Enlisted Personnel Allocation System (EPAS) Enhancements to the Recruit Quota System (REQUEST) - A Simulation Evaluation

Sticha, Paul J.; Diaz, Tirso; Greenston, Peter M.; McWhite, Peter B

doi:10.21236/ada474853

Cited by 2 publications

(6 citation statements)

References 3 publications

(5 reference statements)

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“…EPAS uses supply groups (SGs) as a surrogate for individuals in the assignment process. 2 Although the version of the EPAS optimization used in the EPAS field test (Sticha, Diaz, Greenston, McWhite, 2007) allowed for a greater number of supply groups (SGs) than previous versions, no attempt to increase the number of SGs or to change their definition had been made. The EPAS Functional Description (FD; Greenston et al, 2001) described the methodology that was used to define the 150 SGs used in the field test.…”

Section: Defining Epas Supply Groupsmentioning

confidence: 99%

“…In the EPAS field test, Sticha et al (2007) made several recommendations regarding changes to the SGs that might lead to improved fidelity of EPAS allocations. Specifically, they recommended that different clustering methods be considered for TSCs 3B and 4 than are used for TSC 1-3A.…”

Section: Defining Epas Supply Groupsmentioning

confidence: 99%

“…• Input files used in the EPAS Field Test (Sticha, Diaz, Greenston, & McWhite, 2007). In many cases the relevant input data were unchanged from the values used in the EPAS Field Test, particularly for index files, which primarily contain element names and configuration information (e.g., the number of contract months).…”

Section: Defining Epas Input Files Based On Fy 2009 Requirementsmentioning

confidence: 99%

“…The first three of these constraints were also used in the EPAS Field Test (Sticha et al, 2007). In addition, the field test included a constraint regarding high-priority MOS, because the ability of EPAS to meet the accession requirements for these MOS was a major concern in the evaluation.…”

Section: Constraintsmentioning

confidence: 99%

“…At the beginning of the project, the EPAS server, which had been used for the field test (Sticha, Diaz, Greenston, McWhite, 2007), did not run because of problems with the primary system disk drive. Our first activities for this project were to procure a replacement to the server and to recover the information that was contained in the original server.…”

Section: Appendix a Restoration / Specifications For Epas Servermentioning

confidence: 99%

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Non-Cognitive Predictors and TSC 3B Market Expansion: Examining MOS Impacts

Sticha¹,

Dias²,

Weaver³

et al. 2011

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ARI has been investigating the potential that non-cognitive predictors could play in expanding the supply of highly-motivated AFQT test score category (TSC) 3B applicants. The initial research effort was known as the Expanded Enlistment Eligibility Metrics (EEEM) project, and preliminary results were encouraging: non-cognitive predictors have been tested that appear to identify a subset of TSC 3B applicants with predicted attrition (and possibly job performance) comparable to that of TSC 1-3A applicants. One concern regarding the implementation of these new predictors is whether an increase in TSC 3B applicants and a corresponding decrease in TSC 1-3A applicants would have repercussions for Army MOS TSC 1-3A goals. The objective of this effort is to estimate the effect of illustrative increases in the number of TSC 3B applicants on the allocation of applicants to their initial MOS training. The objectives were addressed with application of the Enlisted Personnel Allocation System (EPAS) model, designed to simulate the allocation / classification process. 15. SUBJECT TERMS enlisted selection and classification, Enlisted Personnel Allocation System (EPAS), non-cognitive predictors, Soldier Quality Accession Goals SECURITY CLASSIFICATION OF 19. LIMITATION OF ABSTRACT 20. NUMBER OF PAGES

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Section: Defining Epas Supply Groupsmentioning

confidence: 99%

Section: Defining Epas Supply Groupsmentioning

confidence: 99%

Section: Defining Epas Input Files Based On Fy 2009 Requirementsmentioning

confidence: 99%

Section: Constraintsmentioning

confidence: 99%

Section: Appendix a Restoration / Specifications For Epas Servermentioning

confidence: 99%

See 3 more Smart Citations

Non-Cognitive Predictors and TSC 3B Market Expansion: Examining MOS Impacts

Sticha¹,

Dias²,

Weaver³

et al. 2011

Self Cite

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Determinants of the Army Applicant Job Choice Decision and the Development of a Decision Support Tool for the Enlistment Incentive Review Board

Diaz¹,

Sticha²,

Hogan³

et al. 2012

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The Army offers a variety of enlistment incentives to encourage applicants to choose Military Occupational Specialties (MOS) where the need is greatest. MOS incentive types, levels, amounts, and qualification criteria are determined by the Enlistment Incentive Review Board (EIRB). To help the EIRB effectively and efficiently perform this function, this research reviewed current incentive policy decision making process and tools, estimated a Job Choice Model (JCM) based on actual applicant choice data from the Army's Recruit Quota System (REQUEST) for the first and second quarters of FY 2010, and developed a proof-of-concept Decision Support Tool (DST) based on the JCM for predicting the number of enlistments by MOS and Term of Service (TOS) and associated cost given a user-defined policy scenario. The effects of incentives on applicant enlistment choices estimated by the JCM were intuitive for simple policy changes and more difficult to anticipate for more complex policy changes. The benefit of the JCM is that effects of policy changes on MOS fill and budget can be quantified objectively. The proof-of-concept DST demonstrated the value of a tool for informing the EIRB in allocating incentives to MOS and TOS enlistment options that can provide the most benefit to the Army. 15. SUBJECT TERMS Enlistment Incentive Review Board, Army enlistment incentives, discrete choice modeling, job choice modeling and simulation, Army classification SECURITY CLASSIFICATION OF 19.

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Enlisted Personnel Allocation System (EPAS) Enhancements to the Recruit Quota System (REQUEST) - A Simulation Evaluation

Cited by 2 publications

References 3 publications

Non-Cognitive Predictors and TSC 3B Market Expansion: Examining MOS Impacts

Non-Cognitive Predictors and TSC 3B Market Expansion: Examining MOS Impacts

Determinants of the Army Applicant Job Choice Decision and the Development of a Decision Support Tool for the Enlistment Incentive Review Board

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