An insight into how PricewaterhouseCoopers have used Palisade solutions over the years in consulting projects. As a provider of advisory services to companies in a wide selection of industries, all of whom are faced with different issues and challenges, this presentation provides an overview of how one of the world's leading consultancies has utilised the flexibility and versatility of @RISK.
Captive study and optimising the insurance program of AP Moller Maersk
Risk analysis and risk adjusting the budget model during an IPO
Risk adjusted pricing of large projects in FL Smith
@RISK model for the Danish Government on project risk
@RISK model for the deciding what air plan the military should buy
Why do different people in the decision making team see things from entirely different perspectives? What is it about different personality types that pre-dispose people to different decision making biases? What can we do to counter these biases? The evidence indicating that decision-making bias is part of human nature is overwhelming and long established - the remaining area for discussion is how we can ensure high quality decisions in the context of this bias.
Unilever is present in 170 countries, employs 163 000 people and has an annual turnover in excess of €40 bn. By any definition this is a large and complex organisation and on a daily basis, it needs to make numerous high quality strategic decisions. The Unilever Decision Analysis Group, which is charged with embedding Decision Analysis throughout the organisation, forms part of the solution through considering 3 key steps. Firstly, it aims to understand the origin of this bias, including personality types and the biases that different personality types are pre-disposed to. Secondly, it has developed a rigorous decision-making process to counter those biases. Thirdly and finally, it ensures that communication of results to decision makers is fully adapted to their needs and addresses decision making bias.
Having just celebrated its 26th anniversary, Palisade stands at the forefront of risk and decision software analytics. Palisade President Sam McLafferty will provide a bit of background on Palisade’s history and will describe what sets Palisade apart in the market. He will describe the latest enhancements and additions to the DecisionTools Suite product line before providing a glimpse into what’s coming next from the company.
There’s been a lot of talk about the need for “proper risk analysis” in the last couple of years. But what does that mean? After all, risk management appears to have failed at many levels and even now companies are still trying to figure out how to grapple with risk. Any meaningful risk analysis must incorporate probabilities, but that is still a foreign concept to many decision-makers. Palisade Vice President Randy Heffernan will touch upon of the reasons for the failure of many risk management efforts, and explore The Power of Probabilities in risk analysis: what it is, why it’s important, and how you can benefit.
Application of the Monte-Carlo Method to Determine the Costs for Construction Projects – Influence of Ranges and Correlations on Probability Distribution
Depending on the project phase, the costs for construction is either determined as a rough estimate or calculated precisely. In this respect, the degree of accuracy is dependent upon the mathematical combination of the input parameters. However, input parameters include uncertainties and fuzziness. These input parameter ranges can be accounted for in a non-systematic, deterministic manner. The range of possible costs can be restricted by establishing both an optimistic and a pessimistic consideration. In most cases, a value between the two boundaries determined is applied. No statement can be made, however, about the accuracy of the value selected.
To calculate costs, the deterministic method will be demonstrated for the preliminary planning stage. For this purpose, the equations to be used to perform a rough calculation of costs will be shown. The Monte-Carlo method will then be applied on the basis of the deterministic calculation mode used initially. The Monte-Carlo calculation sequence will be both described and displayed graphically. For each simulation exercise, distribution functions will be selected for the input parameters, and minimum and maximum values will be determined, as well as expected values, as far as reasonably possible. The @RISK software will be used to carry out the simulations. The results will be shown as probability distributions for the output parameters defined in a preceding step. The results of several simulations with varying distribution functions will be compared to each other and analysed. The comparison should show whether it is useful to apply weighted triangles as distribution functions.
The influence of a reduction in the input parameter range on the probability distributions will also be determined. Such a range reduction is enabled by a more detailed knowledge of the prevailing site, management, structural and process conditions. The degree of uncertainty and fuzziness can be lowered as a result. The paper is to demonstrate and analyse the influence of the input parameter improvement on the results.
Correlations will be established for selected parameters in order to identify the influence that the type of correlation (i.e. positive or negative) may have on the results. The influence of correlations will be investigated for four different distribution functions.
A building project example will be used to apply the Monte-Carlo method. As a result, construction costs will be shown as a probability distribution, and significant values will be stated. The probability distribution may also be used as a basis for the decision-making process to determine the construction time that is useful with regard to construction management and economic aspects. In addition, parameters with a major influence on construction time can be identified.
Application of Palisade @RISK for the
Analysis of Risks in the Wind Power Industry
One of the goals of Global Risk Strategy (GRS) area of EDP Renováveis is to evaluate EDPR’s risk exposure and to define company’s risk profile. This includes recommending the appropriate transactional limits, risk policies and macro-strategies for managing risks
To address this command, GRS developed a Portfolio Risk model based on Microsoft Excel using Palisade’s @RISK. This financial model builds the EBITDA and FCF probability distribution with a bottom-up approach from basic inputs like fuel prices, exchange rates, and wind resource, taking into accountexisting correlations between all variables
This model helped EDPR to understand its EBITDA and EBITDA@RISK dynamics
Measure risk per geography and also at aggregated level
Identify the correlations / natural hedges (correlation between variables may create natural hedges)
Assess the contribution of each risk factor
Quantify the value of hedging on risk mitigation: how much may the EBITDA@RISK be reduced by hedging energy price, exchange rates, wind resource,…
Portfolio effect has a great value in risk mitigation and is now used as a risk management lever:
Through diversification effect (value of having a portfolio with different geographies and different risk factors) and natural hedging (geographies with EBITDA in contra cycle or with negative correlation). This is now included in the guidelines for energy management in EDPR and also considered in the growth strategy definition
Impact of hedging on the aggregated risk is not significant due to the loss of portfolio value
An Application of Optimisation &
Simulation for Solvency II
The Solvency II regulations are fundamentally redesigning the capital adequacy regime for European (re)insurers and will be effective from 31 October 2012. The Solvency II objectives are to establish a set of EU-wide capital requirements and risk management standards replacing the current Solvency I requirements.
Solvency II establishes two levels of capital requirements: i) Minimal Capital Requirement (MCR), i.e. the threshold below which the authorisation of the (re)insurer shall be withdrawn; and ii) Solvency Capital Requirement (SCR), i.e. the threshold below which the (re)insurer will be subject to a much higher supervision. The SCR should deliver a level of capital that enables the (re)insurer to absorb significant unforeseen losses over a specified time horizon. It should cover, at a minimum, insurance, market, credit and operational risks, corresponding to the Value-at-Risk (VAR) of the (re)insurer’s own basic funds, subject to a confidence level of 99.95% over a one-year period.
Solvency II offers two options for calculating SCR, i.e. by applying either: i) a standard model, which will be provided by the regulator; or ii) an internal model, which will be developed by (re)insurers. A standard model cannot consider the company’s specific factors, thus the SCR will be higher. In contrast, an internal model results in a lower SCR as all the (re)insurer’s specific factors are considered. Therefore, Solvency II offers capital-reduction incentives to insurers that invest in developing best practices in risk management and control.
This paper presents an internal model, which applies optimisation and Monte Carlo simulation to calculate the SCR. The model is successfully applied and verified on real market data. It can help (re)insurers to reduce their SCR providing higher underwriting capabilities and increasing their competitive position, which is their ultimate objective.
