sailor in the right billet, this research will examine how concepts from behavioral economics might nudge sailors to accept hard to fill billets, including offering personalized combinations of non-monetary incentives. Our research shows the following: ML algorithms can predict future outcomes by finding statistical patterns in the data unobservable to humans, and help develop a fitness score for each worker-job pair; blockchain technology can provide a secure, reliable, and efficient way to distribute sensitive data, while controlling whom, where, when, and how the data are accessed; the multiple-criteria decision-making literature contains dozens of methods to aggregate individual performance and billet data to rank equivalent classes of sailors for billet-fitness, but none of these methods are well validated; and behavioral economics and non-monetary incentives can nudge sailors to accept hard-to-fill billets.
Type
Report
Description
NPS NRP Executive Summary
Series/Report No
Department
Identifiers
NPS Report Number
Sponsors
N1 - Manpower, Personnel, Training & Education
Funding
This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrp
Chief of Naval Operations (CNO)
Chief of Naval Operations (CNO)
Format
Citation
Distribution Statement
Approved for public release. Distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.