Developing a Standard Update Process for the Army's Annual MOS Availability Factors (AMAFs)
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This report describes research conducted to develop a standard methodology for updating the U.S. Army’s Annual Military Occupational Specialty (MOS) Availability Factors (AMAFs). An AMAF specifies the amount of direct and indirect productive time (over the course of a year) that a soldier has available to perform MOS duties. Traditionally, the Army has calculated AMAFs by measuring soldiers’ non-available hours per day, treating the remainder of the 24 hours as available time, and annualizing that available time figure. Largely through field data collection, the Army identified specific “non-availability factors” — that is, the non-MOS-related activities that comprise non-available time — and measured how much time soldiers allocate to each of those activities. Because the process is costly and time-consuming, however, regular AMAF updates have not been feasible. Through a combination of literature reviews and interviews, we examined other military services’ and commercial firms’ approaches to manpower availability, as well as advantages and disadvantages of various data-collection approaches. This process helped us generate an alternative methodology that may allow more regular AMAF updates — and ultimately yield more accurate calculations of manpower requirements. This document synthesizes the relevant information we gathered and presents the approach generated on the basis of that information. The proposed “3-Gate” approach entails beginning with quick, low-cost, low-rigor data collection and moving sequentially to a moderate-speed/cost/rigor method — and then perhaps to a slower, high-cost, high-rigor method — if certain “triggers” indicate it is necessary to do so.
Table of Contents
Background on AMAFs and Purpose of Study
Lessons on Estimating Non-Available Time from Other Services and Commercial Firms
General Methods for More Adaptive, Lower-Cost AMAF Estimation
Guidelines and Specifications for Collecting Data
Appropriate Metrics and Formalizing Estimates
Sample Size Calculation for Web Survey
Research conducted by
The research described in this report was sponsored by the United States Army and conducted by the RAND Arroyo Center.
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