Exploration and Production

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.

For those who want to find out more, further details about the Project Risk Maturity Model and its lead developer, Martin Hopkinson, are in the case study on our website.
 

Dr. Jose A. Briones of SpyroTek Performance Solutions recently gave a Palisade webcast presentation, using the success of Apple’s iPad as a working example, in "Use of @RISK for Quantifying Uncertainty in Innovation Project Management."

Product innovation has been described as the way out of today’s difficult business environment. However, the rate of success of development projects — in particular white space or disruptive innovation projects — remains too low.

The analysts at SpyroTek believes that a reason for the low success rate of development projects is the erroneous application of analysis methods designed for incremental innovation, such as NPV and DCF, to projects with high levels of uncertainty.

In the presentation, Jose discusses the use of @RISK and Probabilistic Decision Analysis in the management of innovation projects with high levels of uncertainty. Probabilistic decision analysis, when combined with the right management processes like Discovery Driven Planning, is a very effective approach to evaluate and manage the risk and potential of innovation projects.

» Watch "Use of @RISK for Quantifying Uncertainty in Innovation Project Management"
» View related slides from Dr. Briones

Join us this Thursday, Janurary 12, 2012, for a free live webcast entitled, "Refining the Business Case for Sustainable Energy Projects Using @RISK and PrecisionTree: A Biofuel Plant Case Study" to be presented by Scott Mongeau.

The sustainable energy industry sits at the nexus of growth and change: the popular groundswell for ‘green initiatives’, ongoing debates concerning global warming / climate change, fickle government incentives, the quest for renewable and alternative sources, expansion in developing economies, and the rapid emergence of new technologies. Sustainable energy industry sectors such as biofuel, solar, wind power each have unique selling points as well as practical challenges.  Across the board, profit margins are uncertain and tight, demanding detailed analysis and complex business cases.  Palisade's DecisionTools Suite is an ideal vehicle for conducting the deep risk analysis needed to separate the hype and ‘wishful vibes’ from the real risks and tangible profit cases needed to ‘green light’ sustainability projects.

Sustainable energy’s central competitor and sometimes partner, the petroleum majors, have distinct advantages, having established, streamlined supply chains and being embedded into the global economy.  However, traditional petroleum exploration is going to increasingly extreme and risky lengths to locate and exploit new reserves (i.e. Athabasca Oil Sands, deep sea drilling, project development in politically unstable regions).  The petroleum majors are dedicated users of the Palisade DecisionTools Suite to make their increasingly complex and risky business cases.

This free live webcast asserts that an energy development ‘risk / reward parity’ level is growing between new petroleum exploration and production and sustainable energy initiatives.  The presentation uses a biofuel plant case study as an example of how a profitable business case can be made for a sustainable energy project using techniques commonly applied in petroleum exploration and engineering initiatives.  The biofuel industry is expected to multiply its production by a factor of 50 by 2020.  The uncertainties of government subsidy, tax credits, and loan guarantees are crucial to meeting biofuel profit margins. Stochastic statistical analysis greatly improves the ability to pinpoint risk and to identify mitigation strategies. The case study uses @RISK to model biofuel project NPV, Evolver to suggest plant optimization strategies, and PrecisionTree to guide strategic decision making. The approaches presented have promise as a due-diligence tool for prospective sustainability entrepreneurs, investors, project managers, and firms. 

Scott Mongeau is Lead Consultant and Founder of Biomatica BV (biomatica.com), a niche consultancy specializing in biotechnology industry risk management. Scott has over a decade of experience in biotech, including key positions at Genentech Inc. related to risk management. He currently consults for several biofuel start-up initiatives and completed his thesis on biofuel project risk management. In addition to consulting, Scott is a part-time PhD researcher in the Executive Doctorate Program at Nyenrode Business University in the Netherlands. He holds a Global Executive MBA (OneMBA) and Masters in Financial Management (MFM) from the Erasmus Rotterdam School of Management (RSM). Additionally, he holds a Certificate in Finance from University of California at Berkeley, a Masters in Communication from the University of Texas at Austin, and a Graduate Degree in Applied Information Systems Management from the Royal Melbourne Institute of Technology as a Rotary Ambassadorial Scholar. Having lived and worked in a number of countries, Scott is an American citizen and currently consults and conducts research from his office in Leiden, Netherlands.

» Register now (FREE)
» View archived webcasts

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.

