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@RISK and Mathcad Interact to Solve the Mystery around Biotechnology in Europe

   Katholieke Universiteit Leuven

Presenter: Ir. Koen Dillen
Industry Focus: Agricultural and Food Economics

The @RISK 4.5 module from Palisade Corporation is used by the department of agricultural and food economics (Katholieke Universiteit Leuven) in a worldwide stochastic equilibrium displacement model. The project aims at estimating the economic impact of agricultural biotechnology innovations in the EU and their distribution among member countries, producers, processors, consumers, input suppliers and government. The software package developed is a unique combination of three interlinked modules: a Microsoft Excel 2003 module, a Mathcad 2001i module, and an @RISK 4.5 module. The package allows integrating uncertainty around parameters in complicated welfare calculations using stochastic distributions and Monte Carlo simulations. In order to make this package work several creative solutions had to be found.

Enterprise Risk Management - How to Build a Model and Use it for Decision Making


Presenter: Frank Lyhne Hansen
Industry Focus: Risk Management Consultancy

Risk management creates value by identifying the risks which create value, by hedging the risk not creating value and by controlling the overall risks of the company.

Traditionally, risk management has been defined defensively, i.e. as a process where undesirable risks were defined, measured and controlled. This was done by transferring the risk to others through insurance, by preventing risk or by keeping sufficient capital to finance losses.

Modern risk management looks more broadly at risk. All types of risks are included and analysed at the same time, no matter who is formally responsible of each single risk. Risk is not necessarily undesirable. Risk is an inevitable consequence of running a profitable business. No risk, no gain. Looking at risk more offensively, the object of risk management can be defined as ensuring that the company is exposed to the risk it wishes and believes that it is exposed to.

After looking at the process of implementing Enterprise Risk Management, Frank will present a case from a large Danish company that have used @RISK to develop the ERM model. @RISK is used to simulate the future earnings in the company, and to make sensibility analysis on the different risk factors. The @RISK-ERM model is used to make risk financing decisions on the different risk factors. @RISK is used to report the risk-picture of the company.

Financial Ratios and Stock Prices: Consistency or Discrepancy?
Longitudinal Comparison Between UAE and USA

   Notre Dame University

Presenter: Viviane Y Naimy, Ph.D, Professor of Finance, Notre Dame University, Louaize – Lebanon, Faculty of Business Administration and Economics, Department of Accounting, Finance, and Economics
Industry Focus: Financial

This paper aims at studying the association between stock prices and relevant financial ratios, and comparing the results for Dubai and USA based-stocks. It is noticed that the relationship between Dubai stock prices and respective ratios is not significant, whereas a better correlation is observed for US stocks. Several models and tests are developed in this paper for studying and measuring relationships between prices and ratios of companies belonging to different sectors in USA and UAE. Bestfit and StatTools from Palisade were used to build the financial models in order to reach important conclusions for investors and financial analysts and consultants in the Gulf area.

Getting ahead of the demanding shareholder requirements – implementing risk aggregation methodology (Enterprise Risk Management) at MOL Group

   MOL Group

Presenter: Peter Saling
Industry Focus: Oil & Gas

MOL Group’s risk assessment and aggregation are built on the Enterprise Risk Management (ERM) methodology. Core initiative of the concept is to measure (quantify), manage and report different classes of risks (financial, operational and strategic) based on a common methodology and on consolidated basis.
ERM model is a bottom-up model which includes all Business Units of MOL Group in an integrated form. The model is primarily intended to be used for strategic decision making. With the quantification of risks, a new dimension supplements the previous, only return- or NPV-based comparison of projects. The inclusion of such risk-return trade-off considerations definitely gives value to company.

Almost 80 different kinds of risks are tracked and quantified via the ERM model. (there can still be several sub-drivers behind main risk drivers.)

Quantification employs Monte Carlo simulation - running several thousands of iterations, where defined inputs behave as stochastic variables using probability distribution functions.  Correlations are taken into account as well.

ERM discovers risk-return attributes of Business Units, projects and business decisions. Contribution of risk types and individual risks to the total volatility (Cash Flow, EBITDA, NPV, etc.) can be calculated also. It enables the company to better understand sources and nature of different kinds of risks.

In the near future, ERM application can be further extended integrating risk considerations into capital allocation decisions, performance management and KPI setting.

