Integrated Cost & Schedule Risk Analysis Dynamic Integrated Cost Estimator (DICE) Model This document contains Booz Allen Hamilton proprietary and confidential information and is intended solely for the use and information of the client to whom it is addressed. This data shall not be released to other contractors without written consent from Booz Allen Hamilton. Adelaide, Australia 28 June, 2011 Booz Allen Proprietary/Not for Distribution
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This document contains Booz Allen Hamilton proprietary and confidential information and is intended solely for the use and information of the client to
whom it is addressed. This data shall not be released to other contractors without written consent from Booz Allen Hamilton.
Whether assessing/analyzing NASA, DoD or Intelligence Community owned projects, the story is the same each time: Programs are increasingly experiencing growth above and beyond their initial cost and schedule estimates
This is not just a cosmetic problem: Cost and schedule growth delays capabilities and constraints the budgets of other programs causing a waterfall of instability
Studies have examined the reasons behind this growth reaching similar conclusions
1. Early program optimism leading to optimistic estimates
2. Insufficient cost and schedule reserves available to cover risk
3. Weak independent validation of cost and schedule
Recognizing this, many guides, including the GAO’s Cost Estimating Handbook, have included Risk Analysis as a required step in best practice cost estimating processes
Introduction
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RealTime Analytics™
One of the challenges in performing cost and schedule analysis is the time required to run simulations
– Risk analysis, required for all cost estimates by 2009 Weapons System Acquisition Reform Act of 2009 and GAO, requires the use of simulations
– Run-times of minutes or hours prohibit most risk analyses models from being decision making tools as they can not be re-run during meetings
RealTime Analytics™ (RTA) is a collection of technologies, tools and methodologies allowing complex analytics to be performed far faster than using currently available methods
This presentation will focus on the Dynamic Integrated Cost Estimator (DICE) and the methodologies it addresses:
Joint Risk Analysis methods estimate cost and schedule simultaneously; JCL scatter plot produced directly from analysis
When Joint Risk Analysis methods are not used, cost and schedule risk analyses must be combined using a Monte Carlo simulation
When risk analyses are combined, care must be taken to ensure results are compatible
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JCL analysis can be performed using existing resources; likely risk management, cost estimating, and scheduling personnel
The artifacts needed to perform a JCL analysis are:
– A program schedule (IMS or analysis schedule) with uncertainty bounds on task durations
– A quantified risk register (probabilities, cost and schedule impacts) where each risk is mapped to a task in the IMS
– A cost estimate with uncertainty bounds that maps to the schedule
Creation of these artifacts requires communication between program’s cost estimating, scheduling and risk management staff
Joint Confidence Level Analysis Process at NASA
Integrated Risk Assessment
Program Risk
Register
Integrated Master
Schedule
Cost Estimate
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Joint Confidence Level Analysis has gained significant momentum recently
– NASA is leading the way in the development of this methodology
– NASA Policy Directive 1000.5 mandates that programs will be baselined at the “70 percent confidence level” using a “joint cost and schedule probability distribution”2
– NPD 1000.5 also stipulates that projects are funded at no less than 50% of the JCL or as approved by the decision authority, maintaining JCLs through the program lifecycle
– The goal is to provide stronger assurance that NASA can meet cost and schedule targets3
– A recent GAO report cites NASA’s JCL policy as an effort “to provide transparency on the effects of funding changes on the probability of meeting cost and schedule commitments” 4
– NASA Cost Analysis Division (CAD) has developed a handbook to provide more information and guidance on this topic
– Programs conducting JCL Analysis include James Webb Space Telescope and SOFIA
While the methodology has made substantial strides, the cost and schedule communities must overcome political and technical obstacles before full adoption
NASA Joint Confidence Level Analysis Policy
2 – NPD 1000.5 - http://www.hq.nasa.gov/office/codeq/doctree/10005.htm - January 15, 20093 – JCL Status Report - http://www.nasa.gov/pdf/421542main_JCL%20Status%20Report-2010%20Feb.pdf – February 20104 – GAO Report – “NASA – Assessments of Selected Large-Scale Projects” - http://www.gao.gov/new.items/d11239sp.pdf - March 2011
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NASA JCL Model Prototype: DICE
In Fall 2010, NASA CAD commissioned the development of a JCL model prototype
The intention of this effort was to explore the value of producing a standard toolset for NASA programs conducting JCL analysis
Booz Allen created the Dynamic Integrated Cost Estimator (DICE) with a focus on streamlining the JCL process and decreasing simulation runtimes
Other key features of the DICE prototype development included:
– Rapid schedule import from MS Project
– Cost-Loading
– Discrete Risk Analysis
– JCL Scatter Plots and Iso-Curves
– Benchmarking effort with other JCL tools
It is important to note that there are many tools that projects can use to develop JCLs, but DICE is optimized for this analysis
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DICE facilitates Joint Confidence Level Analysis
DICE is an Adobe Flex-based tool for cutting-edge cost and schedule risk analysis
– Includes modeling capability for producing build-up Joint Confidence Levels (JCLs)
– Achieves industry-leading runtimes using Booz Allen’s RealTime Analytics
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DICE – Benchmarking against Primavera Risk Analysis