Abstracts with presentations

Keynote: Making Good Use of Risk Models in Major Projects: Trends, Challenges, and a Way Forward

Presenter: Dr Stephen Grey

It is not difficult to find bad risk models, nor is it difficult to find well-intentioned professionals trying to apply bad models to tough situations. In an effort to avoid mistakes, many smart decision-makers find tensions rise as they endeavour to apply flawed techniques while simultaneously facing criticism from others who scoff at the whole idea of risk modelling. The true value of risk analysis often lies somewhere in the crossfire. Dr Stephen Grey will show you how to rescue that value -- without getting shot.

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Probabilistic Methods in New Venture Evaluation Using @RISK

   Swinburne University of Technology

Presenter: Clint Steele
Industry Focus: Finance

The substance of the report will start with a review of the practice of risk assessment up to this point in time related to the management of uncertainty in entrepreneurial ventures. Then a methodology for the use of @RISK in the evaluation of entrepreneurial ventures will be presented and applied to an established HBR case study, ‘Clarion Optical’.

The case presents how the effects of uncertainty can indeed be quantified and mitigated through the use of @RISK. However, to take full advantage of probabilistic methods, a more complex and intimate model of the proposed venture is needed. The recommended solution to this is a business plan that includes an operations plan plus a quantification of the uncertainty associated with values stated throughout the plan.

The findings will be of value to entrepreneurs (including corporate entrepreneurs) and investors such as venture capitalists, financial angles and corporations pursuing radical innovation through corporate entrepreneurship.

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Using StatTools to Unlock the Potential of KPI Reporting

   Australian Graduate School of Management

Presenter: Paul Walsh, Senior Lecturer
Industry Focus: Government

Over the last decade business and government sectors have experienced a revolutionary zeal for performance measurement. Dashboards, Balanced Scorecards, and voluminous KPI reports are now commonplace. Yet most organisations limit the reporting and analysis of KPIs to variance tables, traffic lights, bar charts and line graphs. These are the fundamentals but there is lot more value-add organisations can extract from their KPI reporting. Paul’s will identify eight business needs that require a deeper level of KPI analysis. He will discuss these needs and demonstrate how an excel add-in like StatToolsTM can assist. Paul will also discuss the challenges in taking organisations to the next level of KPI reporting.

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Using NeuralTools to Generate a Pricing Model for Wool

   Western Australia Department of Agriculture, Curtain University of Technology

Presenter: Kimbal Curtis and John Stanton
Industry Focus: Agriculture

This case study presents an option for estimating the market price for standard indicators types of wool using Neural Tools. The method addresses concerns and suggested limitations with standard regression approaches, and is proposed as a complement to, and validation of, estimates from existing methods.

Most Australian wool is sold by open cry auction, with approx 3500 sales per week, per selling centre. The parcels of wool are listed in a catalogue with a number of categorical and numeric descriptors (independent variables). For market reporting, the industry selects a set of ‘indicator’ types with specified values for the descriptors and quotes prices for those types. Unlike a share market index, there may be no sales of lots with exactly the same specifications as an indicator type and so the market indicator value has to be estimated using interpolation with a numerical model.

For some abundant wool types, standard regression methods work well. However, for some of the less common types of wool, there are problems with regression. Not all types may be represented in each sale, independent variables are often correlated and the relationships between variables may be non linear. For these reasons we chose to test the usefulness of neural nets.

Our approach has been to trial neural nets using 6 months data for each of the three main selling centres, Sydney, Melbourne and Fremantle. Testing was undertaken against published values for the indicator types. A range of neural net configurations were explored. Variable Impact Analysis was used to confirm those variables that are most important, and to identify candidate variables for deletion.

The approach is quick to use, appears to handle correlated variables, interactions and non linearity, and can be used to confirm the results of existing methods. Live prediction can be used to explore price sensitivity of the independent variables, something of interest to both wool buyers and sellers.

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Gaining Insights into Business and Technology Valuations Using @RISK

   Capital Value Pty Ltd

Presenter: Michael Churchill
Industry Focus: Finance

Two case studies will be examined: one involving early-stage technology commercialization and one involving a mature business. Participants will see how insight can equally be provided into potential upside and downside risks for the more "risky" early-stage venture and the mature business.

Michael's presentation will cover the selection of key variables, distribution types, assessment of the possible distributions, selection of the discount rate and presentation of outputs.

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More Abstracts

New Product Analysis using @RISK

   Resolve Decisions, New Zealand

Presenter: Kimball Fink-Jensen, Principal and Project manager
Industry Focus: Manufacturing

This case study features the use of risk management towards improving the stability of revenue flows. The project involved assessing the manufacturer's place in the value chain, and identifying opportunities where our client could take up a more prominent position in that chain and drive greater revenue. Essentially we were looking to move the client from a product-driven manufacturing approach to a customer-driven marketing approach.

Purpose and objective of the model
The objective of the modeling in this stage of the project was on developing a full financial picture of the four offers we had developed to test their financial viability or otherwise. The key modeling tasks were to forecast manufacturing costs for a range of products over the next ten years (price modeling had been done separately) and then to create a picture of the market to enable demand for the new offers to be assessed. As well as providing financial information, the model was also used as an engagement tool for the client. Our client contacts were predominantly from an engineering background, and found decision making in a marketing environment different from the manufacturing world, where cause and effect can be more directly linked. The models were therefore important vehicles for engaging the client at the micro level, thus building their confidence in the macro level outputs of the model.