Case Study of a Risk-based Life-cycle Model - For a Large PPP Project
Dr Kross will present his findings on a large scale project assessment undertaken in Germany. Dr Kross was asked to have close look at the budget forecasts for a large scale construction project in Berlin, following a new policy whereby projects of that type need to be analyzed for their PPP-Readiness. The challenge has become that the German Federal Government is a self-insurer and that hence, budget forecasts are supposed to be risk-free, i.e., no provision for all those uncertain and undesired future surprises. Those are dealt with, by policy, as and when they occur. Hence the challenge in 2009 was to develop a project plan and a calculation for the building development which truly is risk-free. And in 2010 it became yet another challenge to update the earlier calculations and to add a cash-flow model with a maximum 40 year life cycle, which effectively yields a risk-based “public sector comparator (PSC)”. A lot of work went into this, and the results are multi-fold. We now know the main uncertainty drivers, not only in the initial development phase, but also in the later operational and maintenance activities. We know for which components and activities, a rather detailed SLA negotiation is success-critical. We know those aspects which need to be specified in great detail and those which should not be specified in great detail. And we know that the life cycle should not be 20 years, rather, 27 years would be a smart decision.
With respect to the true techniques, effectively the core was to moderate analyses based on subjective assessments – which effectively were captured in @RISK for Project and @RISK for Excel on the screen, whilst actually conducting the interviews. The probability functions were then upgraded in several interview sessions, and complemented with a probabilistic life-cycle model which was developed on the basis of interview-based parameters, and then calibrated in two additional workshops in order to reflect what the client truly felt was necessary in order to support sensible decisions.
A Case Study of Risk Management Tools Adoption
Within Engineering SMEs
In today’s dynamic commercial environments, project management approaches are
becoming ever more critical in supporting organizations to achieve their customer and
enterprise goals. An often undervalued element of this important practice may be seen
as the deployment of effective risk management techniques and solutions to help
managers make appropriate decisions. Neglecting risk management is often cited as
one of the main factors that may lead to assumed failure within typical engineering
projects. It is widely believed that such failure may be avoided if risk management is
effectively addressed during the early phases of the project life cycle. The purpose of
this case study has arisen from one of the most important areas in project
management, both from a practitioner and a researcher perspective; ‘How to avoid
failure and achieve higher rates of project success?’. The outcome of this work is to
demonstrate, through a pilot study within an engineering SME, how the adoption of
specific risk management tools, such The DecisionTools Suite, can be important
enablers in assisting managers to achieve higher levels of success.
An Exploration of Copulas and
When simulating multiple variables one needs to define the dependencies and relationships between them, for example by using correlations. During the credit crisis, it became apparent that in times of turmoil, correlations between different assets are higher than in normal circumstances. The use of different techniques to model this effect can be explored using @RISK.
The DecisionTools Suite in Mining and Natural Resources
@RISK and PrecisionTree are particularly useful in problems faced by companies in the mining and natural resources sector. Much like in oil and gas exploration, @RISK can be used to analyze the uncertainty associated with estimating the resources underground, the variable world prices for such resources, as well as the costs of blasting and extraction. PrecisionTree can be used to map out the various complex decisions that must be made in sequence when considering any form of natural resource extraction. The two can even be combined to perform Monte Carlo simulation on uncertain elements in decision trees.
Based in Sydney, Palisade's Mark Meurisse has experience with these applications in Australia and will provide enlightening and useful approaches to problems commonly faced.
Determination of a Risk Component in the
of Power - The Case of a Transmission Company
The Romanian power market commercial grid code provides for a risk component in the price of power based on market exposure risk. The paper uses @RISK with a correction for the average evolution to assess the mentioned exposure.
Diamond Model: Synergies of Empirical
and Analysis of the Model
This paper examines how @RISK can be used to help structure micro-financing initiatives by developing and forecasting social welfare projections, modelling the probability of poor households defaulting and assisting with premium pricing.
Estimating Demand for Services through the Characterisation of Towns and Areas through Standard Dwelling Types
The design of infrastructure to deliver essential services (such as water supply) to communities in developing countries poses the critical question: what is the demand? Engineering standards present some basis for design in such circumstances but this is often not satisfactory due to:
The lack of suitable base data – often relies on out-dated census data
1st world engineering standards are often not applicable and may result in over expenditure
Infrastructure is often implemented in stages with the level of service that is upgraded from one stage to the next
Current estimation techniques are not suitable for risk analysis which is a critical consideration when infrastructure will be (project) financed
The authors have developed a model through which demand can be estimated and which overcomes all the problems listed above. This model is based on the definition of standard dwelling types (SDT’s) and uses @RISK to simulate the demand as well as growth in demand. Key benefits of the model include the following:
Rapid model establishment with limited available information
Modelling demand for all services (water, sewage, electricity & solid waste) which facilitates integration and planning
Progressive enhancement of the model as new information becomes available
In spite of the simulation complexities, the results of the model are in a form readily understood and digested by municipal officials and politicians
Allows detailed risk analysis and also facilitates the mitigation of demand risk
Forms the basis of analysing different cost-recovery mechanisms and tariff structures
Integrates seamlessly with the financial model of the project
The paper will discuss the basics of the model and the results of a recent case study will be presented.
Forecasting Cost (at Completion) in
Fast-Paced Industrial Construction Projects:
A Case Study on Agile Cost Control driven by Change
Industrial construction projects tend to increasingly be executed fast-pace. The implications of schedule-driven projects often include near to permanent change, high levels of uncertainty and very limited time available for performing risk assessments. Flexible project management systems in general and, specifically as in this case study, simple but powerful cost control models are needed in order to cope with the implications of fast-paced projects and at the same time provide adequate predictions to inform decision makers. This paper presents the probabilistic model developed for forecasting cost at completion of construction of a flue gas treatment plant in Europe. The model was built and run on Microsoft Excel with the aid of Palisade’s @RISK for Excel. Key features of the model include prediction of total project cost at completion, correlation of different contractors’ claims reflecting applicable contractual relations and identification of critical contractors’ claims for subsequent negotiations. Overall the key benefit for decision makers was being provided with accurate estimates in a timely manner, which more realistically reflected the impacts of any changes identified at any point in time.
This presentation examines HOW TO REALISE A PROJECT IN TIME, thanks to optimising the probabilistic planning with measurements to minimise delay or risks and also with measurements to lower the demands on quality (scope).
In order to find the right set of measurements (they cost money and have an expected effect and chance to succeed, so not all will be executed) one needs an optimiser to calculate the set. In this case, @RISK for Project has to be combined with other software in The DecisionTools Suite. This set of programs for this specific use could become a template for @RISK, for a typical kind of planning-use.
In general, knowing the effectiveness and chance of success of measurements is underestimated, not registered and in a way, the circle PLAN DO CHECK ACT is never truly closed in common project management. I call for more attention to registering effectiveness of measurements, not just for the next project, but also to optimise the choice for measurements within the project itself to meet the final deadline.
Implementing Strategic Planning under Uncertainty using Palisade’s RISKOptimizer
Multiple Criteria Decision Making (MCDM) models have become quite common in firms’ strategic planning, a reflection of the movement away from the notion of a firm with a single objective of profit maximisation to a multi objective view that sees the firm as simultaneously striving after a set of goals. However, the effectiveness of these models has been limited because some of the factors that were assumed to be deterministic are in reality, uncertain. This study presents a framework that integrates uncertainty into the strategy formulation process for a chemical manufacturing firm using Palisade’s RISKOptimizer. The approach combines both MCDM with Monte Carlo simulation with the objective of developing a strategic production plan that will achieve the best use of existing facilities while providing information on the possible expansion of the firm’s productive capacities. Through this approach, we were able to deliver a strategic plan that not only performs well across a broad spectrum of possibilities but is also nimble enough to respond quickly to unexpected events and contingencies.
Modelling behaviour using @RISK and PrecisionTree Why probability estimates aren’t always what they seem.
