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| GOVERNMENT & POLICY |
With
increased responsibilities, staff cutbacks, and drastically
reduced budgets, this is a challenging time for most government
institutions. Whether you're focused on cost estimation, human
health risk assessment, strategic resource allocation, or production
forecasts, you cannot afford to ignore how uncertainty effects your forecasts and exposes your organization to unnecessary risk. Your knowledge and your toolset will make the difference
between whether your work succeeds or fails.
Today, Crystal
Ball is the risk analysis software tool chosen by more than 85% of the Fortune 500.
In government, organizations as diverse as the US Army Corps
of Engineers, the New York Power Authority, Los Alamos National
Labs, and Health Canada all rely on Crystal Ball to manage risk
and make more informed business and strategic decisions.
Crystal Ball is a Microsoft® Excel®-based suite of analytical tools that includes Monte Carlo simulation, optimization, and forecasting. With little effort, you can apply these advanced analytical techniques to your new or existing spreadsheets to create more accurate cost and financial predictions and better informed business decisions.
Low-cost software
and improved computing power can enable you to better calculate
the risks in your strategy or process. Crystal Ball can help
you better assess your alternatives, increase the confidence
you have in planning details, and make more informed decisions
despite a lack of data or an uncertain. |
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Key features of interest to your industry include sensitivity and tornado analysis, correlation, and historical
data fitting. The sensitivity analysis and tornado analysis are
two separate methods that help you to understand which of the
uncertain inputs drive the uncertainty in your models. Correlation
lets you link uncertain inputs and account for their positive
or negative dependencies. If historical data does exist, the data
fitting feature will compare the data to the distribution algorithms
and calculate the best possible fit and parameters for your data.
One of the greatest benefits of Crystal Ball is
its ability to transparently communicate risk to engineers, accountants,
and managers who may not be comfortable with results expressed
in terms of probability (e.g., a 93% certainty of pollutant contamination
in a given area). With Crystal Ball, you can quickly run spreadsheet
simulations and view and change the input assumptions, helping
your managers and peers to visualize your methods and understand
your results. And by quantifying and explaining your operational
risks, you can begin to foster results-driven discussion and improve
the confidence in strategic decisions.
With Crystal Ball, you can:
- Replace min/max estimates with more accurate range of all possible outcomes
- Reduce the time required to produce estimates,
- Eliminate multiple manual “what if” estimates,
- Mitigate your cost and schedule risks,
- Gain immediate insight to the driving inputs and output variations,
- Make knowledgeable decisions on where to focus resources, and
- Provide decision-makers with factual data that shows the risk associated with each choice.
LEARN MORE ABOUT CRYSTAL BALL FOR GOVERNMENT AND POLICY APPLICATIONS
This page offers links to a growing number of resources, including recorded Web seminars, articles, white papers, case studies, and example models. Additionally, you can view a list of common uses and examples reported directly from customers using Crystal Ball. You can also download a free trial version of Crystal Ball to see how it can help improve your business forecasts and decisions!
"Within 5 minutes of opening the box,
I was successfully running Monte Carlo Simulations -- Great
user interface."
-- Alan Barta, U.S. Dept. of Agriculture |
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RECORDED WEB SEMINARS
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Assessing Uncertainty and Risk in Government Acquisition
US Government Agencies are implementing policies designed to assess risk in the acquisition process in an effort to prevent program failure and avoid cost and schedule overruns. More recently, agencies such as the Air Force and NASA are asking for cost estimates at specific percentiles (e.g., 70th percentile for cost) for budgeting purposes. This requires knowledge of the probabilistic outcomes of the program or project and, in particular, knowledge of the shape and statistical parameters for an S-curve (cumulative distribution). While this is a positive step, the Government and their contractors (in general) still have fuzzy understanding of the difference between uncertainty and risk.
In this presentation, we will first define uncertainty and risk and show risks can occur in any of these interrelated areas: cost, schedule, and performance. Second, we will show problems with risk analysis processes that may be encountered in the acquisition process. Third, we will present alternate views of risk relationships that can provide a framework for more successful risk assessments. Fourth, we will identify risks found in Government acquisition and finally, we will show how to quantify uncertainty and risk in Crystal Ball.
At the end of this one-hour session, you will have developed an understanding of:
- The relationship between uncertainty and risk
- How to identify problems with risk analyses and how to “fix” them
- Types of risk faced in Government acquisition, their potential causes, and a framework for assessing uncertainty in risk analysis
- How to quantify uncertainties and risk using Crystal Ball
Presented by Ray Covert, Technical Director at MCR, LLC.
Recorded June 2, 2008
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View recording
Download files
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Simulation in an Alien Environment: How to Help Public Bodies Apply Risk Analysis
English municipalities now have a system of tradable permits that involves risk and uncertainty within the management of waste. Learn how Urban Mindes introduced Monte Carlo simulation methods to the deterministic economic model developed by the UK Government model to help manage risks.
Presented by Glyn Jones, Environmental Economist with the not-for-profit consultancy, Urban Mines
Recorded November 7, 2006
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View recording
Download files
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Simulation and Water Supply Forecasting
Demonstrates how to use Monte Carlo simulation and regression methods to develop better water supply forecasting models in the American West. He will present and comment on a variety of case studies of canal companies in Colorado.
Presented by John McKenzie, founder of Innovastat Corporation
Recorded March 20, 2007
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View recording
Download files
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Global Warming – Will We Bake or Not?
This seminar shows a Monte Carlo simulation model that forecasts global temperature increase by 2100 using both a linear and logarithmic relationship between CO2 concentration (independent variable) and temperature (dependent variable).
Presented by Gaetan ‘Guy’ Lion, Vice President, Planning and Analysis
Recorded July 19, 2007
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View recording
Download files
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WHITE PAPERS
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Basic Cost Risk Analysis: Using Crystal Ball on Government Life Cycle Cost Estimates
R. Kim Clark, Associate, Booz Allen Hamilton
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Download |
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Cashing in on Cable: Warning Flags for Local Government
By David Tuerck, Jonathan Haughton, James Angelini, John Barrett, all of The Beacon Hill Institute at Suffolk University. The above link leads to a press release summarizing the paper,
and a link to the PDF version of the paper is the bottom of
the page. |
Download |
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Crystal Ball in the Rain Forest
By John Reid, Conservation Strategy Fund |
Download |
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Quantifying Financial Risk in a Business Case
Michael Lionais, CMA, Manager Strategic Costing, Agriculture and Agri-Food Canada

