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This two-day course covers the primary methods for cost estimation needed in systems development, including parametric estimation, activity-based costing, life cycle estimation, and probabilistic modeling. The estimation methods are placed in context of a Work Breakdown Structure and program schedules, while explaining the entire estimation process.
Emphasis is also placed on using cost models to perform trade studies and calibrating cost models to improve their accuracy. Participants will learn how to use cost models through real-life case studies. Common pitfalls in cost estimation will be discussed including behavioral influences that can impact the quality of cost estimates. We conclude with a review of the state-of-theart in cost estimation.
What You Will Learn:
- What are the most important cost estimation methods?
- How is a WBS used to define project scope?
- What are the appropriate cost estimation methods for my situation?
- How are cost models used to support decisions?
- How accurate are cost models? How accurate do they need to be?
- How are cost models calibrated?
- How can cost models be integrated to develop estimates of the total system?
- How can cost models be used for risk assessment?
- What are the principles for effective cost estimation?
From this course you will obtain the knowledge and ability to perform basic cost estimates, identify tradeoffs, use cost model results to support decisions, evaluate the goodness of an estimate, evaluate the goodness of a cost model, and understand the latest trends in cost estimation
- Introduction. Cost estimation in context of system life cycles. Importance of cost estimation in project planning. How estimation fits into the proposal cycle. The link between cost estimation and scope control. History of parametric modeling.
- Scope Definition. Creation of a technical work scope. Definition and format of the Work Breakdown Structure (WBS) as a basis for accurate cost estimation. Pitfalls in WBS creation and how to avoid them. Task-level work definition. Class exercise in creating a WBS.
- Cost Estimation Methods. Different ways to establish a cost basis, with explanation of each: parametric estimation, activity-based costing, analogy, case based reasoning, expert judgement, etc. Benefits and detriments of each. Industry validated applications. Schedule estimation coupled with cost estimation. Comprehensive review of cost estimation tools.
- Economic Principles. Concepts such as economies/diseconomies of scale, productivity, reuse, earned value, learning curves and prediction markets are used to illustrate additional methods that can improve cost estimates.
- System Cost Estimation.Estimation in software, electronics, and mechanical engineering. Systems engineering estimation, including design tasks, test & evaluation, and technical management. Percentage-loaded level-of-effort tasks: project management, quality assurance, configuration management. Class exercise in creating cost estimates using a simple spreadsheet model and comparing against the WBS.
- Risk Estimation. Handling uncertainties in the cost estimation process. Cost estimation and risk management. Probabilistic cost estimation and effective portrayal of the results. Cost estimation, risk levels, and pricing. Class exercise in probabilistic estimation.
- Decision Making. Organizational adoption of cost models. Understanding the purpose of the estimate (proposal vs. rebaselining; ballpark vs. detailed breakdown). Human side of cost estimation (optimism, anchoring, customer expectations, etc.). Class exercise on calibrating decision makers.
- Course Summary. Course summary and refresher on key points. Additional cost estimation resources. Principles for effective cost estimation
Ricardo Valerdi,is an Associate Professor at University of Arizonia and the developer of the COSYSMO model for estimating systems engineering effort. Dr. Valerdi’s work has been used by BAE Systems, Boeing, General Dynamics, L-3 Communications, Lockheed Martin, Northrop Grumman, Raytheon, and SAIC. Dr. Valerdi is a Visiting Associate of the Center for Systems and Software Engineering at the University of Southern California where he earned his Ph.D. in Industrial & Systems Engineering. Previously, he worked at The Aerospace Corporation, Motorola and General Instrument. He served on the Board of Directors of INCOSE, is an Editorial Advisor of the Journal of Cost Analysis and Parametrics, and is the author of the book The Constructive Systems Engineering Cost Model (COSYSMO): Quantifying the Costs of Systems Engineering Effort in Complex Systems (VDM Verlag, 2008).
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