Monte Carlo Simulation Technique for a Probabilistic Implementation of Structural Engineering Procedures

   TWI Ltd

Presenters: Ujjwal Bharadwaj, Ali Sisan, Vadim Silberschmidt - Structural Integrity Technology Group
Industry Focus: Engineering

Engineering Critical Assessments (ECAs) are used to determine the acceptability of flaws in various components in key industries around the world. Most techniques use a deterministic model based on procedures stipulated in standards. However, a more realistic assessment requires modelling of uncertainties in input data so that estimates of failure probabilities can be made.

There are techniques such as First Order Reliability Methods (FORM) and Second Order Reliability Methods (SORM) that do perform a probabilistic assessment of engineering failure due to the flaw under consideration. However, there are some technical and commercial difficulties in using these techniques.

This presentation demonstrates the use of Monte Carlo Simulation (MCS) using @RISK in the assessment of the probability of failure in an engineering component containing a flaw (fatigue crack). The result of using MCS technique is compared with the results obtained from the FORM and SORM techniques.

The presentation draws on TWI’s experience in using deterministic models, and FORM and SORM techniques, to demonstrate the successful use of MCS in @RISK in a probabilistic engineering implementation. The presentation concludes that the MCS technique, given the advances in computing speed and technology, compares favourably with other techniques.

Property At Risk


Presenter: Shabab Qadar, Head of Research, UK and Ireland
Industry Focus: Estate Management

Traditional property appraisals have relied on point estimates of the key determinants of investment value. At Grosvenor the approach is to accept that determinants such as rental growth, investment yields, capital value growth and other property specific factors are highly uncertain. Also, that to some extent correlated with each other. Shabab will be presenting how Grosvenor using @RISK have been able to combine the complexity of property appraisals with Monte Carlo simulation to asses the risk to the internal rate of return of projects and ensure shareholder value is maintained.

Reliability Value Analysis using Excel and @RISK

   Cranfield University, Boreas Consultants

Presenters: Karl Woods, Cranfield University, John Strutt, Boreas Consultants
Industry Focus: Finanacial Consulting

Traditional reliability, availability and maintainability (RAM) analysis does not provide an explicit link to project cash flow in assessing the reliability of competing design options. Although this may support the decision for the most reliable system, it does not necessarily select the system which provides the greatest value to the investor. By incorporating traditional RAM analysis, cash flow calculations and value decision making criteria, reliability value analysis can support the decision making process in terms of the trade-off between frontloading investments in reliability and operational costs. Presented here is the application of @RISK to a discrete event time to failure simulation that generates the output required to support reliability value decisions during design. Cut-set theory is used to define the event triggers in Excel and @RISK inputs defined to reflect the uncertainty associated with the time to failure of each component. @RISK simulations provide system failure patterns throughout the design life; each failure event is attributed a cost and located in a specific year that inputs to a cash flow model to determine reliability value metrics. Subsequently, @RISK’s sensitivity analysis capability is used to identify components with the greatest impact on project value. The technique has been verified for a series system and applied to project cash flows for subsea production systems.

Risk Assessment of BSE Controls


Presenter: Philip J Comer
Industry Focus: Agriculture

Over the past 10 years DNV has carried out in excess of 50 risk assessment studies in connection with the epidemic of Bovine Spongiform Encephalopathy (BSE) in cattle, and the emergence of variant Creutzfeldt Jacob Disease (vCJD) in the population of the United Kingdom and elsewhere. Many of these studies have used probabilistic risk assessment methods. Although the number of BSE cases in the UK has reduced dramatically and there have been far fewer vCJD cases than feared at the outset, there are still many areas of scientific uncertainty and decisions to be made where risk assessment will play a part. As the risk from BSE decreases, decisions need to be made to review the controls that were put in place when the risk levels were much higher. Such decisions will need to be based on sound science and supported by risk assessments.

A study has been carried out for the UK Food Standards Agency to review the way in which Specified Risk Material (SRM) controls are supervised and enforced in abattoirs. SRM controls were first introduced in the UK in 1989 and in the rest of Europe in 2000. These controls are designed to remove from the food supply those tissues which are known to harbour infectivity in an animal with BSE. A model has been developed, using Precision Tree, which can be used to assess the implications of alternative inspection strategies on exposure to BSE infectivity. Input data for the model includes both expert judgements (e.g., Likelihood that animal identification is not correctly checked) and scientific data (e.g., amount of infectivity in infected tissues). The model is evaluated using @RISK.

The study provides an interesting case study of the use of probabilistic risk assessment to support decision processes by government agencies.