Key considerations
The key considerations in the cost modeling were the range of input factors for cost, and the 'recipe' of inputs that created the cost for each product line. Each product line had to be modeled separately and we relied on the client's work to determine the @RISK parameters to use. In this exercise we drew extensively on work that the client had already undertaken on an activity-based cost project. Modeling the demand uptake for the new offers was a much more iterative process. We worked through a detailed list of micro level assumptions with the client. Some of these were based on market research, some on expected response to communication programmes and some on expert view points. Using @RISK we were able to take the client through the bottom-up build of the model, enabling them to translate the concepts behind the offers into a numerical framework. This process was also a useful vehicle for communicating the structure and key relationships of the offers that we were proposing.


The key benefits of the modeling for the client were threefold:

1) They had a robust financial analysis of the new offers, which is crucial for gaining approval to move the company into a new area of operation.

2) @RISK was able to demonstrate the key drivers behind the success of each offer, making it possible to generate a prioritized list of watch outs for the implementation phase

3) By working with the model themselves, the client understood and engaged with the offers much more effectively than had they been simply presented with the ou

Getting More Out of @RISK

Presenter: Rishi Prabhakar, Palisade Corporation

This presentation takes @RISK beyond the level of the introductory course and adds several powerful tools and concepts. The Alternate Parameter function is analysed closely for its usefulness as well as subtleties to be mindful of. Decision variables and policy choices are analysed using RiskSimtable, and then with RISKOptimiser for even better results. The Advanced Options such as Goal Seek and Stress Testing will be explored as powerful risk analysis tools.  

These functions and more (such as creating standardised reports on demand) will be enhanced by introducing VBA for Excel into the working of the models. Learn how to smooth and simplify processes by utilising powerful, yet user-friendly code. Reduce tedious manual work to nothing more than the click of a button!

Getting More Out of the DecisionTools Suite

Presenter: Rishi Prabhakar, Palisade Corporation

This presentation will show you how to integrate the elements of the DTOOLS Suite into a complete risk program. PrecisionTree will help identify the model and decision analysis that needs to be done, as well as provide an efficient and effective way of presenting the results. We will use TopRank to set us on the right path to creating a probabilistic model out of a deterministic one. @RISK (including BestFit and RiskView) adds the uncertainty to the model and runs the Monte Carlo simulations required for effective risk analysis. RISKOptimiser produces the values for decision variables in your model optimise your required outcome.

Intro to @RISK for Project

Presenter: Rishi Prabhakar, Palisade Corporation

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’

Predictive Modelling featuring NeuralTools and Evolver

Presenter: Rishi Prabhakar, Palisade Corporation

Neural networks are inspired by the structure of the human brain, so can model extremely complex relationships. They make excellent predictive modelling tools! In this presentation you will discover NeuralTools and its advanced yet user-friendly numeric and categorical prediction. The structure/topology and characteristics of the three major types of neural net available will be discussed, providing a practical foundation for their use and interpretation.  

Also inspired by a natural process, Evolver is Palisade’s genetic algorithm super solver. Using nature’s own optimisation techniques of genetic crossover amongst the strongest and mutation Evolver can solve practically any problem. In this presentation we will focus on using Evolver to answer sensitivity and boundary value questions arising from NeuralTools models, for example “what is the maximum loan amount that keeps this customer in the ‘Timely Repayment’ category?”.

Preview of PrecisionTree 5.0

Presenter: Mark Meurisse, 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 analyze various problems in decision analysis. A complementary beta version of PrecisionTree 5.0 will be available for all attendees.

Meet the Experts

Presenter: Sam McLafferty, Mark Meurisse, Rishi Prabhakar, Palisade Corporation

Sam McLafferty is not only Palisade’s founder, president, and CEO, but the head of software development. Sam wrote the original @RISK program, and is actively involved with engineering behind all Palisade software. Mark Meurisse is a technical expert on most Palisade software, and regularly advises the development staff on enhancements and suggestions from users. Rishi Prabhakar gives consulting and training classes on most Palisade software. All three have seen @RISK and other tools applied in dozens of different industries. Join them for this exciting roundtable discussion, where you’ll be able to provide feedback about Palisade tools and seek advice for your particular modelling issues. So bring your spreadsheet models and your software wish list while you get to know the people behind @RISK, the DecisionTools Suite, and more.

Software Presentation @RISK 5.0 and DecisionTools Suite 5.0

Presenter: Sam McLafferty, CEO, Palisade Corporation

This major upgrade to @RISK and the DecisionTools Suite is the direct result of extensive customer input, as well as attention to the improvements with Excel 2007. Far more than a set of mere cosmetic changes, the upgrade acknowledges and meets numerous customer mandates. Sam will highlight the most prevalent of these, including requests for a more intuitive 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 usage of risk analysis tools.

PrecisionTree and TopRank are also being released in all-new 5.0 versions. Improvements to these important DecisionTools Suite components will be discussed as well. PrecisionTree 5.0 is covered more fully in its own session, “Introduction to PrecisionTree 5.0.”

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