In the last few months, nearly 1,000 professionals from around the world have gathered to push the boundaries of risk analysis through the Palisade Risk Conference series. Since March, Palisade Risk Conferences have been held in Santiago, Chile; São Paulo, Brazil; Johannesburg, South Africa; Tokyo, Japan; and Shanghai, China. Decision makers from industry and academia have presented dozens of real-life case studies, applying sophisticated quantitative techniques in new and exciting ways. These innovative approaches use Monte Carlo simulation, optimization, decision trees, and other techniques found in Palisade’s @RISK and DecisionTools Suite software to solve a wide range of pressing problems.
Some examples include:
Using stochastic modeling for financial analysis in the mining industry Presented by Collahuasi Mining Co
Assessing the financial viability of new projects Presented by the Brazil National Development Bank
Risk assessment of capital projects in the power industry Presented by PricewaterhouseCoopers
Achieving optimal inventory levels to minimize cost Presented by Mitsubishi Chemical Company
Risk assessment of food safety imports Presented by the Shanghai Food and Drug Administration
Probabilistic risk analysis of cross-border oil projects Presented by Sinopec
Join us next week in London and Frankfurt! Upcoming dates:
The current version of @RISK and the DecisionTools Suite, version 6.1, has now been fully translated into Spanish, Portuguese, French, German, Japanese, and Chinese. The user interface, example models, video tutorials, and complete help files and user manuals have all been carefully translated. Users can specify the language at install, and even change languages later -- all from the same installer. This is a major benefit to multinational companies seeking to roll out a single risk analysis standard around the world.
@RISK and DecisionTools Suite Maintenance Update
In addition to the language translations, a maintenance update to @RISK and DecisionTools Suite software has been released, version 6.1.2.
"Contrary to what may seem obvious on the surface, the driving force behind risk analysis is not statistics, simulation or intricate mathematical models – it is actually much simpler than that. To put it in basic terms, risk analysis is the acknowledgement that there is uncertainty over the assumptions of the project. Statistics and simulation are only tools that help model this uncertainty, and only when we recognize uncertainty over the assumptions of a project can we begin to consider appropriate actions and mitigation strategies."
Rafael Hartke is an Oil and Energy Industry Consultant at Palisade Corporation, where he assists in the development and strategy of quantitative risk analysis methods geared towards the energy industry. He also served as a Financial Engineer in Risk Management at Brazilian-based energy corporation, Petrobras, where he created risk models for complex investment projects and assessed project risks for medium and large projects, including Brazilian Pre-Salt giant fields, projects in the Gulf of Mexico, and offshore infrastructure projects. Palisade Corporation is the provider of the world’s leading risk and decision analysis software, @RISK and the DecisionTools Suite.
With flooding an increasing threat to coastal residents north of Sydney, Australia, @RISK software was employed by engineering firm AECOM to model the risks and benefits of various preventative measures. AECOM was engaged by the Australian Department of Climate Change to undertake an economic analysis of climate change impacts on infrastructure through the development of a series of case studies. These studies will be used to inform the Australian government’s discussion on policy responses to the risk that climate change will increase infrastructure investment and maintenance costs. In this case, the area of study was the increased risk of flooding from Narrabeen Lagoon in the northern Sydney local government area of Pittwater. Read more.
"Using [DecisionTools] software applications allows me to focus on teaching problem solving (what analysis to run, what assumptions to make, what inputs to use, and how to interpret the results), rather than the computational aspects, which would otherwise take up most of the class time. This is especially important in the fast-paced half-semester courses we now use." Dr. Joe Hahn, Pepperdine University
What will be the effect of a new health policy in a country?
How do we quantify and mitigate health risks in our food supply?
Should we allow imports of a certain agricultural product?
Quantitative risk analysis techniques can help you answer these and many more questions. A new postgraduate certificate program in Risk Analysis in Health and Food Safety is being offered by EpiX Analytics and the Royal Veterinary College (RVC), University of London. “People interested in risk analysis in health and food safety come from a variety of backgrounds, so it was important for us to use software that is not only statistically sound, but also user friendly. This is why we chose @RISK as the primary teaching software for this course,” said Dr. Francisco Zagmutt, managing partner of EpiX Analytics and one of the course instructors.
This course will use many examples and case studies to provide participants with the skills for cutting-edge quantitative risk analysis in health and food safety. The course is designed to accommodate the work schedules of professionals from research institutions, governmental and international agencies; agricultural, food, pharmaceutical and related industry; and academic staff and post graduate students.