Over the past three decades, behavioural economists and psychologists have gathered a significant amount of evidence suggesting that most people find it surprisingly difficult to make accurate judgements about probabilities. This is a cause for concern in real-world decisions, which normally involve at least some degree of risk and uncertainty. Even more troubling are the consequences for long-term decisions, in which it is necessary to account for multiple possible sequences of events; if each event includes an erroneous prior probability judgment, this will have the effect of multiplying the overall error in the decision.
This presentation will discuss some examples of probabilistic decision making where intuitions and judgements are regularly incorrect - such as the Monty Hall problem, the base rate fallacy, and the conjunction fallacy - and demonstrate these cases via implementation within @RISK and PrecisionTree. Furthermore, the presentation will also explain how models of behaviour during decision making can be developed using Palisades software.
Modelling Known Unknowns –
A Case Study for Private Sewers
Recently English and Welsh wastewater companies have been required by the government to adopt more sewers and associated assets from private owners. The assets are potentially in a poor state of repair, may have been constructed from poor materials, can be difficult to access and in the case of pumping stations have not been built to modern standards of safety and reliablilty. Above all, information on these assets is very limited.
The adoption of these assets represents a risk to UK wastewater companies as there are many uncertainties:
How many assets are there to adopt and where are they located?
What state are the assets in and how much work is required to restore them to modern standards?
What will be the immediate cost of adopting the assets?
What will be the cost of maintaining the assets in the long term?
In the UK regulatory system wastewater companies need to maintain levels of service and justify the required expenditure in order to secure the income required to undertake the work. However, this is difficult for private sewers given the lack of information and level of uncertainty. Ultimately, companies need to know:
What is the best strategy to adopt and maintain these unknown assets?
How much will this cost?
level of service will it achieve?
How certain are we?
In this context a major UK water and wastewater company employed Mott MacDonald to build a model to predict the expected level of service over the next 40 years and the associated capital and operating costs, which takes into account different maintenance plans and levels of uncertainty. Mott MacDonald used Microsoft Excel to build this investment tool and used @RISK to model the uncertainty in the inputs to understand the variability in the outputs.
The paper will consider these and other challenges found in modelling the investment needs for a large goup of private sewers and associated assets for which limited information was available and how those challenges were overcome using @RISK.
Pragmatic use of DecisionTools in Project, Program & Portfolio Management
Today decision making is considered as a key competence of project, program and portfolio managers. They face a business world of large complexity, with increased number of decision centres. Decision making must be faster, more accurate, and preferably based upon more reliable assumptions, and input and output parameters. Organisations, striving for higher transparency and open communication to their stakeholders and shareholders, seek ways to reduce the subjective way of decision making, and therefore show an increasing interest in decision tools. This presentation will demonstrate areas in project, program and portfolio management where these techniques can be applied. What are the prerequisites, the benefits, and the critical success factors?
Real Option Valuation of Technology
Application of PrecisionTree
The valuation of technology based companies and their intellectual property is among one of the more challenging problems in risk analysis, with no clear consensus on methodology.
The widely used risk-adjusted net present value (rNPV) method, based on assessment of income, growth rate and discount factor, can neglect strategic options in technology development and is unable to deal with all scenarios, such as the value of an option to license IP.
Real Option analysis was introduced in the 1980s as a means of capturing flexibility in decision making as part of the valuation process. This method has attracted some level of interest, particularly for valuing bio-pharmaceutical technology, although surveys suggest it is only used as a primary method by 5-10% of analysts; in the US it is an integral part of the AICPA Practice Guide to valuation of privately held companies. Typically each milestone or stage in development of a technology based product is treated as an option, with the final option being the eventual sale (or, more rarely today, IPO) of the technology based company.
Among the reasons for Real Option analysis not being more widely adopted is its mathematical basis, and the widely used binomial tree approach is less than intuitively obvious to investment decision makers. Decision trees represent an accessible approach to Real Option valuation methods, which is more transparent to decision makers, who usually have some familiarity with the basic concept. PrecisionTree allows large and sometimes complex trees to be constructed easily in Excel, and the effect of changes in parameter values or tree branches can be seen immediately without the need for tedious recalculation.
This presentation will use PrecisionTree and @RISK models to illustrate the practical application of Real Option valuation of technology businesses, licenses, and options to license technology.
Refining the Business Case for Sustainable Energy Projects Using Palisade @RISK and Precision Tree: A Biofuel Plant Case Study
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 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 presentation asserts that an energy development ‘risk / reward parity’ level is growing between new petroleum exploration 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 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. The approaches presented have promise as a due-diligence tool for prospective sustainability entrepreneurs, investors, project managers, and firms.
Representing Uncertainty by Probability and Possibility
− What’s the Difference?
Uncertain parameters in modelling are usually represented by probability distributions reflecting either the objective uncertainty of the parameters or the subjective belief held by the model builder. This approach is particularly suited for representing the statistical nature or variance of uncertain parameters. Monte Carlo simulation is readily used for practical calculations. However, an alternative approach is offered by possibility theory making use of possibility distributions such as intervals and fuzzy intervals. This approach is well suited to represent lack of knowledge or imprecision concerning uncertain parameters. Interval arithmetic and global optimisation is used for practical calculations. The two alternative approaches are based on quite different concepts and mathematical principles and also yield quite different results when applied to identical numerical uncertain data. This is demonstrated by a number of numerical examples.
The two approaches are applied to risk and uncertainty management in compliance with the principles of New Budgeting laid out in 2008 by the Danish Ministry of Transport to be used in large infrastructure projects. Basically, the new principles are proposed in order to prevent future budget overruns. One of the central ideas is to introduce improved risk management processes and the present paper addresses this particular issue. A relevant cost function in terms of unit prices and quantities is developed and an event impact matrix with uncertain impacts from independent uncertain risk events is used to calculate the total uncertain risk budget. Cost impacts from the individual risk events on the individual project activities are kept precisely track of in order to comply with the requirements of New Budgeting. Additionally, uncertain likelihoods for the occurrence of risk events are allowed for in order to adequately reflect the complexity of realistic budgeting in the presence of uncertainty. Application is demonstrated by means of numerical test cases and comparisons are made with numerically identical input parameters.
@RISK for Excel used to
Support Investment Appraisal
A presentation which demonstrates applications where @RISK for Excel has been used to support investment appraisal through a single model integrating the full range of key input variables from the initial project cost and schedule to market demand and price forecasts
Examples of outputs include risk-based predictions of project completion dates, capital out-turn costs (taking account of delay costs), production outputs, unit costs, annualised production costs, revenue, cash-flows, and returns on investment (NPV / IRR). Sometimes risk practitioners regard time and cost models as separate entities, and use different software. Results are then presented separately or else integrated using somewhat forced methods. This approach differs insofar as integration occurs at the input stage, and in a single model.
Risk-based Models for the
Design of Arctic Platforms
The Confederation Bridge connects two provinces on Canada’s east coast. At a length of 13 km, it is the longest bridge in the world which is exposed to dynamic sea ice conditions every winter. The bridge was completed in 2001, and took 3 years to construct.
Ice loading on the piers had a major influence on the design and cost of the bridge piers. Ice loads, unlike those of waves or winds, involve major uncertainties which are still not totally understood today. The presenter used @RISK in the 1990’s to model such factors as ice floe size, strength and movement. Hundreds of years of simulated ice floe impacts were used to determine the design ice load for the bridge piers. Much of the research carried out in the field and in the laboratory prior to the construction of the bridge focused on the ideal distributions to model the ice and environment parameters used in the @RISK models.
