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All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

The Dangers of Parametrics

Building a parametric cost model is hard work. The data is noisy and often does not behave like we want it to. We need statistics to give us an indication of the goodness of our models, but; statistics can be manipulated and mislead. On top of all of that, our own very human biases can lead us astray; causing us to see patterns in the noise and draw false conclusions from the data. Yet, it is the data itself that is the foundation for making better cost estimates and cost models. I believe the mistake we often make is we believe that our models are representative of the data; that our models summarize the experiences, the knowledge, and the stories contained in the data. However, it is the opposite that is true. Our models are but imitations of reality. They give us trends, but not truth. The experiences, the knowledge, and the stories that we need in order to make good cost estimates is bound up in the data. You cannot separate good cost estimating from a knowledge of the historical data. One final thought. It is our attempts to make sense out of the randomness that leads us astray. In order to make progress as cost modelers and cost estimators, we must accept that there are real limitations on our ability to model the past and predict the future. I do not believe we should throw up our hands and say this is the best we can do. Rather, to see real improvement we must first recognize these limitations, avoid the easy but misleading solutions, and seek to find ways to better model the world we live in. I don't have any simple solutions. Perhaps the answers lie in better data or in a totally different approach to simulating how the world works. All I know is that we must do our best to speak truth to ourselves and our customers. Misleading ourselves and our customers will, in the end, result in an inability to have a positive impact on those we serve.

Prince, Frank A.↗
NASA NTRS1978

How much energy does energy cost?

Estimating the energy cost of producing and delivering an energy product involves the quantitative determination of all relevant energy flows and the aggregation of these flows into meaningful indices of system performance. Five emerging energy technologies are subjected to energy analysis. The energy delivered by each is substantially greater than the energy consumed during construction and lifelong operation of the system. Net energy analysis can provide interesting and perhaps useful information regarding specific technologies, but it does not necessarily provide additional information essential to the making of decisions regarding those technologies.

Devine, W. D., Jr.↗
NASA NTRS2015

Underestimation of Project Costs

Large projects almost always exceed their budgets. Estimating cost is difficult and estimated costs are usually too low. Three different reasons are suggested: bad luck, overoptimism, and deliberate underestimation. Project management can usually point to project difficulty and complexity, technical uncertainty, stakeholder conflicts, scope changes, unforeseen events, and other not really unpredictable bad luck. Project planning is usually over-optimistic, so the likelihood and impact of bad luck is systematically underestimated. Project plans reflect optimism and hope for success in a supposedly unique new effort rather than rational expectations based on historical data. Past project problems are claimed to be irrelevant because "This time it's different." Some bad luck is inevitable and reasonable optimism is understandable, but deliberate deception must be condemned. In a competitive environment, project planners and advocates often deliberately underestimate costs to help gain project approval and funding. Project benefits, cost savings, and probability of success are exaggerated and key risks ignored. Project advocates have incentives to distort information and conceal difficulties from project approvers. One naively suggested cure is more openness, honesty, and group adherence to shared overall goals. A more realistic alternative is threatening overrun projects with cancellation. Neither approach seems to solve the problem. A better method to avoid the delusions of over-optimism and the deceptions of biased advocacy is to base the project cost estimate on the actual costs of a large group of similar projects. Over optimism and deception can continue beyond the planning phase and into project execution. Hard milestones based on verified tests and demonstrations can provide a reality check.

Cost estimation↗
NASA NTRS2005

The Effect of Infrastructure Sharing in Estimating Operations Cost of Future Space Transportation Systems

NASA and the aerospace industry are extremely serious about reducing the cost and improving the performance of launch vehicles both manned or unmanned. In the aerospace industry, sharing infrastructure for manufacturing more than one type spacecraft is becoming a trend to achieve economy of scale. An example is the Boeing Decatur facility where both Delta II and Delta IV launch vehicles are made. The author is not sure how Boeing estimates the costs of each spacecraft made in the same facility. Regardless of how a contractor estimates the cost, NASA in its popular cost estimating tool, NASA Air force Cost Modeling (NAFCOM) has to have a method built in to account for the effect of infrastructure sharing. Since there is no provision in the most recent version of NAFCOM2002 to take care of this, it has been found by the Engineering Cost Community at MSFC that the tool overestimates the manufacturing cost by as much as 30%. Therefore, the objective of this study is to develop a methodology to assess the impact of infrastructure sharing so that better operations cost estimates may be made.

Sundaram, Meenakshi↗
NASA NTRS2003

Dynamic cost risk estimation and budget misspecification

Cost risk for new technology development is estimated by explicit stochastic processes. Monte Carlo simulation is used to propagate technology development activity budget changes during the technology development cycle.

cost risk random walk Monte Carlo simulation princ↗
NASA NTRS1990

Long-range planning cost model for support of future space missions by the deep space network

A simple model is suggested to do long-range planning cost estimates for Deep Space Network (DSP) support of future space missions. The model estimates total DSN preparation costs and the annual distribution of these costs for long-range budgetary planning. The cost model is based on actual DSN preparation costs from four space missions: Galileo, Voyager (Uranus), Voyager (Neptune), and Magellan. The model was tested against the four projects and gave cost estimates that range from 18 percent above the actual total preparation costs of the projects to 25 percent below. The model was also compared to two other independent projects: Viking and Mariner Jupiter/Saturn (MJS later became Voyager). The model gave cost estimates that range from 2 percent (for Viking) to 10 percent (for MJS) below the actual total preparation costs of these missions.