PricewaterhouseCoopers put together a beautiful video about the Corridor Budgeting program, developed by Tobias Flath and Michael Hofmann. Corridor Budgeting is a methodology combining planning, business management, and risk management in order to prepare for a range of possible outcomes, and thereby generate a more realistic picture of the future.
Palisade's DecisionTools Suite is an integral part of this program. As explained in the video: "We identify the factors underlying variables and ranges that impact on financial results. The Corridor is regularly analyzed and validated, giving visibility into any gaps or delta between target bandwidths and actual figures. Specially designed software then aggregates these bandwidths and event risks to paint an accurate picture of possible scenarios."
The video depicts modeling with Monte Carlo simulation: "A simulation models the total risk exposure. The width of the curve indicates the level of uncertainty. The height shows the likelihood that an event will occur, giving senior executives insights into the full spectrum of future possibilities, and making it easier to make the right decisions."
The video concludes, "Corridor Budgeting allows businesses to forecast more realistically, and prepare more effectively for what's to come, equipping them to face the future, however it turns out." It's a simple and beautiful explanation of how risk and decision analysis are a central part of business decisions today.
All DecisionTools Suite products now include revised and updated example files, as well as all-new examples in a range of industries. All examples are clearly organized and easy to navigate. These examples have been designed and written by leading MBA professor and author Dr. Chris Albright of Indiana University. They provide step-by-step guidance on setting up and running models to address a wide range of industry applications. In addition, many examples offer short, built-in videos that walk you through the model.
Furthermore, new video tutorials have been developed by Dr. Albright to help new users get started quickly, and to help experienced users get more out of the software.
Quick Start models files and videos
These short, interactive tutorials are designed to teach you how to use DecisionTools software by walking you through an actual model – all under 30 minutes! Build a model step by step, following the simple video instructions provided.
Guided Tour Videos
Guided Tours explain the functionality of each part of the software ribbon in detail. Learn how the features work, improve your efficiency, and avoid errors in your models.
Example Videos
Follow along as experts demonstrate the powerful analytical features of the DecisionTools Suite, and then open the actual risk and decision analysis models. Models are available here, and linked directly from your software.
@RISK (risk analysis software using Monte Carlo simulation) is now a truly cross-platform tool, enabling risk modeling of your Microsoft Project schedules using the same @RISK you use for risk analysis modeling in Microsoft Excel! You can now do your project risk modeling in Excel rather than Microsoft Project, providing a new world of flexibility. A new interface layer reproduces your schedule in Excel, enabling you to use all Excel formulas and @RISK functions. When you make changes to your model in either Project or Excel, those changes are reflected in the other with @RISK’s Sync feature. (Note that all @RISK modeling takes place in Excel, so @RISK functions do not appear in Microsoft Project.) Then simulate your Project schedules in Project itself, using Project's scheduling and calculation engine.
The benefits of using Excel for your Project risk modeling are many. You can easily build risk registers in Excel for your Project model using new “RiskProject” functions. You can integrate your cost and schedule analyses. You can standardize on a single tool – @RISK – to meet the needs of your project managers, cost estimators, finance analysts – everyone who deals with risk and decision making under uncertainty in your company. Plus, a single interface means a shorter learning curve for everybody.
@RISK is part of The DecisionTools Suite -- an integrated set of programs for risk analysis and decision making under uncertainty that runs in Microsoft Excel.
The ongoing debate about the feasibility of offshore windfarms as a renewable energy source continues to generate discussion and headlines.
A key issue for potential operators is that offshore windfarms face more adverse weather conditions, such as higher wind speeds and the increased risk of being struck by lightning, than their onshore counterparts. In addition, a failed offshore turbine may take several months to repair, rather than a few days. The financial implications of repair and downtime must therefore be factored in to any calculations related to the feasibility of the operation.
This is made more difficult due to the inherent level of uncertainty involved. For example, the nascent nature of the industry means there is a shortage of historical data on the failure frequencies of the turbines. Even information that is available is subject to uncertainties – such as the prices of crane ships and access vessels (which may vary per season and even from day-to-day), the cost of spare parts, and the electricity price, as well as the lead times of spares and vessels.
However, using @RISK (Palisade's Microsoft Excel software add-in for risk analysis using Monte Carlo simulation) for probabilistic analysis, the Energy Research Centre of the Netherlands has developed an innovative approach to determine whether offshore wind farms are financially viable from an operations and maintenance perspective. The @RISK risk simulation software model produces a distribution that determines the uncertainty associated with the downtime and maintenance costs of an offshore wind farm. This enables a project developer to make an informed decision, firstly as to whether to proceed with the project and then, if this is affirmative, the best way to do so.