The author of this case study acted as principal ice consultant to the bridge builders. He will report on the original ice load models, and a more recent analysis which has used 12 years of measured loads and additional ice observations as a comparison.
An examination of an innovative approach to Schedule Risk Analysis on Managed Services Contracts employing Palisade’s @RISK on SAP based data sets.
Also considered is a comparative analysis with traditional Monte Carlo, Gantt based schedule analysis techniques, where such techniques may not always be optimal for work of a strongly repetitive nature. In conclusion the proposition is offered that an @RISK SAP based analysis method offers powerful advantages including high visibility of gains from Improvement Opportunities and Risk Mitigations. Further added values include strong indicators of the contract Earned Value position and the opportunity to easily calibrate ongoing completion cost against actual past performance. The final project cumulative performance distributions may also be added to corporate knowledge banks enabling the accurate estimation of future programme performance. Finally a comparative analysis is provided examining the optimal usage of both the "actual" and "simulated" (Monte Carlo) techniques using Palisade tools.
This presentation was awarded winner of "Best Use of Technology in Risk Management" at the 2010 Risk Management Awards, sponsored by Risk Management Professional magazine.
Strategic Transport Decision-Making:
The SIMSIGHT approach based on Risk Simulation and Scenario Foresight
The proposed presentation concerns a brand new approach, SIMSIGHT, involving the combination of risk simulation and foresight based on scenario analysis for decision support. SIMSIGHT aims at providing decision support for transport decision making with a focus on awareness of feasibility risk. First, the SIMSIGHT modelling framework and the theories behind are described and afterwards SIMSIGHT is illustrated by an example concerning examination of an infrastructure project for a new airport in Greenland selected among three alternatives for upgrading and/or replacing the present airfield at Nuuk. The SIMSIGHT analysis aims at shedding light on the robustness of the socio-economic feasibility relating to undertake such a major infrastructure investment.
Providing suitable decision support for strategic transport decision making is a topic of growing concern. For large infrastructure investments, to exemplify with one important transport topic area, assessments are needed that explore the robustness of decisions that have been taken based on comparison of already examined alternatives. For large infrastructure projects comprehensive assessments are indeed needed. Typically, such investments have many-sided consequences which ought all to be taken into consideration to seek out the best alternative from a set of candidates that has come forward from the preparatory planning and design phases. In previous presentations among others at the Palisade risk conference methodologies of both a deterministic and of a stochastic type have been set out with the COSIMA-ROAD and CBA-DK approaches that have been tested on real-world cases (Salling, 2006; Salling, 2010). The COSIMA-ROAD and CBA-DK are both based upon Microsoft Excel platforms allowing for the add-in feature of @RISK. The CBADK model, furthermore, forms the basis for transport infrastructure planning containing a cost-benefit analysis module and a risk analysis module.
The purpose of this presentation is to present an approach to explore the robustness of a decision about implementing a certain alternative, for example having been based on applying either the COSIMA-ROAD or the CBA-DK approach. The relevance of examining robustness is related to the issues about uncertainty and risks, which may take a major role in connection with large scale projects, where factors such as construction costs and demand prognoses are uncertain for a number of reasons. Clearly, the variability relating to these will dominate and have high importance as regards the long-term socio-economic return or feasibility of the investment (Salling, 2008). A special interest in this context is to explore the concepts and belief of the “fat-tails” and “over-confidence” theory concerning input parameters as concerns MIN and MAX estimates. Specifically, three input distributions are investigated within @RISK namely the Trigen (Triangular), the Beta-PERT and the Erlang distributions, all relying on subjective measures corresponding to a minimum, most likely and maximum parameter value. However, how confident are we upon the latter? Is it merely guess work and speculations or is it possible to make actual decision support based upon subjective input parameters? And finally, how does @RISK cope with entries specifically concerning openended tails, thus, how are the extreme values represented in the Monte Carlo simulation?
The presentation revolves around a fixed case study concerning the enlargement of airport alternatives in the Capital of Greenland, Nuuk (Salling and Banister, 2009). A set of scenarios are created in order to assess the various input parameters to the SIMSIGHT approach where after a set of resulting accumulated descending graphs are depicted and scrutinised.
Using Quantitative Net Present Value Risk Analysis to Support a Multi-pass Project Risk Management Process
The Association for Project Management’s guide to risk management (PRAM 2004) advocates the use of a top-down multi-pass approach. It recommends undertaking between 2 and 5 cycles of this iterative process to ensure that the project strategy is optimised from a risk perspective. Each cycle takes the risk management process to further levels of detail. Eventually, after key strategy decisions have been taken and the project plans have reached an acceptable level of maturity, the risk management process enters something that more closely resembles a steady state. However, the principle of using a top down approach is often inadequately understood and thus not followed in practice.
This paper is based on the (fictional) example of a road bridge project and illustrates how a multi-pass process might be applied in one case. The example is used to illustrate a number of important points. In particular, it shows how insights developed during each cycle of the process are used to influence subsequent cycles. It commences with a constructively simple quantitative risk model of the type that can be run in Monte Carlo risk tools such as @RISK for Excel. It then shows how the structure established by this first-pass model can be used to develop more detailed models designed to answer questions related to key project strategy risks.
Use of a top down approach helps to support a critical feature of risk analysis: one must make sure that the analysis addresses the right question. For the purposes of a first pass risk analysis, identifying the right question should start with understanding the fundamental purpose of the project. One might think that the purpose of building a road bridge would be to improve the efficiency of road transport links. However, from the perspective of the contractor, who is the subject of the example, the fundamental purpose of the project is to make money. If the first pass analysis fails to address the issue of profitability, it will fail to direct the risk management process correctly.
This paper demonstrates the how, in the example project, successive iterations of a developing NPV risk model can be used to support the following decisions:
Should the contractor be involved in this project?
What is the best choice for the bridge location?
What is the most risk efficient contracting strategy?
How can the contractor differentiate itself from its competitors?
Since these decisions would be fundamental to the project concerned, it makes sense for them to be made before the risk management process takes on a more tactical purpose, e.g. by managing a large number of risks on a case-by-case basis in a risk register. This paper thus demonstrates how quantitative analysis can be used, in its own right, to support a capable risk management process of the nature required to achieve Level 4 as defined by the Project Risk Maturity Model.
Advanced Features of DecisionTools Suite 5.7 and @RISK 5.7
Join us for this discussion of the latest features in @RISK and the DecisionTools Suite, led by Palisade president Sam McLafferty. New support for 64-bit Excel, the @RISK Library, and upcoming support for high performance computing (HPC) clusters will be covered. Bring your questions and topics of interest.
Agricultural Food Production and Distribution Management Decisions Resolved by The DecisionTools Suite
Agricultural food production and distribution is an industry wrought with uncertainty. There are implications for food safety, supply chain, logistics, economics, and customs and trade policy. All of these factors need to be well understood and managed in dynamic and sensitive economic, political and natural environments. Some of these questions will be addressed in this presentation using select tools within The DecisionTools Suite.
This session covers some ideas in modelling best practices, in both Excel and @RISK. Topics within the general Excel section include issues in model design, structure, formatting, error-checking and sensitivity analysis, as well as a brief overview of key functions required to create dynamic and flexible models. The @RISK session covers a selected set of topics, focussing on some of the powerful but slightly lesser known features of @RISK, such as the use of the Theo functions, and the correct use of correlation as a modelling approach to capture dependencies.
Customised Software Applications using @RISK & VBA
@RISK and DecisionTools Suite software ship with full-featured development environments that allow you to create custom applications using Palisade technology directly in Excel (Excel Developer Kits or XDKs). You can customise the application interface to include only what the users need, hiding unused @RISK functionality and preventing user access to the underlying model logic. You can also automate processes like reporting, generating only the charts and data you want. The result is a perfectly tailored application ready to roll out to your workgroup. And because the application is in Excel, the training required for users is minimal.