Sherif, J. S.↗
NASA NTRS1973

Cost analysis of atmosphere monitoring systems

The cost analyses of two leading atmospheric monitoring systems, namely the mass spectrometer and the gas chromatograph, are reported. A summary of the approach used in developing the cost estimating techinques is presented; included are the cost estimating techniques, the development of cost estimating relationships and the atmospheric monitoring system cost estimates.

Yakut, M. M.↗
NASA NTRS1979

Estimating the cost of production stoppage

Estimation model considers learning curve quantities, and time of break to forecast losses due to break in production schedule. Major parameters capable of predicting costs are number of units made prior to production sequence, length of production break, and slope of learning curve produced prior to break.

Delionback, L. M.↗
NASA NTRS2019

Labor Estimation and Trending in an Operations Environment

Accurate cost estimation for future work is important for ensuring that organizations have the personnel and resources needed to complete a task successfully. Operations support in particular provides additional challenges for estimating cost. Unlike manufacturing-based work, it may be difficult to derive a "cost per product," and projects that appear to be similar may have drastically different underlying assumptions. In addition, for critical operations, a certain level of adaptability to changing circumstances is expected. Responding to contingencies or anomalies requires additional support and troubleshooting, and could result in increases to project cost. Labor estimation is one of the most important inputs for estimating the cost of an operations-based project, especially in a pre-established facility. Various methods are needed to develop reliable estimates. These methods include a bottom-up summarization of known or expected work items, and a top-down estimate generated by trending and scaling actual labor from past analogous operations support.

Laing, Jason↗
NASA NTRS1990

Managing Information On Costs

Cost Management Model, CMM, software tool for planning, tracking, and reporting costs and information related to costs. Capable of estimating costs, comparing estimated to actual costs, performing "what-if" analyses on estimates of costs, and providing mechanism to maintain data on costs in format oriented to management. Number of supportive cost methods built in: escalation rates, production-learning curves, activity/event schedules, unit production schedules, set of spread distributions, tables of rates and factors defined by user, and full arithmetic capability. Import/export capability possible with 20/20 Spreadsheet available on Data General equipment. Program requires AOS/VS operating system available on Data General MV series computers. Written mainly in FORTRAN 77 but uses SGU (Screen Generation Utility).

Taulbee, Zoe A.↗
NASA NTRS1982

Life Cycle Cost Analysis of Shuttle-Derived Launch Vehicles, Volume 1

The design, performance, and programmatic definition of shuttle derived launch vehicles (SDLV) established by two different contractors were assessed and the relative life cycle costs of space transportation systems using the shuttle alone were compared with costs for a mix of shuttles and SDLV's. The ground rules and assumptions used in the evaluation are summarized and the work breakdown structure is included. Approaches used in deriving SDLV costs, including calibration factors and historical data are described. Both SDLV cost estimates and SDLV/STS cost comparisons are summarized. Standard formats are used to report comprehensive SDLV life cycle estimates. Hardware cost estimates (below subsystem level) obtained using the RCA PRICE 84 cost model are included along with other supporting data.

Source record↗
NASA NTRS1973

Cost analysis of atmosphere monitoring systems

A methodology was developed to predict realistic relative cost of life support systems and to define areas of major cost impacts in the development cycle. Emphasis was given to tailoring the cost data for usage by program planners and designers. Cost estimates can be completed using the developed equations for varying degrees of equipment refinement, as well as comparative costs between different functional methods. Cost analysis of two leading atmosphere monitoring systems, namely the mass spectrometer and the gas chromatograph, is discussed. A summary of the approach used in developing the cost estimating techniques is presented. Included are the cost estimating techniques, the development of cost estimating relationships, and the atmosphere monitoring system cost estimates.

Yakut, M. M.↗
NASA NTRS1975

Cost analysis of life sciences experiments and subsystems

Cost estimates for experiments and subsystems flown in the Spacelab were established. Ten experiments were cost analyzed. Estimated cost varied from $650,000 for the hardware development of the SPE water electrolysis experiment to $78,500,000 for the development and operation of a representative life sciences laboratory program. The cost of subsystems for thermal, atmospheric and trace contaminants control of the Spacelab internal atmosphere was also estimated. Subsystem cost estimates were based on the utilization of existing components developed in previous space programs whenever necessary.

Yakut, M. M.↗
NASA NTRS1992

Standard cost elements for technology programs

The suitable structure for an effective and accurate cost estimate for general purposes is discussed in the context of a NASA technology program. Cost elements are defined for research, management, and facility-construction portions of technology programs. Attention is given to the mechanisms for insuring the viability of spending programs, and the need for program managers is established for effecting timely fund disbursement. Formal, structures, and intuitive techniques are discussed for cost-estimate development, and cost-estimate defensibility can be improved with increased documentation. NASA policies for cash management are examined to demonstrate the importance of the ability to obligate funds and the ability to cost contracted funds. The NASA approach to consistent cost justification is set forth with a list of standard cost-element definitions. The cost elements reflect the three primary concerns of cost estimates: the identification of major assumptions, the specification of secondary analytic assumptions, and the status of program factors.

Christensen, Carisa B.↗