The Benchmark Separation Projection Method for Predicting Monthly Losses of Air Force Enlisted Personnel PDF Download
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Author: C. Peter Rydell Publisher: ISBN: Category : United States Languages : en Pages : 136
Book Description
RAND is helping to design an Enlisted Force Management System (EFMS) for the Air Force. The efms is a decision support system designed to assist managers of the enlisted force in setting and meeting force targets. The system contains computer models that project the force resulting from given management actions, so actions that meet targets can be found. Some of those models analyze separate job specialties (disaggregate models) and others analyze the total enlisted force across all specialties (aggregate models); some models make annual projections (middle-term models) and others monthly projections. The Short-Term Aggregate Inventory Projection Model (SAM) is the component of the EFMS that makes monthly projections (for the rest of the current fiscal year) of the aggregate enlisted force.
Author: C. Peter Rydell Publisher: ISBN: Category : United States Languages : en Pages : 136
Book Description
RAND is helping to design an Enlisted Force Management System (EFMS) for the Air Force. The efms is a decision support system designed to assist managers of the enlisted force in setting and meeting force targets. The system contains computer models that project the force resulting from given management actions, so actions that meet targets can be found. Some of those models analyze separate job specialties (disaggregate models) and others analyze the total enlisted force across all specialties (aggregate models); some models make annual projections (middle-term models) and others monthly projections. The Short-Term Aggregate Inventory Projection Model (SAM) is the component of the EFMS that makes monthly projections (for the rest of the current fiscal year) of the aggregate enlisted force.
Author: Michael P. Murray Publisher: ISBN: Category : Languages : en Pages : 84
Book Description
This Note describes procedures for updating the middle-term loss equations that will be used in the Air Force's Enlisted Force Management System (EFMS). Updating involves four activities: (1) adding data to the files used to estimate the equations; (2) reestimating the existing specifications of the equations; (3) exploring possible respecifications of the equations to exploit additional data or to accommodate new EFMS needs; and (4) testing and evaluating new versions of the equations intended for use in the EFMS. This document concentrates on the first three activities. The fourth is treated in N-2688.
Author: David Schulker Publisher: ISBN: 9781977407474 Category : Business & Economics Languages : en Pages : 0
Book Description
RAND Project Air Force was tasked with developing a new capability for planners: a retention early warning system (REWS) that alerts policymakers when a subgroup of U.S. Air Force (USAF) military members is at risk for future shortages. The goal of the research project was to develop a forecasting model for retention, operationalized within a prototype decision-support application, that can alert decisionmakers to emerging problems and thus allow them enough time to consider adjusting accession and retention policies before shortages occur. The authors' overall approach to designing the system drew on widely used paradigms for solving data science problems. These paradigms emphasize understanding the business problem, drawing on a wide array of data sources and types, testing several flexible prediction approaches to optimize performance, and operationalizing the information for decisionmaking. To gain an understanding of the data sources that would be desirable for this application, the authors performed an extensive review of the turnover literature and identified gaps in existing USAF data collection efforts.
Author: Albert A. Robbert Publisher: ISBN: 9781977408600 Category : Business & Economics Languages : en Pages : 0
Book Description
Over the past ten years, maintenance career fields in the U.S. Air Force have been negatively affected by a series of events that have resulted in an experience shortage. Although there has been an improvement in Total Force manning since 2015, several skill levels are still experiencing shortages. To bridge the experience shortfall, the U.S. Government Accountability Office called for an Air Force retention strategy tailored to retain experienced maintainers. The RAND Corporation was asked to explore whether individual characteristics, economic and geographic factors, and the new Blended Retirement System (BRS) could provide additional insights into what predicts retention of this workforce. This report focuses primarily on aircraft maintenance career fields, with some attention to munitions and logistics career fields as resources permitted. The authors undertake two analytic approaches to examine the underlying determinants of retention. First, they use logistic regression to determine how strongly a variety of individual and environmental characteristics are associated with decisions to reenlist, extend an enlistment, or separate from the Air Force; second, they use RAND's Dynamic Retention Model to estimate how the new BRS will affect maintenance, munitions, and logistics career fields when those in the new system reach retention decision points. The authors find that changes in individual characteristics and environmental variables have improved retention in the maintenance, munitions, and logistics career fields. Although much of what influences retention is beyond the Air Force's control, the authors offer a number of recommendations and identify areas of emphasis that could be exploited.
Author: C. Peter Rydell
Author: C. Peter Rydell
Author: C. Peter Rydell
Author: Marygail K. Brauner
Author: United States. Congress. Senate. Committee on the Judiciary
Author: Rand Corporation
Author: 
Author: 
Author: Michael P. Murray
Author: David Schulker
Author: Albert A. Robbert