Palisade Custom Development has written applications for cost estimation, asset management, retirement planning, oil and gas prospecting, and more – all utilising @RISK technology in Excel. In this presentation, we will cover as many examples of custom applications as time allows.
This session will show you how to use the elements of the new DecisionTools Suite as a comprehensive risk analysis, optimisation, and statistical analysis toolkit. Each of the products in the Suite — @RISK, RISKOptimizer, Evolver, PrecisionTree, TopRank, StatTools, and NeuralTools — will be presented, showing how they can be used to solve practical problems in the real-world. Pick up hints and tips for using the products together.
RISKOptimizer and Evolver use powerful genetic algorithms to perform optimisation in Microsoft Excel. RISKOptimizer builds on traditional optimisation by adding Monte Carlo simulation to account for uncertain (stochastic), uncontrollable factors in your optimisation problem. This session introduces you to these powerful tools, showing you how to set up a model, define constraints within the model, and ultimately arrive at the optimal outcome. Examples of resource allocation, budgeting, and scheduling will be included.
This introduction to @RISK will walk you through a risk analysis using various example models. Key features of @RISK will be highlighted, and new enhancements in version 5.7 will be pointed out along the way. You will experience the intuitive interface of @RISK as you define distributions, correlations, and other model components. During simulation you will be able to see all charts, thumbnails, and reports update in real time. View results with a variety of graphing options, including new cumulative-histogram overlays, scatter plots in scenario analysis, and more. There’s so much to see, we’ll cover as much as time permits.
Introduction to Project Risk Management
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
In this session we will learn how to use Palisade’s two data analysis tools: StatTools and NeuralTools.
StatTools is a Microsoft Excel statistics add-in. This session will cover how to perform the most common statistical tests, and will include topics such as: Statistical Inference, Forecasting, Data Management, Summary Analyses, and Regression Analysis.
NeuralTools imitates brain functions in order to “learn” the structure of your data. Once NeuralTools understands the data, it can take new inputs and make intelligent predictions. The new predictions are based on the patterns in known data, and offer uncanny accuracy. NeuralTools can automatically update predictions when input data changes, and it can even be combined with Palisade’s Evolver or Excel’s Solver to optimise tough decisions and achieve desired goals. We will demonstrate, using easy-to-understand examples, applications of NeuralTools predictions.
This session covers the choice of the appropriate distribution in @RISK. A variety of approaches are presented and compared, including pragmatic, theoretical and data-driven methods. The use of distributions to treat a variety of risk modelling situations is discussed, and some new distributions and features in v5.7 are shown.
Select Industry Applications of
The DecisionTools Suite is used in a wide variety of industries for a range of applications. In this presentation, we will use a number of simple examples to illustrate how the Suite can be used in finance, pharmaceuticals, energy and other industry sectors.
Inga Ambrasaite Scientific Assistant
Decision Modelling Group at DTU Transport
Inga Ambrasaite is currently employed as a scientific assistant in the Decision Modelling Group at DTU Transport. She graduated from the Technical University of Denmark in September 2010 with a Master degree in Civil Engineering. Her thesis entitled Comprehensive Infrastructure Assessment based on the Rail Baltica Case, which investigated the appraisal of the transport corridor through the three Baltic countries to Poland. The main occupational skills are within the area of transport planning and engineering – transport infrastructure project evaluation using Decision Support Systems, Cost-Benefit Analysis, Multi-Criteria Decision Analysis and Risk Analysis.
Ms Ambrasaite is schedule to commence her PhD study May 2011 in the area of transport infrastructure assessment by the use of composite analyses combining cost-benefit analysis, multi-criteria decision analysis and quantitative risk analysis.
Stephan Beeusaert Sales & Business Development Manager Palisade Europe
Stephan Beeusaert, Sales and Business Development Manager for Palisade Europe, has been with the company for over 6 years. Stephan holds a BA in international business and economics from the University of Applied Sciences Cologne, Germany. Steve has worked for several multinational corporations in Europe and the US.
Christopher Brand Captum Capital Limited
Chris Brand is an Associate at Captum Capital Limited, where he provides consulting and training services to early stage life science companies in the behavioral aspects of business development. He is also a Research Assistant at Birkbeck, London University where he is active in the psychology of decision making. Chris holds an MSc in Cognitive and Decision Sciences from University College, London, an MA in Philosophy from the University of York and a BSc in Philosophy and Psychology from the University of Keele.
Dr Michael Brand Co-founder and Director
Captum Capital Limited
Michael Brand is a founding director of Captum Capital Limited, an innovative consulting company which provides business development services to early stage life science companies. Captum offers a series of training courses in business development, including the highly successful Valuing Life Science Technology MasterClass, which has been attended by over 350 executives. Michael spent most of his career in the USA holding senior executive level positions in multi-national corporations, including a venture capital company. He has successfully negotiated international joint venture, licensing and investment agreements. He holds a PhD from Imperial College, London, a MBA from the Sloan School, MIT, Boston, and the Investment Management Certificate of the CFA Society of the UK; he is a Fellow of the Royal Society of Chemistry.
Senior Systems Analyst / Designer
TATA Consulting Services
Vojo Bubevski comes from Berovo, Macedonia. He graduated from the University of Zagreb, Croatia in 1977, with a degree in Electrical Engineering - Computer Science. He started his professional career in 1978 as an Analyst Programmer in Alkaloid Pharmaceuticals, Skopje, Macedonia. At Alkaloid, he worked on applying Operations Research methods to solve commercial and pharmaceutical technology problems from 1982 to 1986.
In 1987 Vojo immigrated to Australia. He worked for IBM™ Australia from 1988 to 1997. For the first five years he worked in IBM™ Australia Programming Center developing systems software. The rest of his IBM™ career was spent working in IBM™ Core Banking Solution Centre.
In 1997, he immigrated to the United Kingdom where his IT consulting career started. As an IT consultant, Vojo has worked for Lloyds TSB Bank in London, Svenska Handelsbanken in Stockholm, and Legal & General Insurance in London. In June 2008, he joined TATA Consultancy Services Ltd.
Vojo has a very strong background in Mathematics, Operations Research, Modelling and Simulation, Risk & Decision Analysis, Six Sigma and Software Engineering, and a proven track record of delivered solutions applying these methodologies in practice. He is also a specialist in Business Systems Analysis & Design (Banking & Insurance) and has delivered major business solutions across several organisations. He has received several formal awards and published a number of written works, including a couple of textbooks. Vojo has also been featured as a guest speaker at several prominent conferences internationally.
Dr Cammaert joined the Enterprise Risk Management group of DNV (Det Norske Veritas) in December, 2001, and moved to DNV Technology Services in January 2005. Since January 2007 he has been the Programme Director, Arctic Technology, for DNV Research and Innovation. He has led a multi-discipline group of researchers working in the areas of ice mechanics, Arctic metocean, and advanced computational mechanics. He retired from DNV in September 2010, but still works with DNV as a part-time Principal Researcher. Prior to joining DNV he had his own consultancy in Canada, while he was also a Professor of Ocean Engineering at the Memorial University of Newfoundland. From 1976 to 1988 he was employed by Acres International Limited, of Toronto, where he worked on specialist risk assessment studies in offshore, marine and Arctic engineering applications, and he also directed the Acres Hydraulic Laboratories in Niagara Falls for two years. He began his career in Arctic and Ocean Engineering as an Assistant Professor at Memorial University in 1971.