» Arc of Yates case study
» Take a look at the great work Arc of Yates is doing.

Randy Heffernan
VP, Palisade Corporation

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.

» Register now (FREE)
» View archived webcasts

Join us this Wednesday, October 19, 2011, for a free live webcast entitled "Modeling Oil & Gas Risk Problems using The DecisionTools Suite" to be presented by Rishi Prabhakar.

In today’s industry getting oil and gas safely and efficiently to the surface is a significant challenge. Oil & Gas problems and decisions are beset by uncertainty in all areas: production forecasting, reserves estimation, calculating exponential decline, scheduling, etc. There are many complex options for strategy and operations. The DecisionTools Suite has been used successfully throughout the entire value chain in the Oil & Gas industry.  This webcast will feature some of the common problems and solutions addressed effectively by the DecisionTools Suite.

Rishi brings a broad range of experience and expertise to the Palisade team. He has worked in and consulted to the energy industry, telecommunications, scientific research, banking and finance with an emphasis on operational risk and Basel II. Rishi has expert skills in the areas of statistical analysis, simulation, time series forecasting, risk/capital modelling, extreme value theory, survey design and analysis. He holds a BSc Mathematics from the University of Technology, Sydney.

» Register now (FREE)
» View archived webcasts

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.”

» More about Professor Asher Drory
» More about @RISK

For their capstone design projects, undergraduate mining engineering students at Missouri University of Science and Technology develop “real-world” solutions. So, Dr. Samuel Frimpong provides his students with real-world tools, including Palisade’s @RISK software.

Similarly, he uses @RISK to help graduate students undertake research projects in geology and geological engineering, mining and petroleum engineering.

Dr. Frimpong says the risk analysis software helps students with risk modeling for everything from investment to production. Projects might include production forecasting, reserve estimation, exponential decline, and other key areas. @RISK also helps students understand stochastic processes – how random events can affect engineering phenomena over time.

“@RISK offers a comprehensive package for simulating stochastic processes defined by parametric probability and statistics,” says Dr. Frimpong, who has been teaching at the Rolla, Mo.-based university for more than 6 years. “The Excel environment also makes @RISK user-friendly.”

He also praised the software’s “efficient pre-simulation definition of input variables and post-simulation results.”

Dr. Frimpong says he has been using @RISK since his time at University of Alberta, Edmonton, Canada, where he completed his PhD in 1992 and later served as an associate professor of mining engineering.

A native of Ghana, Dr. Frimpong holds several patents in the area of oil sands extraction and is a noted expert in mine design, mineral economics, modeling methods and operations research.

» More about Dr. Samuel Frimpong
» More about @RISK

Today a moderately powerful earthquake rattled Washington, D.C. and was felt as far north as Massachusetts. Sitting here, feeling the earthquake shake my desk and water glass in central New York State, hundreds of miles from the epicenter, I was reminded that we are never far from the risk of natural disaster.

The Washington Post’s Jason Samenow wrote today that aftershocks are a significant concern. Although the 5.9 magnitude quake did not appear to cause significant damage, earthquakes are rare in the region and people are ill-prepared for them. According to the Post: “McNutt, director of USGS expressed a concern that the earlier quake will precede something more powerful: ‘What the concern is, of course, is that this is a foreshock. If it’s a foreshock, then the worse is yet to come.’ If not a foreshock, Mike Blanpied, associate coordinator for the USGS earthquakes hazards program cautioned aftershocks are possible: ‘Aftershocks could go on for days, weeks, or even months. They’re most likely to be felt under the next three or four days.’”

It got me thinking to ways that risk and data analysis techniques that we use every day in business applications could be applied in this situation. After all, the use of Monte Carlo simulation and and decision trees in DecisionTools Suite software has been used to cope with natural disasters – from volcanoes to hurricanes.

A few years ago the US Geological Survey asked the same question in an interesting study on the use of Monte Carlo simulation for the prediction of aftershocks in California. The paper, published in 2008, notes the typical absence of data specific to a particular earthquake site and examines the usefulness of Monte Carlo simulation for “assessing recurrence from limited paleoearthquake records.” In the absence of data, Monte Carlo simulation can be quite effective.

In a similar situation, the use of neural networks was examined by researchers in China to get a handle on the risk of aftershocks from the enormous 2009 Sichuan province quake. In their paper, published by the Journal of Sustainable Energy and the Environment in 2009, data from initial aftershocks was provided to a neural network so that it could “learn” any patterns in the aftershocks. These patterns were then used to predict future tremors. The concentration and trend of the aftershocks was predicted “precisely,” according to researchers.

