Analyzing operating and support costs for Air Force aircraft. Issue 1 (3rd August 2018)

• Record Type: Journal Article
• Authors: Hewitson, Scott C.; Ritschel, Jonathan D.; White, Edward; Brown, Gregory
• Is Part Of: Journal of defense analytics and logistics. Volume 2:Issue 1(2018)
• Page Start: 38
• Page End: 54
• Publication Date: 2018-08-03
• Subjects: Stability -- Regression -- Cost analysis -- Operating and support costs; Military art and science -- Periodicals; Military research -- Periodicals; Defense industries -- Periodicals; Logistics -- Periodicals; 355.4
• DOI: 10.1108/JDAL-03-2018-0006
• Languages: English
• ISSNs: 2399-6439

Abstract

Abstract : Purpose: Recent legislation resulted in an elevation of operating and support (O&S) costs' relative importance for decision-making in Department of Defense programs. However, a lack of research in O&S hinders a cost analyst's abilities to provide accurate sustainment estimates. Thus, the purpose of this paper is to investigate when Air Force aircraft O&S costs stabilize and to what degree. Next, a parametric O&S model is developed to predict median O&S costs for use as a new tool for cost analyst practitioners. Design/methodology/approach: Utilizing the Air Force total ownership cost database, 44 programs consisting of 765 observations from 1996 to 2016 are analyzed. First, stability is examined in three areas: total O&S costs, the six O&S cost element structures and by aircraft type. Next, stepwise regression is used to predict median O&S costs per total active inventory (CPTAI) and identify influential variables. Findings: Stability results vary by category but generally are found to occur approximately five years from initial operating capability. The regression model explains 89.01 per cent of the variance in the data set when predicting median O&S CPTAI. Aircraft type, location of lead logistics center and unit cost are the three largest contributing factors. Originality/value: Results from this research provide insight to cost analysts on when to start using actual O&S costs as a baseline for estimates in lieu of analogous cost program data and also derives a new parametric O&S estimating tool designed as a cross-check to current estimating methodologies.