Measuring the uncertainty also helps to make the project more viable in terms of financing. With the help of @RISK, wind farm developers – and their potential investors – can make informed decisions about whether an offshore operation will offer a good return on investment.
Alternative Energy eMagazine interviewed Randy Heffernan, Vice President of Palisade, for the June/July 2012 issue. Questions addressed in the interview include:
What is risk analysis? How does it work?
How can companies in the energy industry use risk analysis?
Is there a minimum project budget that you would consider to begin to benefit from risk analysis?
What are some of the benefits of analyzing risk early on?
At what stage of a project do you recommend starting the risk analysis, who should be involved and where does the data come from?
What are the costs involved with risk analysis?
Can you share some examples to illustrate how risk analysis can be an important tool for analyzing the success of clean energy projects?
The article highlights FutureMetrics' use of @RISK to hedge wood prices in the production of burning wood pellets. Based in Bethel, Maine, FutureMetrics is recognized as one of the leading domestic experts in the economics of the production and use of renewable bioenergy.
Today, the global consumption of wood pellets is approximately 15 million tons per year. It is expected to exceed 45 million tons by 2020. The largest market for wood pellets exists in Europe, where regulations encourage the use of carbon neutral fuels, like biomass. With such a dramatic jump in global wood pellet consumption predicted in the future, FutureMetrics and INRS, via their partnership in FutureEnergy Partners developed a wood price hedging product that uses @RISK to measure its effectiveness.
“I have been using @RISK since the early 1990’s, so I have a perspective on the commitment to the users that the Palisade team has,” said Dr. William Strauss, president and founder of FutureMetrics. “Every new version has new and very useful features that often are based on feedback from users. Palisade’s @RISK software has the richest feature set and has the most relevant tools for analyzing models that contain uncertainty.”
The legacy of apartheid in South Africa has left much of the country without basic services such as housing, water and electricity. The government initiatives in place to tackle the issue do not have enough resource to meet the scale of the need so commercial finance programmes will play a key role in delivering these services. But poor planning without enough information makes it difficult to recoup the costs of a project, thereby making it unattractive to potential commercial financers – in other words, ‘unbankable’.
For example, an engineer might design a high-specification water system. However, the focus on design may make it over-complex and therefore expensive – with the end result that it does not meet the needs of the community, the government or the financing organisation.
Bigen Africa, a consulting company that describes itself as a ‘development activist’, tackles this issue with risk analysis. It uses @RISK as a tool to enable it to identify, manage and mitigate the risk associated with each project and ensure it attracts funding and is successful.
@RISK risk modeling software helps Bigen Africa to understand and demonstrate that it is the number and type of houses that drives the demand for services, where this demand is, what it will be in the future and who will use the services. It forms the basis of engineering / planning, the financial risk analysis model, the revenue model and strategy, affordability analysis and the integration between the services (housing, roads, solid waste, water, sanitation, electricity, etc).
@RISK provides the level of detail that banks require before making a decision on whether to finance a project. At the same time, the methodology benefits from simplicity and is easily understood by the wider audience involved in the project but not necessarily familiar with the specific concept of demand risk.
Beta 2 of Palisade’s new DecisionTools Suite 6.0 risk and decision analysis software is now available for download. Beta 2 includes the new time series simulation feature in @RISK 6.0, which allows you to model and simulate values that change over time. This is particularly useful in financial modeling and portfolio simulation.
Integration with Microsoft Project for simulation of Project schedules
Easier-to-understand double-sided tornado
Better distribution fitting
The DecisionTools Suite 6.0 is offers new versions of all products in the Suite: @RISK, PrecisionTree, TopRank, NeuralTools, StatTools, RISKOptimizer and Evolver.
As every risk manager knows, however good a risk-based model, the validity of the forecasts it makes is dependent upon the quality of the input data. One approach to obtaining assurance that forecasts from Monte Carlo analysis are realistic is to measure the capability of the risk management process that has been used to produce risk models.
The Project Risk Maturity Model (RMM) performs this measurement and has been demonstrated to help produce risk models that result in realistic forecasts (including models using Palisade’s risk analysis software, @RISK).