In science as well as business, quantitative risk and decision analysis techniques produce tangible benefits that directly impact many of us.

Randy Heffernan
VP, Palisade Corporation

In the August 16, 2011 edition of the New York Times there was an interesting article about the use of predictive analytics by police departments. Entitled “Sending the Police Before There’s a Crime,” the article explores how the Santa Cruz, California police department optimizes the use of limited resources by anticipating where crimes are more likely to occur so they can deploy police there in advance. How does it do this? According to the article:

“Santa Cruz’s method is more sophisticated than most. Based on models for predicting aftershocks from earthquakes, it generates projections about which areas and windows of time are at highest risk for future crimes by analyzing and detecting patterns in years of past crime data. The projections are recalibrated daily, as new crimes occur and updated data is fed into the program.”

This may sound like science fiction technology, but the model Santa Cruz is using is exactly what neural networks do.  Neural networks are an artificial intelligence data analysis technique that identifies patterns from historical data and uses those patterns to predict new outcomes when presented with current partial data.  

It’s the same technology that shuts off your credit card when it’s stolen and someone uses it to buy ten 60-inch TVs in another country.  In that case, the credit card company has established spending patterns from your purchasing history, and when a transaction appears that falls outside that pattern, a neural network assesses the probability of fraud. If the probability is high enough, the card is blocked.

The applications for neural networks are limitless. They have been used for medical diagnosis, commodities price prediction, patient load forecasting in hospital, and much, much more. You can read examples of examples of interesting neural network applications using NeuralTools, a leading neural networks tool for Excel, here.

Santa Cruz’s efforts are being monitored and copied by other major metropolitan forces such as the Chicago and Los Angeles police departments. Such analytics could prove to be a major tool in the resource-strapped battle against crime for years to come.

» NBC Nightly News video: "New police motto: To predict and serve?"

Join us on Thursday, August 25, 2011, for a free live webcast delivered by Tim Robinson and David Wilson, entitled "Use of Simulation Models in Pricing Health Insurance and Reinsurance Risk."

While healthcare claim costs are fairly predictable for large populations, existing pricing models often prove inadequate for that portion of the risk that is the most variable: large or “excess loss” claims typically covered by employer stop loss and other forms of reinsurance for high-cost claims. Even when rating and underwriting applications are able to accurately forecast expected claim costs, they are typically not structured to measure the variability in such claim costs from year to year. This is problematic when conducting detailed enterprise risk assessment studies or estimating capital and surplus requirements for health insurance programs. This webcast will illustrate some applications of @RISK risk modeling software to solving these problems. Examples will include Monte Carlo simulation models designed to quantify capital and surplus requirements for a health reinsurance captive; simulation models designed to price aggregate employer stop loss insurance; and simulation models designed to price aggregating specific or “inner aggregate” corridors in employer stop loss insurance.


Tim Robinson has over 20 years of experience as a healthcare actuary. He has a broad range of actuarial, underwriting and management experience working with diverse organizations including reinsurers, insurance companies, disease management firms, health plans and employer groups.  Tim has worked most recently on developing innovative healthcare rating and underwriting models; strategic and analytic support for a variety of start-up health insurance programs; and underwriting applications of predictive modeling and large claims analysis.  He also has extensive experience with product development, pricing, underwriting and valuation work for insurers and plan sponsors.  Tim is a Partner with Windsor Strategy Partners, LLC.  He works with clients in the healthcare industry, directing actuarial and strategic analysis in support of their risk management goals and initiatives.

David Wilson is the founder and President of Windsor Strategy Partners. Windsor Strategy Partners is a specialized healthcare strategy firm helping clients develop and implement strategic growth and risk management initiatives. WSP’s clients include leading reinsurers, insurers, captive insurers, provider organizations, technology companies, employee benefit consulting firms, reinsurance intermediaries and investment groups. David leads the firm’s marketing and research effort and acting as a senior advisor to our clients and partners. David has been active in the health insurance arena for over 30 years. He is recognized as a leading expert in healthcare insurance and reinsurance pricing and underwriting. He is a strategic advisor to start-up and established companies in the health insurance field.

» Register now (FREE)
» View archived webcasts

@RISK is available with companion product PrecisionTree in the DecisionTools Suite. PrecisionTree creates decision trees in Excel to allow you to map and understand the complex decision problems. @RISK functions are recognized by PrecisionTree, and the two may be launched from a common Excel toolbar.

