Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Forecasting Officer Losses PDF full book. Access full book title Forecasting Officer Losses by T. M. Beatty. Download full books in PDF and EPUB format.
Author: T. M. Beatty Publisher: ISBN: Category : Employee retention Languages : en Pages : 21
Book Description
Air Force Personnel Managers must be able to accurately forecast the force size. This need is explicit in meeting statutory budget limitations. Further officer losses drive accession, training, and promotion, thus the need for accuracy in forecasting losses cannot be over emphasized. To accomplish this objective loss rates have been generated using Ordinary Least Squares (OLS) stepwise regression. The objective of this paper is to expose the relative efficacies of alternative methods which could be used viz. Maximum Likelihood Estimation (MLE) and OLS standardized coefficient (Beta) predictor models. (Author).
Author: T. M. Beatty Publisher: ISBN: Category : Employee retention Languages : en Pages : 21
Book Description
Air Force Personnel Managers must be able to accurately forecast the force size. This need is explicit in meeting statutory budget limitations. Further officer losses drive accession, training, and promotion, thus the need for accuracy in forecasting losses cannot be over emphasized. To accomplish this objective loss rates have been generated using Ordinary Least Squares (OLS) stepwise regression. The objective of this paper is to expose the relative efficacies of alternative methods which could be used viz. Maximum Likelihood Estimation (MLE) and OLS standardized coefficient (Beta) predictor models. (Author).
Author: Barry Siegel Publisher: ISBN: Category : Languages : en Pages : 21
Book Description
The officer retention forecast model (ORFM) is an integrated set of time-series and econometric models that produce loss rate forecasts for the structured accession planning system for officers (STRAP-O). Loss rate forecasts are generated over a 7-year horizon. The manager has the capability to alter these forecasts through a change in the real value of military pay or through the selection of the forecasting technique. This report describes the structure of ORFM and illustrates its capabilities. (Author).
Author: Publisher: ISBN: Category : Time-series analysis Languages : en Pages : 83
Book Description
Accurate prediction of officer loss behavior is essential for the planning of personnel policies and executing the U.S. Army's Officer Personnel Management System (OPMS). Inaccurate predictions of officer strength affect the number of personnel authorizations, the Army's budget, and the necessary number of accessions. Imbalances of officer strength in the basic branches affect the Army's combat readiness as a whole. Captains and majors comprise a critical management population in the United States Army's officer corps. This thesis analyzes U.S. Army officer loss rates for captains and majors and evaluates the fit of several time series models. The results from this thesis validate the time series forecasting technique currently used by the Army G-1, Winters-method additive.
Author: Michael C. Campbell Publisher: ISBN: Category : Employee retention Languages : en Pages : 0
Book Description
The key to effective military personnel planning is accurate loss forecasting. Accurate estimates of future losses enable personnel managers to determine the number of individuals to recruit and promote, as well as the size and cost of future personnel inventories. The thesis describes the generation and analysis of several simple loss rate forecasting models. The models are divided into two classes, those that incorporate eligibility data and those that do not. Aviation officers, particularly pilots, were narrowed down to Lieutenants with four to nine years of commissioned service. They were divided into three communities (jet, prop, and helo). Two methods of loss forecasting were used, BI which is somewhat akin to OP-01s technique and the method I wish to exploit, EAOS. EAOS techniques appear to contribute more to officer loss forecasting than the BI technique. However, BI techniques are still significant but to a lesser degree. The findings are discussed within the context of the study.
Author: edward S. Bres Publisher: ISBN: Category : Languages : en Pages : 21
Book Description
Several time-series-based forecasting techniques were used to project Navy unrestricted line officer loss rates, by grade and length of service category. An autoregressive minimum absolute error regression model was selected as the overall best technique, producing a substantial increase in forecasting accuracy over previously used techniques. (Author).
Author: U.S. Army War College Publisher: Lulu.com ISBN: 0359235743 Category : Reference Languages : en Pages : 552
Book Description
This text explains and synthesizes the functioning and relationships of numerous Defense, Joint, and Army organizations, systems, and processes involved in the development and sustainment of trained and ready forces for the Combatant Commanders. It is designed to be used by the faculty and students at the U.S. Army War College (as well as other training and educational institutions) as they improve their knowledge and understanding of "How the Army Runs." We are proud of the value that senior commanders and staffs place in this text and are pleased to continue to provide this reference.
Author: Anita U. Hattiangadi Publisher: ISBN: Category : Military planning Languages : en Pages : 177
Book Description
The Marine Corps' manpower costs are almost 60 percent of its annual budget. The Enlisted and Officer Strength Planners must develop plans, by paygrade and month, to meet endstrength requirements in the budget execution year and out-years (6 years into the future). To develop these plans, the planners must forecast endstrength losses and gains. This study focuses on doing this accurately. Inaccuracy results in finishing either the year above the congressionally mandated endstrength target (overspending the budget) or below the endstrength target (which has operational consequences). Previously, there was no institutionalized and documented methodology for forecasting losses and no systematic attempt to improve existing techniques. New planners relied on information gleaned during overlap with their predecessors and sometimes developed their own methods (which were susceptible to errors). They had few reference tools and no capability to run loss scenarios. We first assessed the existing loss forecasting processes. Then, we made the processes more systematic. Next, we improved/added to the loss forecasting model and created reference tools. Finally, we documented the entire process in detail. We recommend creating an SSN-based file, adding a civilian planner/consultant to the endstrength team, and waiting to hard-wire models until the planners are comfortable with the modified models and their methods.
Author: T. M. Beatty
Author: T. M. Beatty
Author: Barry Siegel
Author: 
Author: Michael C. Campbell
Author: edward S. Bres
Author: Roland G. Ruppenthal
Author: U.S. Army War College
Author: 
Author: United States. Congress. Senate. Committee on Appropriations
Author: Anita U. Hattiangadi