Risk Reality v. Models: Combining the Complexity of Reality and the Simplicity of Models

   Thales Management Consultancy

Presenter: Adam Ogilvie-Smith
Industry Focus: Risk Analysis - Generic

The presentation looks at how one should balance the challenge of building models that are sufficiently simple to be practical, yet sufficiently complex to reflect reality.

Software is Only Part of the Solution…


Presenter: Dr. Sven Roden, Decision Analysis Group, Finance Academy
Industry Focus: Fast Moving Consumer Goods

For the last three years Unilever’s Finance Academy has been rolling-out and embedding its Decision Making Under Uncertainty (DMUU) programme to its finance managers, project leaders and key decision makers within the Innovation portfolio. The key aim of this programme is to create a culture where high quality decisions and probabilistic analysis are the norm. Palisade’s DecisionTools Suite provides the analytical engine which enables the analysts to develop clear insights and gain commitment to action. By building a collaborative relationship with Palisade, we have developed joint courses focused on Unilever specific requirements and armed over 200 people with the software tools they need to analyse complex decisions. This presentation will share the experiences and learnings we have gained from the past three years.

Stochastic Modeling of Exploration Assets

   Hungarian Oil and Gas Plc.

Presenter: Dr. Zsolt Komlosi, Senior Advisor
Industry Focus: Oil and Gas

Quantitative evaluation of the asset for an investor is estimating growth of Shareholder Value (SV) generated by the investment. Generally it means a development and running of a discounted cash flow model. In case of exploration assets where probability of risk is extremely high, application of stochastic modeling (as Monte Carlo simulation and portfolio optimization) and building portfolio of all are a must. The procedure is as follows. Firstly, net present value probability distribution of each asset should be determined with @RISK simulation. Simultaneously a measure of risk as Value at Risk (VaR) can be derived for each asset as well. Secondly, select the best sort of assets with RISKOptimizer running on portfolio containing all assets available. The results of optimization should be displayed on NPV vs. VaR plot. The preferred solutions can be found on the efficient portfolio curve containing portfolios having maximum NPV at given risk (VaR), or in other approach, having minimum risk (VaR) at given NPV. Thirdly, evaluation a new asset can be done in the “mirror” of the portfolio. Analyst should reevaluate entire portfolio including the new asset. The location of new portfolio’s symbol on NPV vs. VaR plot qualifies the new asset. Favorable asset moves portfolio into direction of higher NPV and/or lower VaR values.

Successfully Valuing Storage: A Real Options Approach to the Valuation of Real Assets

   University of Dundee

Presenter: Dr. Jennifer I Considine
Industry Focus: Academic Finance

This presentation is concerned with the role of strategic planning in the optimisation of real assets in the energy industry. Specifically, a real options approach using @RISK Monte Carlo simulation methods when used as part of Real Options Valuation strategies. The approach is used to evaluate and value, storage facilities in the natural gas industry. Beginning with an overview of standard storage valuation techniques, the paper moves to a real options approach, and in depth look at dynamic heading strategies, such as back to back call and put options.

Using the @RISK Developers Kit to manage Risk in Aerospace & Defence


Presenter: Tim Mobley
Industry Focus: Aerospace & Defence

Istria Ltd, a UK based risk management company, has incorporated the @RISK Developers Kit into an end to end software solution that manages risks from identification through to their conclusion. In this session, Istria will use a live case study from the aerospace & defence sector to illustrate how @RISK can be used to integrate simple qualitative assessments into a robust statistical analysis tool.

Using @RISK in Project Risk Assessments at Infineon

   Infineon Technologies

Presenter: Dr. Martin Erdmann, Director Risk Management
Industry Focus: IT

Infineon uses the methodology of Quantitative Risk Analysis mainly to assess the risks in R&D projects. These risks are related to the schedule of the projects as well as to their respective business plans. A regulated proper usage of ‘@RISK for Project’ and ‘@RISK for Excel’ has been introduced and implemented in a corresponding company processes. This presentation will share the experiences Infineon had in this company wide roll out and give an overview of the results.

Using @RISK to Calculate Radiological Doses from a Final Repository for Spent Nuclear Fuel

   Swedish Nuclear Fuel and Waste Management Company

Presenter: Allan Hedin
Industry Focus: Energy

@RISK has been used for probabilistic calculations of radionuclide transport and dose from a final repository for spent nuclear fuel. Such a repository is being developed by the Swedish nuclear industry with the aim of filing a licence application in 2009 for one of the two Swedish candidate sites currently being investigated. The total investment in the repository is of the order of £1 billion and the construction and operation phases of the facility are expected to extend over several decades.