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Download |
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Using Monte Carlo Simulation in Life Cycle Assessment for Electric and Internal Combustion Vehicles
By David L. McCleese and Peter T. LaPuma, Air Force Institute of Technology, Wright-Patterson Air Force Base, OH |
Download |
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Using the Value Measuring Methodology to Evaluate Government Initiatives
Kevin Foley, Associate, Booz Allen Hamilton

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Download |
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CASE STUDIES
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EXAMPLE MODELS

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Risk in Financial Forecasts Application
for Valuation, Strategic Planning and Capital Appropriation Decisions
From: David T. Hulett, Ph.D., Principal, Hulett & Associates
LLC, Project Management Consultants, 12233 Shetland Lane, Los Angeles,
CA 90049 www.projectrisk.com
Detail: Financial forecasts are notoriously uncertain.
This model is a simple and clear demonstration of how to use Monte
Carlo simulation to calculate the IRR of a project over a five-year
period. The description worksheet discusses the details, assumptions,
and results of the model. The model is (c) 2000 International Institute
for Learning. |
Download
For:
Crystal Ball
Level:
Simple-moderate |
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Budget-constrained Project Selection
Detail: The problem is to determine which projects to select
to maximize the total expected profit while staying within the budget
limitation. Complicating this decision is the fact that both the
expected revenue and success rates are highly uncertain. Includes
optimizations setting file. Uses binary decision variables for Yes/No
decisions and uses the certainty statistic for optimizing the values
observed between two endpoints. |
Download
For:
Crystal Ball & OptQuest
Level:
Simple |
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Cost Estimation Model
Detail: This model is a simplified cost estimating tool
for a project manager to understand the cost risks for a project. |
Download
For:
Crystal Ball
Level:
Simple |
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Capital Investment Analysis for
Two Industrial Plants
From: Egberto Lucena Teles, accountant, master in accounting,
academical professor - Universidade Mackenzie (São Paulo, Brasil), egberto@mackenzie.com.br
Detail: New projects can involve the acquisition of capital
goods - tangible assets of long useful life as lands, immobile or
machines and industrial equipment. Considering a proposed project
of capital investment, the investors should evaluate the expected
future cash flows in relation to the amount of initial investment.
The objective of the analysis through the method of discounted cash
flows is one of finding projects that have a net present value (NPV)
positive.
In the proposed example, the financial director should make a decision
of capital investment in a new industrial plant. The excluding alternatives,
that will call Plant A and Plant B, involve a cash flow of a period
of six years. The Old Plant (Current) generates a cash flow to present
value of $38,211,000. Besides verifying which Plant (A or B) offers
Cash Flow Increment in relation to Current Plant, this model tests
the implicit risk with relationship to expected return (cash increment).
Two models are included, one for each Plant. |
Download
For:
Crystal Ball
Level: Simple-moderate |
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Critical Path / Time to Market
Analysis
Detail: This model can be used to analyze a project schedule
or the time it would take to get a product to market. The goal of
this model is to understand the uncertainty of when the project
will finish and how often a step will fall on the critical path. |
Download
For:
Crystal Ball
Level:
Simple |
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COMMON USES & EXAMPLES
The following examples were provided by our customers and represent
only some of the potential goverment-related applications for
Crystal Ball.
- Analyse cost risks for Private Finance Initiative (PFI) projects
- Applying Uncertainty Analysis to radiation doses received by individuals exposed through various means
- Bond valuation
- Calculate ingestion rates for environmental impact study
- Cash Flow Valuation of Coal properties
- Cost estimation of US Army operations
- E-Government initiative alternative analysis
- Explore the effect of variability and inaccuracies in estimates
of future loads and generation capability on the operation of
the electricity network
- Forecast cargo and passenger arrivals
- Forecasting economic impact of proposed economic development
project
- Global sensitivity analyses and model selection tournaments
- Homeland security research
- Human health risk assessment modeling for hazardous and radioactively
contaminated sites
- Investigate how frequently different discharge activities
would result in violations of water
quality standards
- Life cycle cost projections
- Manage the annual multimillion dollar IT portfolio
- Modeling fish populations and commercial fishing capture rates
- Oil and gas reserves analysis
- Performance assessment of HLW disposal
- Probabilistic Exposure Assessments
- Program management and decision analysis, defense applications
- Quantitative estimates of geothermal resources
- R&D for metallurgical engineering
- Repeated measures simulations in conjuction with customized probabilistic and graph-theoretic modeling
- Risk/return analysis of proposed IT investments
- Risk and uncertainty in assessing invasive species
- Risk assessment of research portfolio
- Software development project cost forecasting
- Uncertainty quatification for a groundwater/vadose zone contamination
model
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