Gus is associate Professor (part-time), Arctic Engineering, Offshore Engineering Section, Delft University of Technology. Responsibility includes helping to develop a Masters level course in Arctic Technology. Also Principal Researcher (part-time) within the Arctic Technology Programme of DNV Research and Innovation, in advising on joint industry projects involving Arctic research.
Tian Claassens Director Bigen Africa
Tian Claassens holds a B.Sc Chemical Engineering degree from the University of Cape Town (1983), an M.Sc Eng degree (1985) and an MBA (1994) both from the University of the Witwatersrand in South Africa.
In a career spanning more than 25 years Tian has gleaned extensive knowledge and experience in the evaluation, structuring and financing of large-scale projects across a wide range of industries. These include the chemical and water treatment, mining, motor, paper and pulp, textile and wool processing, heavy engineering and manufacturing industries. This experience was gained through positions in merchant banking with Rand Merchant Bank, project evaluation and development with the Industrial Development Corporation of South Africa and in development of large-scale automation systems with Nextep Systems Integrators.
Tian is currently a director of Bigen Africa – a South African based consulting engineering and management firm. In post-apartheid South Africa, there is a strong focus on the development, implementation and finance of infrastructure to extend service delivery to all sectors of the population and regions of the country that were disadvantaged under the apartheid regime. With limited government financial resources to fund the infrastructure needed there is increasing focus on alternative financing mechanisms. Against this background, Bigen Africa is increasingly fulfilling the role of an intermediary between government institutions responsible for infrastructure and financing institutions including commercial banks, DFI’s and donor organisations.
In this role as intermediary the skills and experience of Tian has proven invaluable to “translate” between different industries or sectors and in establishing the concept of integrated project development or preparation (“IPD”). IPD is the key process through which project risks are identified and mitigated to the satisfaction of all funders of an infrastructure project. Critically, the IPD process also establishes the mechanisms and capacity to manage risks on an on-going basis through-out the project life-cycle. IPD plays a critical role in unlocking finance for infrastructure projects and in the IPD process, one of the key tools employed is the demand model as presented at this conference.
Tian resides in Pretoria, South Africa and is married with four children.
John Ducker Senior Risk Manager Cassidian Systems
2003 – Present: Cassidian Systems (previously EADS DS UK), Senior Risk Manager.
2000 – 2003 : Tadpole Geospatial Systems, Program Manager.
1993 – 2000 : Independent Consultant
– 1993 : Various Senior Engineering and Representative roles within the UK MoD and Industry.
Areas of Expertise:
35 years of senior enterprise & project management experience within a broad range of IT, Engineering and Corporate Business Systems.
Career specialities in Risk, Project and Program Management; Consultancy and Engineering Audit.
Exposure to all aspects of Risk and Project Management in the Defence, Utility and Commercial engineering sectors.
Andrew Evans Decision Analyst - Decision Analysis Group
Andrew Evans is a Decision Analyst within Unilever’s Decision Analysis Group. His role includes providing internal consultancy on Decision Analysis for project teams and training and coaching finance professionals on the Unilever Decision Making Under Uncertainty (DMUU) Programme. He also works on the embedding of Decision Analysis through the provision of support services to DMUU Practitioners. Prior to joining Unilever, Andrew worked in the Mobile Resource Management (MRM) sector of the IT industry. He is a Chartered Member of the Institute of Personnel and Development and a Lead Practitioner within the Society of Decision Professionals.
Tayo Fabusuyi Lead Strategist Numeritics
Tayo has more than a decade of experience in the field of Management Science/Operations Research. He has particular interest and expertise in the applications of multiple criteria decision analysis (MCDA) tools for strategic planning purposes and in the modelling and analysis of prioritisation and allocations decision issues.
Tayo is the co-founder and lead strategist at Numeritics, a Pittsburgh based consulting practice. At Numeritics, he sets the direction for the firm’s strategy and operations management unit which includes strategy formulation, prioritisation and resource allocation, risk management, scenario planning and performance measurement engagements. Prior to this he worked at the African Development Bank where he took the lead in the design and implementation of the Bank’s corporate balanced scorecard (BSC).
His expertise in MCDA has been utilised in determining how banks can minimise exposure to various forms of risks while maintaining the appropriate combination of asset and liability that maximises shareholders’ wealth. It has also been applied in the manufacturing sector where he has conceptualised and implemented MCDA models that align firm’s operational activities with their strategic goals.
Tayo graduated with highest distinction from Carnegie Mellon University with a M.Sc. in Public Policy and Management with a concentration in Information Systems and Management Science. He also received an M.Phil. degree in Economics from the University of Oxford where he was an American Institute of Economic Research Fellow. He has given presentations at various forums on productivity and resource allocation issues and is an active member of INFORMS.
Adam Grove Statistician Mott MacDonald
Adam Grove is a statistician, who specialises in investment planning. He has developed several risk model applications for UK water companies, which calculated the risk to service at component level.
At University he covered a wide range of statistical subjects including Monte Carlo methods, statistical theory, optimisation and programming, in both under-graduate and post-graduate courses.
Saurabh Gupta Indian Institute of Foreign Trade
Saurabh is currently studying for his Masters in Quantitative economics at the ‘Indian Statistical Institute’, Delhi. He has expertise in software engineering, market Research, and data analysis.
Mufeed Hajjaji University of Huddersfield
Mufeed Hajjaji graduated in 1998 with a BSc degree in Industrial engineering from Alfatah University- Tripoli, Libya. He worked as project engineer/ Manager in a Libyan private engineering company for over six years. He attained a MSc in CIMM from the University of Huddersfield in 2008. He is now completing a PhD in Project Management at the University of Huddersfield.
Frank Lyhne Hansen Leader, Enterprise Risk Management
Frank is leader of the economic and financial modelling team in Enterprise Risk Management. He is experienced both within the financial and non-financial sector and is a member of the PwC steering board on Solvency II. Frank is a specialist in Solvency II, Basel II and economic capital.
Frank has extensive experience in operational, financial and strategic risk management. This includes the development, description and analysis of models as well as implementation, discussion and elaboration of economic models for the total economic optimisation and preparation of management reporting.
Frank has served as project and program manager on several major projects both in Denmark and abroad. In addition, Frank has a long experience of teaching as an associate professor on CBS (financial) where he teaches risk management. Frank has taught at CBS since 1996 and has a large network and extensive experience in teaching in risk management, statistics and finance.
Randy Heffernan Vice President Palisade Corporation
Randy Heffernan started with Palisade in 1997, and helped the company expand with its first overseas office in Plymouth, England, in 1998. Further geographic expansions included London in 2002 and Sydney, Australia in 2005. He has held a variety of roles in sales, marketing, and management, and currently oversees much of the corporate operations. Randy works closely with the sales staff to understand client needs and liaise with software development. Randy holds a Bachelor of Science degree in Business Management and Marketing, and an MBA, both from Cornell University.
Dr Christian Hofstadler Associate Professor Institute of Construction Management and Economics, Graz University of Technology, Lessingstraße
Dr Christian Hofstadler is Associate Professor at the Institute for Construction Management at Graz University of Technology, Austria. He has lectured extensively at conferences and engineering universities around the world. Dr Hofstadler is an expert at the Austrian Standards Institute and the International Federation for Structural Concrete (FIB), and serves as a juridical certified expert for civil engineering in Austria. He is the author of “Construction Sequence Planning and Logistics in Construction Operations” and “Formwork Works – Technological Foundations, Fair-faced Concrete, Process Comparison, Sequence Planning, Logistics and Cost Estimation” (both written in German).