A comprehensive safety case forms a key part of a licence application for a final repository. The core of the safety case consists of probabilistic radionuclide transport and dose calculations covering repository development over typically 100,000 years. Traditionally, these calculations have been carried out with models and probabilistic drivers developed in C++ and Fortran. In a recently published study it is demonstrated how the bulk of the probabilistic calculations can be done with simpler Excel models and @RISK.

The main advantage of the new approach is a reduction of calculation times by about a factor of 100, allowing a considerably more comprehensive set of calculations in a given time to underpin the safety case. The old models are used in benchmark calculations, justifying the use of the simplified, fast Excel models.

Using @RISK to Develop Financial Products

   Union Investment Management Holding AG

Presenter: Christian R. Gärtner
Industry Focus: Financial

  • Historical Simulation vs. Monte Carlo Simulation - advantages and disadvantages
  • Developing a CPPI fund using Monte Carlo Simulation
  • What is CPPI?
  • What are the requirements the product needs to fulfill?
  • Which assumptions and distributions to use?
  • Developing an EXCEL model of the product
  • Using @RISK to finally design the product

Using @RISK for Project to Enhance Financial Services Processes

   PMI Frankfurt Chapter and Director, Value & Risk AG

Presenter: Dr. Wilhelm K. Kross, President, PMI Frankfurt Chapter and Director, Value & Risk AG
Industry Focus: Financial Services

Business literature reveals that process performance enhancements in administrative and financial management seem to have been implemented with less obvious success than is the case for processes involving physical flows of goods and materials. The promises of the “industrialization of banking” seem to have by and large remained lip-service. Underlying issues are multi-fold and include over-constrained thinking, in that cost account structures and transfer pricing assumptions are not truly questioned when activity-based or target and life-cycle cost management techniques are employed in combination with readily available data from management accounting systems.

Project managers have known such issues for years, but are in many real-life organizations still confronted with poorly harmonized cost accounting versus process oriented perceptions of project performance. More innovative organizations nowadays support these coexisting perspectives and have benefited from consequential improvements in the form of overall cost savings, enhanced speed and flexibility, and higher likelihoods of success. The major issue that project plans usually reflect an unknown degree of conservatism, and possibly different degrees of uncertainty and risk taking in different phases and activities, has been addressed through the adoption of a “probabilistic approach”, now supported by a variety of standard software applications including @RISK for MS Project. These techniques and success recipes appear not to have been converted in practice, however, to the field of administrative and financial processes management and related decision making.

In this presentation the author introduces several case examples of auditing, enhancing and redesigning financial services processes, employing risk-based process modelling techniques which were adopted from the field of project management. It is demonstrated how such approaches to auditing and redesigning business processes in real-life financial services environments, can be further integrated to derive recommendations on organizational design solutions and to select and benchmark risk-based key indicators for the focusing of personnel on service level agreements. The results hence include process flexibility and speed enhancements and at the same time significant cost savings – in some cases without actually requiring up-front investments.

Valuing Early Stage Technology

   Captum Capital Limited

Presenter: Dr. Michael Brand PhD MBA
Industry Focus: Life Science

Assigning a value to early stage technology is difficult, but a necessary requirement prior to further investment by venture capital funds, corporate partners, or licensing or sale of the technology. Valuation is problematic when the technology is not fully developed, or the product has not yet reached market so there is no trading history. Basing value on development cost is likely to undervalue a technology which may have the potential to generate significant profit in the future. In the life sciences sector, biotechnology, pharmaceuticals and medical devices, development times are usually prolonged by step-wise clinical trials, but the potential return may be $billions.

Approaches which are commonly taken to this valuation problem include expected Net Present Value and Real Option pricing. Monte Carlo simulation, using @RISK, provides a straightforward, intuitive approach to valuing the future potential of early stage technology, which provides additional information over expected NPV models. Models of drug and medical device development and licensing will be used to illustrate the practicality of this approach.

Business & Investment @RISK Models

   Palisade Corporation

Presenter: Manuel Carmona, European Sales Manager

The aim of this presentation is to demonstrate @RISK to users with little or no experience of stochastic modeling, and to provide a good introduction to the basic features of the software. Additionally, the presentation will be useful for more expert users, should they want to consider using @RISK as a tool to model a number of practical business situations.

We will work on a number of models and case studies such as;

  • How to use @RISK to model the administration of an investment portfolio, consisting in different asset classes such as property, trust funds, personal pension plans, shares etc.
  • How to design an @RISK model for the launch of a new business idea. We’ll design proforma cash-flow models, P&L, and balance statements.

