Jonathan D. Ritschel

Using Pre-Milestone B Data to Predict Schedule Duration for Defense Acquisition Programs

Accurately predicting a realistic schedule for a defense acquisition program is a difficult challenge considering the inherent risk and uncertainties present in the early stages of a program. Through the application of multiple regression modeling, we provide the program manager with a statistical model that predicts schedule duration from official program initiation, which occurs at Milestone B, to the initial operational capability of the program’s deliverable system. Our model explains 42.9% of the variation in schedule duration across historical data from a sample of 56 defense programs from all military services. Statistically significant predictor variables include whether a program is a new effort or modification to an existing program, the year of Milestone B start as it relates to changes in defense acquisition reform policy, and the amount of raw funding (adjusted for inflation) prior to Milestone B for a program. Our final and strongest predictor variable, percentage of the total RDT&E (Research Development Test and Evaluation) funding profile allocated at Milestone B, indicates that increased percentage of RDT&E funding for pre-Milestone B technology risk reduction may shorten a program’s schedule duration to initial operational capability.

Time Phasing Aircraft R&D Using the Weibull and Beta Distributions

Early research on time phasing primarily focuses on the theoretical foundation for applying the cumulative distribution function, or S-curve, to model the distribution of development expenditures. Minimal methodology prior to 2002 provides for estimating the S-curve’s parameter values. Brown et al. (2002) resolved this shortcoming through regression analysis, but their methodology is not specific to aircraft and does not consider aircraft-specific variables, such as first flight. Using a sample of 26 Department of Defense aircraft programs, we build upon Brown et al.’s work by examining whether a model driven by aircraft-specific variables can more accurately predict budget requirements. As a baseline, we compare our model to the commonly cited 60/40 “rule of thumb,” which assumes 60% expenditures at 50% schedule. We discover that our developed Weibull model explains 74.6% of total variation in annual budget, improving the estimation of budgets by 6.5%, on average, over the baseline 60/40 model.

Characterizing the accuracy of dod operating and support cost estimates

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 systems 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

A Macro-Stochastic Model for Improving the Accuracy of Department of Defense Life Cycle Cost Estimates

The authors present a prognostic cost model that is shown to provide significantly more accurate estimates of life cycle costs for Department of Defense programs. Unlike current cost estimation approaches, this model does not rely on the assumption of a fixed program baseline. Instead, the model presented here adopts a stochastic approach to program uncertainty, seeking to identify and incorporate top-level (i.e., “macro”) drivers of estimating error to produce a cost estimate that is likely to be more accurate in the real world of shifting program baselines. The predicted improvement in estimating accuracy provided by this macro-stochastic cost model translates to hundreds of billions of dollars across the Department of Defense portfolio. Furthermore, improved cost estimate accuracy could reduce actual life cycle costs and/or allow defense acquisition officials the ability to make better decisions on the basis of more accurate assessments of value and affordability.

Forecasting foreign currency exchange rates for department of defense budgeting1

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 firms 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

Impact of political-economy variables on cost growth in military weapon system contracts

34 million opportunity cost.

A Cost-Based Decision Tool for Valuing DoD System Design Options

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.

Efficacy of US Legislation in Military Acquisition Programmes: Nunn–McCurdy Act Unveiled

Abstract The DoD has frequently demonstrated its ability to procure phenomenal systems; however, these accomplishments are often tarnished by substantial cost and schedule overruns. While defense acquisition policies are continually being revised to address these perennial problems, many believe that a more fundamental source of these overruns is the lack of flexibility in the systems being developed, which tend to preclude effective responses to unexpected events. However, providing justification to invest in flexibility is a tough sell when the measure of value is a military capability or political outcome, as there is no extant method to demonstrate the potential return on investment. This paper introduces a decision tool for valuing the inherent ability of different systems or designs to respond to uncertainty. The proposed tool is essentially a modification of the current life cycle cost model and is premised on the notion that the need for capability changes in a system arises in a stochastic manner that can be incorpo- rated into a continually updated, expected value model presented in terms of total life cycle cost. The cost-based decision tool presented here quantifies the ability of competing designs to respond to these capability changes via a cumulative distribution function (CDF). The design with the most favorable CDF (i.e., the one that is most likely to meet the most likely set of require- ments at the lowest expected value curve of life cycle cost) is deemed to be the “best” design.

Investigation into the Ratio of Operating and Support Costs to Life-Cycle Costs for DoD Weapon Systems

This study analyses the impact of regulatory legislation, specifically the Nunn–McCurdy Act, by the United States Congress on major military acquisition programmes. Nunn–McCurdys stated objective is to curtail cost growth in weapon system acquisitions. To achieve this end, the legislation threatens cancellation of military acquisition programmes that breach specified cost growth thresholds. This effort collects and analyses a unique data set spanning the lifetime of the Nunn–McCurdy legislation to reveal the threat of termination is rarely enforced. Secondary effects, in the form of programme restructuring are found to be prevalent, but not in those areas that most adversely affect the programme. Thus, Nunn–McCurdy does not provide a strong incentive for acquisition programmes to change processes or procedures. As a result, the legislation is ineffectual in achieving its objective, and cost growth in major US military acquisition programmes remains problematic.