@RISK allows you to:

1. quantify the uncertainty that exists in the values and probabilities which define your decision trees, and
2. more accurately describe chance events as a continuous range of possible outcomes.

Using this information, @RISK performs a Monte-Carlo simulation on your decision tree, analyzing every possible outcome and graphically illustrating the risks you face.

With @RISK, all uncertain values and probabilities for branches in your decision trees, and supporting spreadsheet models, can be defined with distribution functions. When a branch from a decision or chance node has an uncertain value, for example, this value can be described by an @RISK distribution function. During a normal decision analysis, the expected value of the distribution function will be used as the value for the branch. The expected value for a path in the tree will be calculated using this value.

However, when a simulation is run using @RISK, a sample will be drawn from each distribution function during each iteration of the simulation. The value of the decision tree, and its nodes, will then be recalculated using the new set of samples and the results recorded by @RISK. A range of possible values will then be displayed for the decision tree. Instead of seeing a risk profile with a discrete set of possible outcomes and probabilities, a continuous distribution of possible outcomes is generated by @RISK. You can see the chance of  any result occurring.

In decision trees, chance events must be described in terms of discrete outcomes (a chance node with a finite number of outcome branches). But, in real life, many uncertain events are continuous, meaning that any value between a minimum and maximum can occur. Using @RISK with PrecisionTree makes modeling continuous events easier, using distribution functions. Also, @RISK functions can make your decision tree smaller and easier to understand!

» See a short video on using @RISK with PrecisionTree
» Read more about using @RISK with PrecisionTree
» Learn more about PrecisionTree

Presented by Scott Mongeau of Biomatica at the
Palisade Risk Conference in Amsterdam, March 29, 2011

An energy development ‘risk / reward parity’ level is growing between new petroleum exploration and sustainable energy initiatives. This case uses a biofuel plant case study as an example of how a profitable business case can be made for a sustainable energy project using techniques commonly applied in petroleum exploration and engineering initiatives. The toolkit includes risk analysis using Monte Carlo simulation, sensitivity analysis, optimization, correlation, econometrics, decision trees, and real options.

The biofuel industry is expected to multiply its production by a factor of 50 by 2020. The uncertainties of government subsidy, tax credits, and loan guarantees are crucial to meeting biofuel profit margins. Stochastic analysis greatly improves the ability to pinpoint risk and to identify mitigation strategies. The case study uses @RISK to model biofuel project NPV, Evolver to suggest plant optimisation strategies, and PrecisionTree to guide strategic decision making. All of these software tools are part of the DecisionTools Suite.

The approaches presented have promise as a due-diligence tool for prospective sustainability entrepreneurs, investors, project managers, and firms.

» Read the full presentation

Most of Professor Luciano Arantes Rezende Costa’s students at the Brazilian Petroleum Institute work in the local oil industry.

So, when he teaches his 20-hour course on evaluation of petroleum exploration opportunities, he has to provide hands-on lessons his students can immediately apply in their own careers.

That’s where Palisade’s @RISK software comes into play.

"To illustrate the classes, I've created a very simple model in Excel for evaluating exploration opportunities and bidding on them," Prof. Costa says. "Using the flexibility of @RISK, I've included in this model uncertainty about how much petroleum could be found (recoverable volume); how much could be produced by year (production curve); and how much cash flow could be expected from the estimated production."

Prof. Costa speaks from experience. In addition to teaching at the Institute, he works full time for Petrobras, one of the world’s largest integrated energy companies. The Rio de Janeiro-based company currently produces about 2.6 million barrels of oil and natural-gas equivalent a day.

Prof. Costa first encountered @RISK while earning his master’s degree at Colorado School of Mines in 1997. He says @RISK continues to be one of the easiest ways to teach Monte Carlo Simulation, a computerized mathematical technique to account for risk in quantitative analysis and decision-making. "Students can visualize what is going on just by pressing a single button," he says.

"My classes are very practical because students can grasp the concepts easily and use @RISK to create new models for their own real-life problems," Prof. Costa says.

» Learn more about how Petrobras has integrated @RISK into their operations

Recently Brazil-based Petrobras, one of the world’s largest oil companies, implemented a corporate-wide protocol for evaluating the economic risks associated with potential investments. Key risks of interest to the company include those associated with production of oil and natural gas, demand for derivatives, prices of various commodities, and more.