For example, the UK’s Ministry of Defence (MoD) equipment projects include the development and manufacture of new military equipment for the UK’s Army, Royal Navy and Royal Air Force. Risk is often increased on these large and complex projects by objectives that tend to push the limits of technical feasibility. As a result, the MoD is highly committed to its project risk management process.
However, in 2001, the MoD recognised that too many of its projects ran late and over budget. It traced this to over-optimistic risk analysis forecasts in the early stages, leading to projects passing approval points without adequate scrutiny. This realisation prompted the MoD to invest in the Project RMM. As a result, risk models used for project approvals became more reliable and realistic.
This is useful insight for @RISK users, because it enables them to check that the process used to develop their input data has been good enough to support their model. As a result they can be confident of their predictions – regardless of the industry in which they operate.
I attended e-learning micro-event event last week! It’s a great concept being used by Smarter Solutions. The concept is to provide short one hour training classes (“micro-events”) via the web for a very low cost. The micro event I attended was titled, Truly Understanding Hypothesis Testing Concepts: Making a Complex Topic Simple. It truly lived up to its name; ~67% of the participants went away with a better understanding of Hypothesis testing after the hour.
The micro training event was led by Rick Haynes of Smarter Solutions. Rick is an excellent Lean Six Sigma Instructor, Statistical Consultant, Coach and mentor to process improvement practitioners. Rick did an excellent job using the tools at his disposal (even Monte Carlo Simulation using the @RISK software) to make this truly complex topic “simple”.
In case you don’t know, Hypothesis testing is a concept that is taught in Lean Six Sigma and statistics courses. During the event, he walked through the concepts of alpha and beta risk along with power and confidence choices using a completely different method than you would have been taught in a class. Through the use of diagrams and simulations, he made the hypothesis concepts real and understandable. Mr. Haynes, used @RISK was to test the Hypothesis test theory (a t-test), showing how the risk of each hypothesis test decision changed as the initial conditions of the test were changed where most classes just provide graphics and equations. It was a powerful method to teach statistics.
If you are interested in viewing the recording of the micro training event it can be done so for a micro-charge of less the $25! If you do, please let me know your thoughts.
Join us this Thursday, February 16, 2012, for a free live webcast entitled, "How Capable are Your Capability Metrics? Using @RISK to Demonstrate Their Limitations," to be presented by Rick Haynes.
In the field of Six Sigma, there is a lot of discussion about the applicability of the traditional capability metrics. Cp, Cpk, Pp, and Ppk are very popular in some areas, but not all truly understand what the metric is trying to communicate about the process. In this free live webcast we will take a look at a typical data set to see how the capability index (Cpk) is reported based on different assumptions and calculation methods using risk analysis and Monte Carlo simulation software @RISK.
At the end of this webcast you will fully understand the usage of Cpk in regards to:
Normal vs. non-normal data
Stable vs. unstable data
The uncertainty of capability estimates (confidence intervals)
Join us for this webcast, and you will never be confused or lied to by Cpk!
Rick Haynes has more than 20 years' experience in project management, training, applied statistics, engineering, and customer support. He has taught and certified professionals in all Lean Six Sigma areas. His consulting work has included all facets of business; building corporate performance dash boards, developing the Integrated Enterprise Excellence (IEE) system at a manufacturing firm, development of a process management and control system in a manufacturing firm, quality auditing of construction projects, developing reliability models for equipment failures, facilitating executive strategy development efforts, executive leadership coaching, modeling business performance for predictive analysis, improvement practitioner coach. Professional positions include; manufacturing site engineering manager, US Naval Officer (Submarines), corporate process improvement director, DOE research statistician, chemical process engineer, nuclear engineer.
Creating a feasible budget is never easy, but it’s even more challenging during questionable economic times. That was the case for the Arc of Yates, an amazing organization in New York State that provides a wide array of services for individuals with developmental disabilities in Yates County. For many non-profit organizations, funding often comes from local, state and federal sources. Given the current economic climate, Arc of Yates was faced with the prospect of slashed budgets on every governmental level, effectively leaving the organization with a fraction of the funding they have enjoyed previously.
With uncertainties as to where that funding would originate, Arc of Yates utilized risk analysis software @RISK to explore which areas of funding were most likely to be affected. Using probability distributions, Arc of Yates could forecast what portion of the current budget stream may not be available over the next three years. Subsequently, the organization could develop strategies to explore alternative means of funding. Now Arc of Yates has a clear plan of action to meet upcoming budgets for the foreseeable future.