We will show how to forecast cash flows subject to uncertainty, and the advantages of an @RISK model compared to a traditional deterministic model. Our goal will be to make better defensible business models.

We will use some of the models developed by Prof. Wayne Winston from the University of Indiana, and we will show how these models can easily be adapted to our own requirements.

Introduction to NeuralTools

   Palisade Corporation

Presenter: Dr. Mirek Janusz

Neural networks predict unknown information by finding patterns in data, and the technology behind NeuralTools is inspired by the functioning of the brain. The presentation will proceed by solving some specific problems to demonstrate both what neural nets can do, and how easy it is to apply this advanced technology using Palisade's NeuralTools. Problems in Banking, Biology, Medicine or other fields will be solved, time permitting.

Introduction to PrecisionTree 5.0

  Palisade Corporation

Presenter: Erik Westwig, Software Engineer, Palisade Corporation

This presentation combines an introduction of the enhanced user interface, tighter Excel integration, and new features of PrecisionTree 5.0, with demonstrations of how PrecisionTree can be used to analyse various problems in decision analysis.


@RISK in Insurance and Finance with ModelRisk

   Vose Consulting

Presenter: David Vose

@RISK can be used for many different applications within the insurance and finance industries. Insurance applications include estimating loss reserves and setting premium pricing. Finance applications run the gamut and include actuarial modelling, cashflow analysis, corporate treasury, banking regulation (e.g. Basel II), investment analysis and advanced probability calculations. However, incorporating @RISK probability distribution functions to represent uncertainty in these models is often the least of your worries. Creating complex and accurate insurance and finance risk models in Excel can be a daunting task, requiring in-depth calculations, formulae, and specialised Excel functions. The ModelRisk software by Vose Consulting works seamlessly with @RISK to allow analysts access to the most up-to-date and advanced modelling techniques available in the insurance and finance fields, and takes advantage of powerful @RISK features like advanced sensitivity analysis and optimisation. Optimised for speed and accuracy, ModelRisk offers tools that are otherwise impractical to apply directly in a spreadsheet environment because of either mathematical complexity, speed, dimensional or resource constraints. ModelRisk features 70 univariate and multivariate distributions used in insurance and finance, copulas commonly used in correlation modelling, 18 different types of sophisticated financial time series models, portfolio optimisation, ruin and depletion models, stochastic dominance test, aggregate claim distributions, and much more. This session will show, through real-world examples, how @RISK and ModelRisk can work together to solve some of your thorniest insurance and finance problems.

Selecting the Right Distribution

  Palisade Corporation

Presenter: Dr. Michael Rees, Senior Consultant, Palisade Corporation

How often have you looked at the palette of distributions in @RISK and related tools and wondered which one you should use? A crucial aspect of risk modeling is the selection of the appropriate distribution to use to represent key uncertain variables. @RISK offers a wealth of probability distributions – some are very intuitive like the Uniform and Triangular, others are somewhat familiar to anyone with a scientific, engineering or finance background, like the Normal and Lognormal. However, many of the other distributions offered in @RISK gives us access to sophisticated probability thinking that can greatly extend and simplify your risk models.

This session will explain, in simple terms and illustrated with example models, the thinking behind the most powerful distributions, what they model, and how they can be put to use in your risk analyses.

Real Options Modelling using @RISK and PrecisionTree

   Palisade Corporation

Presenter: Dr. Michael Rees, Senior Consultant

In this session, the core concepts behind real options will be introduced, including the value of flexibility in decisions taken under uncertainty. A range of real options models will be shown using @RISK, and then followed by a demonstration of how PrecisionTree may be used for valuing certain real options situations, such as the value associated with structuring a project into phases.


Excel 2007 and Excel Services:
New Ways of Modelling and Sharing

Presenters: Dany Hoter

Dany will be demonstrating Excel 2007 and highlighting key areas that will enhance performance for power users. Dany will also cover the goals Microsoft had in designing and developing Excel 2007, and will introduce Excel Services.  Excel Services is a new server technology included in Microsoft Office SharePoint Server 2007.  Using Excel Services, you can easily reuse and share Excel workbooks on Office SharePoint Server 2007 portals and dashboards.

He will also be very interested in delegate feedback and input that he can use while developing the next version of Excel.