To deal with these risks, Petrobras has integrated @RISK Monte Carlo software for Excel with its in-house statistical analysis software. Using risk analysis solutions enables the company to analyze more complex projects, such as those undertaken with outside partners and those involving multiple concessions (specific drilling areas). In addition, @RISK helps reduce the calculation time for projections that used to take thousands of hours.

» Read more about how Petrobras uses @RISK

New DecisionTools Suite 5.7.1 is a maintenance release that provides fixes and improvements to @RISK and all products in the DecisionTools Suite: @RISK, PrecisionTree, TopRank, RISKOptimizer, Evolver, NeuralTools, and StatTools.  This update is available free of charge for current maintenance holders. As with previous versions, version 5.7.1 is available in English, Spanish, Portuguese, French, German, Japanese, and Chinese. 

Keep your Maintenance Plan current

If you do not have a current maintenance plan, contact Palisade Sales (see info below) for a quote to get up to date on maintenance.

» More information, and get update 

Contact Palisade

This Wednesday from 10:00am to 11:00am ET, Marwaan Karame will present a free live webcast entitled, "The Use of @RISK and Economic Value Added in Business Valuation."

Valuation is a critical part of business decision making, whether it’s to invest in a new technology or to acquire an entire company. Regardless of the investment, there are fundamental principles of finance and economics that determines what something is worth. In this brief introduction, we’ll explore the concepts of Economic Value Added and Free Cash Flow, as well as the key operating drivers of value creation.  In addition, we will quantify the uncertainty that plagues most every business decision by utilizing a superior yet simplistic analysis known as Monte Carlo. Financial risk analysis models will be explored in @RISK (risk analysis software using Monte Carlo simulation).

Marwan Karame is Managing Director of Economic Value Advisors, consulting businesses in the areas of Value Based Management (VBM) and Mergers & Acquisitions (M&A). Previously, Mr. Karame worked in investment banking for Donaldson, Lufkin & Jenrette (DLJ) and Credit Suisse First Boston (CSFB) advising companies in the areas of M&A, Private Placement, Debt Financing, IPOs, and VBM.

» Register now (FREE)
» View archived webcasts

“Another great conference - well done! It's always a stimulating and thought-provoking
experience, and great hospitality.” - Michael Brand, Captum Capital

Over 100 delegates attended the 2011 Palisade Risk Conference at the historic West Indische Huise in Amsterdam in March. Over the course of the two day conference, industry experts presented a selection of real-world case studies about innovative and interesting approaches to risk and decision analysis. This event included the ever-popular workshops and training given by Palisade consultants, as well as a sneak peek at what is in the pipeline of new software from Palisade.

We invite you to join us next week in Mexico City, June 1 -2. Delegates from Consultoría en Decisiones®, PEMEX, IMP and experts from other companies and universities will present case studies and discuss Monte Carlo techniques and risk in all its forms.

Palisade Risk Conferences showcase the latest methodologies for risk analysis and decision making under uncertainty. It is an opportunity to learn applications such as product pricing, production forecasting, cost estimation, risk quantification, portfolio risk management, environmental liability estimation, project management, and much more, while utilizing the user-friendly risk simulation software of @RISK and the DecisionTools Suite. These events are attended by professionals from industries as diverse as oil and gas, pharmaceuticals, insurance, healthcare, engineering, and banking.

Be sure to join us for a stimulating and thought provoking experience at one of our remaining 2011 Risk Conferences in Rio de Janeiro, Sydney or Las Vegas!

» 2011 Rio de Janeiro Conference
» 2011 Sydney Conference
» 2011 Las Vegas Conference

This Thursday from 11:00am to Noon ET, Sean Ritchie will present a free live webcast.

This free live webcast will explore the use of @RISK’s functionality for managing product prices. We will discuss the applications of simulation techniques to manage the impact of price changes at a macro (regional price changes) and micro level (individual bid) levels.  We will discuss the challenges of acquiring accurate elasticity and demand data and how effective modeling can help to improve the quality of this data in the long term.

» Register now (FREE)
» View archived webcasts

If you're not a quantitative sissy, a category to which I happily consign myself, you will want to take a look at Darling's recent paper with co-authors Fengqui You, Thomas Veselka, and Gartner analyst Alfonso Velosa.  It's bound to let the sun shine into some of the darker corners of alternative energy production.