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Graham K Kirk. Sowjanya Reddy. Sarath Chandra M. William Sim. Subodh Kant. Boris Popov. Mikey Messi. Priya Shinde. Bennie Deal. As technology advances and analytical techniques evolve, machine learning and big data systems stand to dramatically change the cost industry- these changes are coming sooner than we may think. Industry requires timely, efficient and defensible analysis, and new data sources are allowing previously unexplored opportunities to meet these goals. We explore how automated algorithms can identify market trends to forecast program cost with greater accuracy, and in less time than historically required by an analyst.

DoD is moving toward rapid acquisition approaches to deploy critical capability to the warfighter quickly.


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  8. Rapid acquisitions have shortened timelines and less definition than traditional acquisitions. These constraints challenge traditional cost estimation practices. Multiple case studies were conducted to understand the challenges to cost estimating processes in a rapid acquisition environment. Easily implementable recommendations are made to help ensure credible and confident cost estimates are developed, even within the constraints of these challenging environments. One of the most important tasks for a software project manager is to accurately forecast the schedule and resources needed to complete the project.

    This paper will describe a novel approach to this problem that combines Monte Carlo-based uncertainty analysis with an innovative new technique for estimating software requirements, which utilizes an agile-style Delphi estimating methodology. This method has been successfully implemented on several government projects and is a viable option for any software project. The analysis is based on 9 fielded systems collected from DoD authoritative data sources.

    Cost contributors, drivers, and factors by major cost elements will also be examined. Results may be used for crosschecking cost estimates or business case analyses at an early phase to inform funding decisions. The process of applying historical cost, schedule and technical data to develop new program estimates is often more difficult than textbooks suggest. The paper provides real-world insight to the issues that arise when capturing, analyzing and applying data for the next estimate. The goal is to integrate information from multiple products, systems and subsystems.

    Lessons learned include experience and best practices when working with financial, engineering, manufacturing and program management.

    Plea against Deshmukh: Matter “quite serious”, says SC; asks Param Bir to approach HC

    Percent Development Cost. Advanced technology acquisition often proceeds in steps characterized by TRL of systems or components. The relationship between TRL ordinal number and percent of total acquisition cost could be used as a factor in estimating the cost of new acquisitions at each phase from concept definition through production decision.

    A study of historical data will be performed to establish such a relationship based on a specific definition of TRLs, which vary across government agencies. Machine Learning Approach to Cost Analysis. Machine learning provides an alternate to parametric modeling. At Boeing, we are experimenting with several machine learning techniques for cost estimation and analysis; Random Forest prediction methodology, in particular, has shown encouraging results.

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    This paper describes our cost applications of Random Forest. Technology Development Cost and Schedule Modeling. A tangible need exists in the scientific, technology, and financial communities for economic forecast models that improve new or early life-cycle technology development estimating. Industry models, research, technology datasets, modeling approaches, and key predictor variables are first examined. Analysis is then presented, leveraging a robust industry project dataset, applying technology and system-related parameters to deliver higher performing parametric cost and schedule models.

    Cost Estimating and Analysis is a vital resource for program and project managers, regardless of agency or activity. This presentation will provide a history of the creation of a cost analysis capability in a new agency, changes over time, lessons learned and current successes of the Cost Analysis Division. With the challenges in quantifying program risks, interdependencies, and the business case impact on portfolios, cost estimators can use real options to estimate probabilistic value in business cases and assess portfolio value.

    Many business cases not only add value as stand-alone investments, but they provide the opportunity for subsequent investments. Cost estimators can measure this incremental program value and the impact of a specific investment on a larger portfolio by using real options. Discount Rate for Government Investment. We often use a discounted-cash-flow construct to evaluate the Economic Viability of an investment.

    Since any resources consumed by the government must be foregone by the private sector, we will argue that the discount rate should be based on a rate that at least proxies the value of private investment. Are the Rates Right? Medical escalation rates continue to trend higher than general inflation - with significant impact on defense firms and acquisition affordability.