We think Arc of Yates’ use of @RISK is a great example of how Monte Carlo Simulation can empower organizations and lessen the concerns and uncertainties that accompany a struggling economy. Knowing where potential shortfalls may occur offers decision-makers the foresight and flexibility to stay in front of budgetary gaps. On a personal level, it’s great to know that we were able---in some small way---to further the effort of a truly fantastic organization.
Join us this Thursday, November 10, 2011, for a free live webcast entitled, "Petroleum Resource Evaluation Using @RISK" to be presented by Dr. Ronald Brimhall.
This free live webcast contains instructions and demonstrations for using @RISK risk simulation software to examine net present value economic analyses for a petroleum resource. In this case, the asset is a low pressure gas reservoir. The main applications of @RISK cover in detail the spectrum of petroleum engineering analyses – rock and fluid properties, reservoir volumetrics, material balance, analogy, decline curve, and net present value. Microsoft Excel statistics spreadsheets with @RISK are the primary analysis tools. Basic principles are emphasized with the understanding that fundamentals may be applied to the entire spectrum of reservoir oil and natural gas assets in cases where variability and uncertainty in all relevant parameters are important.
Variability in rock properties are demonstrated by analysis of electric logs, Variability in original gas is place in demonstrated by comparing volumetric analysis and material balance for generalized reservoir (includes water influx and water production). Application of decline curve analysis with uncertainty in decline rate is applied to NPV analysis. A result of reserves determinations and NPV is compared with an alternative investment opportunity.
Dr. Brimhall’s experience covers 50 years in industry and in academia. He was part of the Petroleum Engineering Faculty at Texas A&M University, and maintained a professional practice related to formation evaluations, resource evaluations, log and pressure transient analyses, production operations for oil, natural gas and groundwater, as well as environmental and resource assessments for subsurface operations in energy and groundwater resources. His past project management experience includes business development as well as proper utilization of environment & natural resources.
Understanding how to use Monte Carlo simulation to account for risk in decision-making is quickly becoming a required skill for today’s business leaders, says Asher Drory, Adjunct Professor of Finance at University of Toronto’s Rotman School of Management.
“Many leading corporations are now using Monte Carlo simulation in their business cases,” Professor Drory says. “Students who want a leg up with such corporations should seek out all opportunities to get experience in working with Monte Carlo simulation.”
In his Financial Management course, Drory uses @RISK to teach some 200 graduate students each year how to use Monte Carlo simulation in analyzing working capital and capital budgeting decisions. Monte Carlo simulation furnishes the decision-maker with a range of possible outcomes and the probabilities that will occur for any choice of action.
For example, Drory's classes use @RISK and Monte Carlo simulation to look at:
How forecasts of financial statements are needed to determine future funding requirements in working capital decisions.
How forecasts of future free cash flows are required and risk must be assessed in capital budgeting analysis.
Separately, Drory and his students use Palisade’s PrecisionTree software in modeling decision tree analysis for new product development. The students have access to the entire DecisionTools Suite which is loaded on all of the computers in the Rotman Finance Laboratory.
“All key financial decisions such as investing, operating and financing decisions can benefit from Monte Carlo simulation,” says Prof. Drory, who has taught at the University of Toronto for 21 years. “I ran across @RISK about 5 years ago when I was looking for PC-based Monte Carlo simulation tools. @RISK has a straightforward and easy-to-use interface.”
Some examples include:
The legacy of apartheid in South Africa has left much of the country without basic services such as housing, water and electricity. The government initiatives in place to tackle the issue do not have enough resource to meet the scale of the need so commercial finance programmes will play a key role in delivering these services. But poor planning without enough information makes it difficult to recoup the costs of a project, thereby making it unattractive to potential commercial financers – in other words, ‘unbankable’. 
In case you don’t know, Hypothesis testing is a concept that is taught in Lean Six Sigma and statistics courses. During the event, he walked through the concepts of alpha and beta risk along with power and confidence choices using a completely different method than you would have been taught in a class. Through the use of diagrams and simulations, he made the hypothesis concepts real and understandable. Mr. Haynes, used @RISK was to test the Hypothesis test theory (a t-test), showing how the risk of each hypothesis test decision changed as the initial conditions of the test were changed where most classes just provide graphics and equations. It was a powerful method to teach statistics.
Creating a feasible budget is never easy, but it’s even more challenging during questionable economic times. That was the case for the 
Subscribe to RSS blog feed.
Subscribe to the Palisade
Follow Palisade on LinkedIn 
Become a fan of the Palisade 
Follow Palisade on Twitter.
Follow Palisade on Google+
View the Palisade 