Martin Hopkinson Principal Consultant QinetiQ
Martin Hopkinson is a principal consultant with QinetiQ, specialising in risk management and governance. Prior to his eleven years in consulting, he gained ten years project management experience in the UK defence industry. He has since worked on projects in both the defence and civil sectors, including ship construction, IT infrastructure, the steel industry and the UK railways infrastructure.
Martin has made significant contributions to Association for Project Management (APM) guides on both risk management and the governance of project management. He was lead author for the Risk Tools and Techniques chapters in the 2nd edition of the APM’s PRAM Guide (2004) and chaired the group that produced Prioritising Project Risks (2008). His most recent publication is The Project Risk Maturity Model (2011), a book published by Gower with a working copy of the tool that has been used to assess risk management capability on projects with a combined value of more than £60 billion.
Dr Mirek Janusz Software Engineer Palisade Corporation
Mirek Janusz is a software engineer at Palisade Corporation. He holds a masters degree in computer science from Cornell University. He helped develop Palisade applications for risk analysis, statistical analysis and optimisation, and has assisted other companies in integrating Palisade's Developer Kits into their own applications. He is the lead developer for Palisade's Excel add-in for neural networks, NeuralTools.
Dr Wilhelm K. Kross Director of Value & Risk AG Kross Consulting
Dr Wilhelm K. Kross is a recognised expert in the fields of project- and risk management. As a director of Value & Risk AG, Dr Kross has worked for banks, IT services providers, and energy traders since early 2000. In the 1990s he applied his expertise to industrial projects in North and South America and Africa. He has also held various positions as a trustee, manager, or director of professional bodies and interest groups, including his current appointment as VP Finance of the PMI Frankfurt Chapter. Dr Kross obtained a postgraduate degree in engineering from RWTH Aachen, Germany, an executive MBA from Athabasca University, Canada, and a doctoral degree in finance from the European Business School, Oestrich Winkel, Germany.
Martien Lathouwers has worked within ARCADIS on risk management in the broadest sense for 8 years. As such he plays a role in large infrastructural projects such as flood defences, highways and railway projects in the Netherlands. His knowledge areas include logistics, project management and safety. In project and program management he translates risks into planning and cost estimates using probabilistic tools. He is a teacher on the use of risk-related tools in project management to principals for the National Program of Flood Defence in the Netherlands.
ARCADIS is an international company providing consultancy, planning, architectural design, engineering and management services for infrastructure, water, environment and buildings. With 15,000 people worldwide and €1.8 billion in revenues, we develop, design, implement, maintain and operate projects that improve mobility, enhance sustainability and raise the quality of life, for clients from the public and private sector around the world.
Jon Lijnes Specialist Advisor Bigen Africa
Jon Lijnes holds a BSc Civil Engineering degree from the University of Cape Town (1977), is a registered Professional Engineer in South Africa and a Fellow of the Water Institute of South Africa.
In a career spanning more than 33 years Jon has gleaned extensive knowledge and experience in the development, planning, conceptual design, detailed design, project management and construction supervision of Civil Engineering projects (mainly in the Utility Services discipline) to the total estimated value of some Є500 Million. As a Director/Shareholder of BIGEN Africa Consulting Engineers, he gained extensive knowledge and experience in “Looking at the Big Picture” on numerous large Water Services related projects. Jon has worked as far afield as Nigeria, Mozambique and Malawi and is currently based in Cape Town, South Africa. He has been happily married for 33 years and has two sons, one of whom is a Post Production Supervisor with a large Events Company in Johannesburg and the other is a Graphic Designer currently working as a Chef in Amsterdam. Jon has also recently become a Grandfather.
Jon currently runs a one man practice from his home in Cape Town and provides consulting services to several Consulting Engineering companies in South Africa. His association with Bigen Africa continues as a specialist advisor on various large-scale projects and importantly he is intimately involved in the development and application of the demand model as presented at this conference.
Sam McLafferty President and CEO
Sam McLafferty is Palisade's founder, president, and CEO. He started the company in 1984 with the release of PRISM, a stand-alone Monte Carlo simulation package for DOS on the PC. PRISM later evolved into @RISK for Lotus 1-2-3, and then for Excel. Sam is Palisade's lead developer, with over thirty years of programming experience. He works closely with the technical and sales staff, ensuring that customer feedback is heard. He personally oversees the development and evolution of every one of the software products Palisade sells. Prior to Palisade, he was a risk analysis consultant.
Mark Meurisse Managing Director
Mark has a 15 year history of providing intellectual development services for risk, opportunity, and decision assessment to private industry and the government sector. Meurisse joined Palisade in 2003. His consulting experience and training seminars and workshops have been delivered throughout North America, Oceana and Asia, and he has consulted on risk analysis projects for clients in the oil and gas, finance, pharmaceutical, agricultural, natural resources, energy, defence, and aerospace industries. The list of clients Mark has worked with include Shell, Westpac, BHP Billiton, Australian Taxation Office, PricewaterhouseCoopers, Thiess, MetLife, KPMG, Austin Energy, HP, Georgia Pacific, Telstra, Evans & Peck, AWAS, Futron, Tyco Healthcare, Mercer Oliver Wyman, Merial, John Deere, the US Air Force, Cornell University, and the US Coast Guard.
Before coming to Palisade, Mark had 11 years consulting, marketing, and research experience in bank credit, agriculture, commercial real estate, finance and environmental engineering. His analytic, modelling, and research expertise include risk analysis, simulation, sensitivity, stress testing, causal flow analysis, market power, geographic information systems, and public policy. He holds a BS in economics from Oregon State University and an MS in agricultural economics from Texas A&M University and is the author or co-author of 9 publications.
Scott Mongeau Founding Director
Scott Mongeau is founding director of Biomatica BV (biomatica.com), a consultancy specialising 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. He is in the Global Executive MBA (OneMBA) program at Erasmus Rotterdam School of Managment, where he also holds a Masters in Financial Management. He has a Certificate in Finance from University of California at Berkeley, a Masters in Communication from 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 resides in the Netherlands.
Dr Javier Ordóñez Director of Custom Solutions
Dr Javier Ordóñez holds a BS in Civil Engineering from the Universidad de Cuenca, Ecuador and a MS in Project Management from the University of Maryland. Javier earned his PhD from the University of Maryland performing research on project risk analysis. His current research deals with cost and schedule integration and correlation issues through the use of Bayesian belief networks.
Javier's experience is in the areas of construction and project management, optimal project and capital investments selection, earned value management, engineering and project risk analysis, and operations research applications to engineering and management problems.
Javier has taught as an adjunct professor in the Project Management Program at University of Maryland and provides training in risk and decision analysis. He is also registered as a Project Management Professional (PMP).
Sergio Pinar is a Market & Risk Strategy Analyst at EDP Renováveis, a world leader company in the renewable energy industry with presence in the most important markets. Sergio’s main responsibilities include the valuation of EDPR global risk exposure and the assessment in the risk management strategies. He performs analyses about portfolio value, diversification effect, hedging policies, financing risk, pipeline delivery and operational risk. Prior to joining EDP Renováveis, Sergio served as a Consultant at McKinsey & Company. Sergio holds a Master in Industrial and Electrical Engineering from Universidad Politécnica de Madrid.
Dr Ionut Purica Executive Director
Advisory Center for Energy and Environment
Presently a senior researcher in the Romanian Academy’s Institute for Economic Forecasting, and Executive Director of the Advisory Center for Energy and Environment, Dr Purica was also a counselor of the Minister of Economy and previously the Minister of the Environment and an expert for the Parliament of Romania. He participated in the elaboration of the EU accession strategy for Romania and the energy (electricity and heat) strategy (for the Ministry of Economy and Trade) and did risk analysis and transaction structuring and project management with USEA, JBIC, MARSH, ITOCHU, MVV, etc.
