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Aircraft availability (AA) is a key metric for assessing operational readiness. The declining trend in AA is a documented concern for senior Air Force leaders. This paper aims to investigate the components of non-available time and subsequently focuses on the largest and fastest growing category: not mission capable maintenance unscheduled (NMCMU). Then, utilization of aircraft platforms is examined to determine the readiness benefits of increasing available hours.

Stepwise regression is conducted on a data set of 30 aircraft platforms, consisting of 542 observations from 1998 to 2017, to reveal drivers of NMCMU. Next, utilization of aircraft platforms is examined through regression and correlation analysis of aircraft platforms and sorties or hours flown.

Regression analysis reveals drivers of NMCMU include platform type, average age of aircraft, fleet size, breaks and cannibalization. These factors explain 80.6 per cent of the variance in the data set when predicting NMCMU. Additionally, the utilization results show that when more hours are made available, 5 per cent of each new hour is used for flying. Further analysis at the individual platform level finds a strong or moderate correlation between available hours and sorties flown for 93 per cent of the platforms.

Implications from the regression analysis demonstrate there are remedies to increase AA, but many of these remedies may be costly. The utilization analysis expresses the potential readiness benefits of increasing available hours.

Within earned value management, the cost performance index (CPI) and the critical ratio (CR) are used to generate the estimates at completion (EACs). According to the research in the 1990s, estimating the final contract’s cost at completion (CAC) using EAC_CR is a quicker predictor of the actual final cost versus using EAC_CPI. This paper aims to investigate whether this trend stills holds for modern department of defense contracts.

Accessing the Cost Assessment Data Enterprise (CADE) database, 451 contracts consisting of 863 contract line item numbers (CLINs) were initially retrieved and analyzed in three stages. The first replicated the work conducted in 1990s. The second stage entailed calculating 95 per cent confidence intervals and hypothesis tests regarding percentage accuracy of EACs for a contract’s final CAC. Lastly, regression analysis was conducted to characterize major, moderate and minor influencers on EAC reliability.

For modern contracts, EAC_CR aligns more with EAC_CPI and no longer demonstrates early accuracy of a contract’s final CAC. Contract percentage completion strongly reduced the per cent error of estimating CAC, while cost-plus-fixed-fee contracts and those with no work breakdown structure greater than Level 2 negatively affected accuracy.

To militate against optimism of early assessment of a contract's true cost.

This paper provides empirical evidence that EAC_CR behaves more like EAC_CPI with respect to modern contracts, suggesting that today’s contracts have relatively high SPI. Therefore, caution is warranted for program managers when estimating the CAC from contract initiation up to and slightly beyond the mid-point of completion.

There appears to be no empirical-based method in the literature for estimating if an engineering change proposal (ECP) will occur or the dollar amount incurred. This paper aims to present an empirically based approach to address this shortfall.

Using the cost assessment data enterprise database, 533 contracts were randomly selected via a stratified sampling plan to build two regression models: one to predict the likelihood of a contract experiencing an ECP and the other to determine the expected median per cent increase in baseline contract cost if an ECP was likely. Both models adopted a stepwise approach. A validation set was placed aside prior to any model building.

Not every contract incurs an ECP; approximately 80 per cent of the contracts in the database did not have an ECP. The likelihood of an ECP and the additional amount incurred appears to be statistically independent of acquisition phase, branch of service, commodity, contract type or any other factor except for the basic contract amount and the number of contract line item numbers; both of these later variables equally affected the contract percentage increase because of an ECP. The combined model overall bested current anecdotal approaches to ECP withhold.

This paper both serves as a published reference point for ECP withholds in the archival forum and presents an empirically based method for determining per cent ECP withhold to use.

The Weapon Systems Acquisition Reform Act (WSARA) was enacted in 2009 to improve Department of Defense public procurement processes and limit cost overruns in major acquisition programs.

Seven years later, the authors investigate the effects of WSARA on cost overruns for major Air Force acquisition programs and then conduct an exploratory case study specifically targeting WSARA impacts on the Operations and Support phase of a program’s life cycle.