Areas covered:

  • Editing complex formulas
  • Visualisation
  • Using Excel services with High Performance computing to achieve scalability
  • Using SharePoint to establish approval workflows and controlling the distribution of Excel files in the organisation
  • New features in Pivot Tables
  • New Business Intelligence features
  • New charting options
  • New Smart Art feature for creating diagrams
  • The new mechanism of using Excel charts in Word and PowerPoint when the data is in Excel and the chart in Word/PowerPoint

Overview of @RISK 5.0 and DecisionTools Suite 5.0

  Palisade Corporation

Presenter: Sam McLafferty, CEO, Palisade Corporation

This major upgrade to @RISK and the DecisionTools Suite is driven by the latest innovations in the field and customer input, as well as attention to the improvements with Excel 2007. Sam will highlight the most prevalent of the new software innovations, including a tour of the stunning new @RISK user interface that is completely integrated into the spreadsheet environment. The discussion will also address how @RISK 5.0 is designed to better meet the needs of corporate-wide sharing, and how it offers more robust analyses.

Excel 2007: New Ways of Modelling

Presenters: Dany Hoter

Dany will be demonstrating Excel 2007 and highlighting key areas that will enhance performance for power users. Dany will also cover the goals Microsoft had in designing and developing Excel 2007 and Excel services. He will also be very interested in delegate feedback and input that he can use while developing the next version of Excel.

Areas covered:

  • Editing complex formulas
  • Visualization
  • Using Excel services with High Performance computing to achieve scalability
  • Using SharePoint to establish approval workflows and controlling the distribution of Excel files in the organization.
  • New features in Pivot Tables
  • New BI features
  • New charting options
  • New smart art feature for creating diagrams
  • The new mechanism of using Excel charts in Word and PowerPoint when the data is in Excel and the chart in Word/PowerPoint


Walk-In Clinic and Meet the Developers

  Palisade Corporation

Presenters: Dr. Michael Rees, Erik Westwig, and Dr. Mirek Janusz, Palisade Corporation

Join Palisade expert Dr. Michael Rees, and Palisade’s top software engineers Dr. Mirek Janusz and Erik Westwig for this exciting round table discussion, where you’ll be able to provide feedback about Palisade tools and seek advice for your particular modelling issues. Bring your thorniest @RISK, DecisionTools Suite, or NeuralTools problems and your trickiest modelling conundrums and get customised advice for your particular problem.


Modelling Uncertain Time Series

   Vose Consulting

Presenter: David Vose

Many risk analysis models need to include projections over time for key variables. For example: investment cashflow models need to make projections of market size, market share, fixed and variable costs, interest and exchange rates; insurance companies need projections of claim frequencies and aggregate claim costs; and engineering companies need projections of failure rates, downtimes and lifecycle costs. Historical data often give us some basis for making projections, but one also needs to factor in changes to the business environment (e.g. new laws, fuel costs, political and demographic changes, emergence of new competitors, new trends) for which historic data may have only partial relevance. A time series constructed with @RISK needs to correctly describe both the amount of uncertainty in each forecast period as well as interactions (dependencies) between periods and other forecast variables in the model. This lecture explains a number of  proven, practical and intuitive methods for developing time series projections in various situations that will help you to get the most accurate forecasts and insight from your risk analysis.

@RISK for Project Refresher

   Palisade Corporation

Presenter: Ian Wallace

The aim of this seminar is to give people a basic understanding of how @RISK for Microsoft Project works, including hands-on experience for setting up and running simulations, and interpreting the results.

Attendees will learn about the key functionality within @RISK for Project in step-by-step method, enabling them to quickly become familiar with basic concepts and terminology.

In addition to graphing and quantifying the risk in a business plan, you will learn how @RISK for Project, using Monte Carlo simulation, enables you to:

  • Calculate the probability of success
  • Graph the margin of error around the most likely outcome
  • Quantify and prioritise the risk drivers
  • Quantify the amount ‘@RISK’

Introduction to Risk Analysis with @RISK 5.0

   Palisade Corporation

Presenter: Dr. Michael Rees

This course will provide hands-on training to cover the basic elements of @RISK, while introducing new features found within @RISK 5.0. Attendees will learn how to create, run, and interpret basic risk analysis models using Monte Carlo simulation. The content is suitable for @RISK beginners, those with experience who may require some reminders, or anyone who wants to spend some time familiarising themselves with the new features of @RISK 5.0. The session will cover:

  1. Introduction to risk analysis and @RISK 5.0
    1. What is risk analysis?
    2. Example model: basic business plan
    3. Interpretation of output
  2. Further aspects of risk analysis using @RISK 5.0




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