Previously Dr Purica worked as a project officer for energy and infrastructure in the World Bank, in Romania and the Balkans (e.g. energy Assessment in Kosovo 1999), being trained in project guarantees, value at risk and procurement. His initial expertise in engineering stems from being a director for international projects of the Romanian Power Company RENEL and senior engineer managing a joint Atomic Energy of Canada Ltd-IMG-Bucharest quality engineering group for the manufacture of nuclear reactor components for the CANDU units in Romania. He worked also as an international researcher for ENEA Rome – the Italian Commission for Energy New Technology and Environment – and as an associate researcher at ICTP Trieste.
Dr Purica has authored books in his field of expertise (www.icpress.co.uk/chaos/p656.html) and published articles in journals like Risk Analysis, IEEE Power Engineering Review, Foundations of Control Engineering, etc. He took his second PhD in economics, (the first one in Nuclear Energy Engineering) and, he is also teaching a course in Risk management to masters of science in the Polytechnic University of Bucharest and the Ecological University.
Dr Michael Rees Consultant
Michael Rees is an independent expert who provides quantitative decision-support to senior executives facing major decisions on strategy, financing, business structure, transactions, valuation and portfolio optimisation. He also leads training courses in financial modelling, risk modelling and related topics for client staff of all levels, and - having worked very closely with Palisade since 2004 - is the most experienced trainer of Palisade products in Europe. His aim is to provide high value-added services that combine his experience in business and finance with advanced quantitative modelling skills.
Michael has over 20 years of business and finance experience, including approximately 10 years as an independent consultant. Prior to this, he was a Vice President at J.P. Morgan and a Partner at Mercer Management Consulting (now Oliver Wyman). He has lived and worked in several countries, and speaks fluent French and German.
Michael has a Doctorate in Mathematical Modelling and Numerical Algorithms, and a BA with First Class Honours in Mathematics, both from Oxford University in the UK. He has an MBA with Distinction from INSEAD in France. He has studied for the Certificate of Quantitative Finance, graduating top of the class, and also receiving the Wilmott Award. He is the author of Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level (John Wiley & Sons, 2008).
Dr Kim Salling Assistant Professor Technical University of Denmark (DTU Transport)
Dr Salling is currently employed as an assistant professor at the Department of Transport at the Technical University of Denmark (DTU Transport). He defended his PhD thesis entitled: Assessment of Transport Projects: Risk Analysis and Decision Support, November 2008. The thesis later received an honorary prize (2009) from the Professor PH Bendtsen foundation. Kim furthermore holds a Master’s degree in Engineering within socio-economic evaluation methodologies and decision support systems with special emphasis on cost-benefit analysis and risk analysis.
His main topic of interest is transport planning and decision support where he currently works in a collaborative research project (a.o. with Oxford University and Princeton University) concerning uncertainties in transport project evaluation granted by the Danish Research Council in the period from 2009-2012. This project seeks to investigate the common bias in transport planning, i.e., overestimation of transport related time benefits and underestimation of the investment costs (so-called Optimism Bias).
Dr Hans Schjær-Jacobsen Professor Copenhagen University College of Engineering
Hans Schjær-Jacobsen is a Professor at the Copenhagen University College of Engineering where he also is a Director of Research, Development, and Innovation. He holds a Master of Science and a PhD degree in Electrical Engineering from the Technical University of Denmark, and also a degree in Business Administration from the Copenhagen Business School. Previously, he held managerial positions with industrial companies as well as institutions for management consulting, training, and education. He also served as a teacher and researcher at different universities and has published a number of scientific papers within the areas of applied mathematics, computer-aided-design of communication systems, and decision making under economic uncertainty.
Ashutosh Sharma Indian Institute of Foreign Trade
Ashutosh Sharma is currently pursuing his MBA (International Business) from the Indian Institute of Foreign Trade (IIFT), Delhi. He graduated from one of the premier engineering institutes of India, NIT Karnataka, and has worked for an American MNC called Cypress Semiconductors as an Applications Engineer. He is also a CFA candidate. He was the international finalist for a competition conducted by Yes Bank, India, on the micro finance sector.
Ashutosh is excited about entrepreneurship and is passionate about developing sustainable business models. He has an interest in studying Base-of-the-Pyramid theory and he has worked for many non-profit organisations including ACTED SAMN, and Prayas Delhi.
Jan Van Broeck Co-founder and International Partner Threon
Jan Van Broeck is Co-founder and International Partner in Threon, an international organisation specialised in Project, Program and Portfolio Management. As an expert in the domain of Strategic Portfolio Management, he assists senior management in organisation towards successful deployment. As Past President of the Belgium Chapter of the Project Management Institute (period 2004-2005), he actively promotes the profession of “Project Management” in the European region and is a regular speaker in seminars at Universities and business schools. He has occupied several senior management and executive positions in the domain of outsourcing, data center operations and business development. Jan Van Broeck is a PMI certified Project Management Professional, and holds a degree in Civil Engineering (construction) from Ghent University and an MBA of the University of Antwerp.
Ian Wallace Consultant & Trainer
Ian is a qualified accountant (ACMA) and spent the first 10 years of his career working in finance functions within the pharmaceutical and precious metal refining industries. Here he gained valuable experience in managing staff, preparing financial and management accounts, and working closely with business managers to help develop project appraisals, corporate plans and annual budgets.
Ian then decided to move into management consultancy with KPMG and worked on a wide variety of interesting projects throughout Europe and the Middle East, both in the private and public sectors. Most of his work was project management related and involved the selection and implementation of the latest systems and business processes within the finance function. Work included preparing strategy studies and business cases for change, PFI and supplier evaluations, recruiting project teams, leading systems design and working with all the management and stakeholders connected with the change. As a result, Ian has considerable experience of project management methodologies such as PRINCE 2 and others.
It was during the course of this work that Ian came across Monte Carlo Simulation and @RISK. He found it such a useful tool for managing expectations, developing risk-efficient plans and getting adequate resources for his projects that in 2001 he decided to specialise in the technique. Ian has now been working closely with Palisade since 2005, and during this time has delivered numerous on-site customer training sessions, public classroom courses, web-conference training sessions, and consultancy projects.
Ian's wide experience, together with his communication skills, enable him to communicate complex subjects using everyday, easy to understand language.
Hans Waszink Director
Waszink Actuarial Advisory
Hans Waszink is an expert in quantitative financial risk modelling. He has a Master's degree in Mathematics from the University of Groningen in The Netherlands, a Master's Degree in Actuarial Sciences from the University of Amsterdam, and an MBA from London Business School. He is a Fellow of the Dutch Actuarial Society and the British Institute of Actuaries.
Mr Waszink is director of Waszink Actuarial Advisory, a niche consulting firm specialising in risk management for the Financial Services Industry.
Peter Wood Director Peter Wood Associates Ltd
Peter is a director of Peter Wood Associates Ltd, a project management consultancy that specialises in risk-based decision support to capital investment. He has established a reputation for being able to combine subjective analysis and rationalisation of complex problems with probabilistic modelling techniques, to create innovative and robust practical solutions.
Peter is a Chartered Architectural Technologist who developed project management skills during six years with the US Navy Europe. He then joined the engineering consultants WS Atkins, building on project management experience before making the transition to project consultancy, risk analysis and management. His experience includes private and public sector clients in a variety of sectors including rail, infrastructure, construction, defence, utilities, process and nuclear industries.