The authors find that while there are some positive impacts on cost overruns in limited areas, the majority of the models demonstrate either no statistically significant effect from WSARA or an increase in cost overruns post implementation.

These findings are consistent with much of the literature on the historical ineffectiveness of previous acquisition reforms to ameliorate cost overruns.

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.

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.

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.

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.

Delineating where stability occurs in a contract provides the window of opportunity for procurement officials to positively affect cost and schedule outcomes. While the concept of a Cost Performance Index (CPI) "stability rule" has been routinely cited by Earned Value Management (EVM) authors since the early 1990's, more recent research questions the veracity of this stability rule. This paper resolves the controversy by demonstrating that the definition of stability matters. We find a morphing of the stability definition over time, with three separate definitions permeating the literature. Next, an analysis of Department of Defense contracts for both cost and schedule stability properties finds that the veracity of the stability rule is intricately tied to the definition used.

This paper examines the relationship between a prime contractor's financial health and its mergers and acquisitions (M&A) spending in the defense industry. It aims to provide models that give the United States Department of Defense (DoD) indications of future M&A activity, informing decision-makers and contributing to ensuring competitive markets that benefit the consumer.

The study uses panel data regression models on 40 companies between 1985 and 2021. The company's financial health is assessed using industry-standard financial ratios (i.e. measures of profitability, efficiency, solvency and liquidity) while controlling for economic factors such as national productivity, defense budgets and firm size.

The results show a significant relationship between efficiency and M&A spending, indicating that companies with lower efficiency tend to spend more on M&As. However, there was no significant relationship between M&A spending and a company's profitability or solvency. These results were consistent with previous research and the study's hypotheses for profitability and solvency. However, the effect of liquidity was the opposite of the expected result, possibly due to the defense industry's different view on liquidity compared to previous research.

The paper provides insights into the relationship between a prime contractor's financial health and its M&A spending, a topic with limited research. The findings can inform policymakers and regulators on the industrial base's future M&A activity, ensuring competitive markets that benefit the consumer.

For decades, the Department of Defense (DoD) has employed numerous reporting and monitoring tools for characterizing the acquisition cost estimates of its programs. These tools have led to dozens of studies thoroughly documenting the magnitude and extent of DoD acquisition cost growth. However, little attention has been paid to the behavior of the other main cost component of a system's life cycle cost: Operating and Support (O&S) costs. Consequently, the DoD has little knowledge regarding the accuracy of O&S cost estimates or how that accuracy changes over time. In a previous paper, the authors described an analytical methodology for remedying this deficiency via a study to characterize the historical accuracy of O&S cost estimates. The results are presented here, and indicate there tend to be large errors in DoD O&S cost estimates, and that the accuracy of the estimates improves little over time

This paper examines the opportunity cost of applying simple averages in formulating the Department of Defense (DoD) budget for foreign exchange rates. Using out-of-sample validation, we evaluate the status quo of a center-weighted average against a Random Walk model, ARIMA, forward rates, futures contracts, and a private firm's forecasts over two time periods extending from Fiscal Year (FY) 1991 to FY 2014. The results strongly indicate that four of the alternative methods outperform the status quo over the shorter time period, and three methods for both time periods. Furthermore, a non-parametric comparison of the median error demonstrates statistical similarities between the four alternative methods over the short term. Overall, the paper recommends using the futures option prices to decrease forecast error by 3.23% and avoiding a $34 million opportunity cost.

For decades, cost growth in major military weapon system programs has been problematic. The result is a multitude of studies documenting internally focused causes of Department of Defense (DoD) acquisition cost growth and a spawning of acquisition reforms that have provided little relief to the problem. The missing components of these prior analyses are the larger economic and political factors that contribute to cost growth. This study analyzes cost growth in major DoD development and procurement contracts through a holistic political-economy construct including the effect of the political party of the President and Congress, and the liberal-conservative record of the Armed Services Committees. These political-economy constructs in both development contracts and procurement contracts are found to be more robust.