Broadleaf Capital International uses Palisade software in their work as a specialist risk management consultancy. The company has helped clients in numerous industries analyze, quantify, and make decisions around risks. Dr. Stephen Grey, Associate Director of Broadleaf, discusses how @RISK has been used to help his clients adopt smarter approaches to managing their company’s and organization’s approach to uncertainty in mining and mineral processing, oil and gas, infrastructure, building and construction, IT and other systems, as well as defense and other government procurements.
Background: Clients in Need
Dr. Stephen Grey and his colleagues at Broadleaf Capital International in Cammeray, Australia, have spent decades helping steer clients towards sound methods of planning projects, from deciding where to invest to ensuring that plans and estimates are realistic before commitments are made. Quantitative analysis is only part of the process, but it is extremely powerful, especially in the later stages of planning and for a final investment decision. Clients come to his consultancy either well-aware that they need a risk analysis conducted on their project, or “we get clients who are in difficulty and don’t understand why,” says Grey. “Once they see there’s a way to get a grip on uncertainty, they’re very keen to do that.”
There are of course, clients who don’t see the necessity of risk analysis at all. “We still get people who don’t think about this aspect of the project,” says Grey. “They simply add on an extra five percent for contingency regardless of the risk.”
Grey explains that for many institutions and businesses, quantitative evaluation, particularly of cost contingency, has become stuck using outdated methods. His theory is that project size and complexity took off much faster than computing power could keep up with. Thus, methods well suited to manual calculation were automated without being altered, rather than being updated and improved as computing power became available.
As outlined in his introduction to cost risk modeling video, Grey explains that two common methods for assessing cost uncertainty are risk event modeling and line item ranging. Risk event models are built up from a risk register, with a probability and impact assigned to each risk. Impacts may be represented by distributions and combined using Monte Carlo simulation (MCS). Line item models are based on a summary estimate, with an allowance for risk against each part of the cost, represented by distributions and combined using MCS. “These both look plausible,” says Grey, “but they are not good choices for the primary approach to analyzing the project cost risk. They introduce complicated interactions that are hard to model well.” Impacts can be accidentally double-counted, especially in delay costs, resulting in unrealistic assessments. “Both of these methods are hangovers from the days when we had to carry out the analysis by hand,” says Grey. “We can do a lot better, and make the analysis simpler.”
A New Method to Improve Project Outcome
Grey and his colleagues at Broadleaf have refined their approach to quantitative cost risk modelling over the past 15 years. A lot of this development has taken place in partnership with one of the major mining companies in Australia as their projects became larger and more costly. With price tags rising to 3 or 4 billion dollars, these projects could involve developing a mine, a power station to run the mine, a railway to get the mine’s ore to the coast, and a port to transfer the materials onto ships. Clearly, there were huge amounts of money at stake for projects of this size and the client has been at the forefront of firms in the resources sector seeking to ensure it has a realistic understanding of risk in large projects.
All companies in this sector have experienced significant cost overruns from time to time and need confidence in their estimates to protect shareholder value. When the cost of steel was especially volatile a few years ago, the challenge of incorporating uncertainty into models was brought to the fore and used as the foundation of the analysis, instead of burying the effect within the many separate items that were each affected by the cost of steel. “We decided to think about the uncertainty in the steel price and apply that to the costs, rather than think about the uncertainty in the costs and try to understand the correlations between them caused by their common dependency on the steel price” says Grey.
Thus, Broadleaf used what is now called risk factor modeling, in which any uncertain inputs, such as schedule duration, or cost of commodities, like steel and concrete, are used in a Monte Carlo simulation to produce a distribution of the total cost of the project. Several of Broadleaf’s clients “won’t consider a proposal for an investment if it hasn’t had a quantitative risk analysis performed on it, and many project teams choose to do it even if it isn’t mandatory, as they know it will improve the chances of winning approval to proceed,” says Grey.
A Proven Approach using @RISK
The process for all these clients has a consistent method; Grey or his colleagues gather relevant inputs from estimators, engineers and other project team members to identify the dominant cost drivers and describe the uncertainty in the quantities.
After incorporating these inputs into the risk factor model created with @RISK, Grey then gets outputs that show where to set targets and contingency amounts; which sources of uncertainty contribute most to the uncertainty in the total cost; and which areas of the cost contribute most to the contingency.
Grey says that Palisade software has been his tool of choice from the very beginning. “I started with @RISK in the 1980s and stayed with it,” he says. “Its rich modelling environment allows me to represent uncertainties in terms that are meaningful to the project personnel so that information can be gathered from them and used in a model in exactly the same terms. This helps them engage with the exercise and means they understand the results we produce and use them to make informed decisions.”
Associate Director, Broadleaf Capital International
New Analysis Methods for New Zealand
Similarly, another early client of Broadleaf’s, the Government of New Zealand, was convinced of the value of risk analysis after Grey modelled the uncertainty in the estimates of costs and benefits for a large IT project. The initial estimate rose markedly after work began, and the team began to explore the challenges it presented. “IT cost over runs were a contentious subject at the time as another large job had recently exceeded its forecast cost by a very large amount,” says Grey. The analysis gave all concerned enough confidence to proceed with the revised assessment of the cost to complete. “Ever since, all large government IT projects in New Zealand over a certain size or level of risk are required to have one of these analyses done before the government will consider it for funding,” says Grey. “It’s now standard practice.” This work led to the Department involved winning a KPMG innovation award that acknowledged Broadleaf’s work.
Other Examples of Broadleaf Success with @RISK
Since those first early successes, Broadleaf has gone on to assist a broad array of clients in numerous industries and sectors.
Non-Profit: Broadleaf assisted the International Organisation for Migration, a UN-affiliated body, in developing their risk management framework. Broadleaf consultants helped the management team evaluate their current approach to managing risk, and guided them in the development of a new set of tools and methods aligned with ISO 31000 (a set of international risk standards codified by the International Organization for Standardization) to be used in the future. Broadleaf facilitated the development of a two-year implementation plan with a significant training component.
Mining: Broadleaf advised one of its many engineering clients who were tasked to prepare a plan and estimate for a coal handling and preparation plant. The client needed assistance with a planning review and schedule risk assessment; they needed to show decision makers an accurate timeframe within which they would deliver the plant—however, their established time table was not yet nailed down, and relied on rule of thumb and experience rather than more quantitative methods. Broadleaf conducted a workshop with their clients to explore uncertainty in the activity durations and risk drivers affecting the project, which produced a concise informative description of the risk associated with the plan. This not only explained the uncertainties but also provided a starting point for later reviews and updates. With this more realistic information in hand, Broadleaf developed a model that allowed the client to establish a more realistic revised delivery timetable.
Beyond these examples, Broadleaf has helped clients in many other industries, including the Sports & Recreation, Rail, Property, Mining and minerals processing, and Information and communication technology sectors, just to name a few.