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L&T Institute of Project Management Uses Palisade’s Risk Analysis Software

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Using @RISK as its solution of choice for quantitative statistical modeling, the Institute, set up a study based on a typical outsourced design project of 800 hours and included 15 key activities that are characteristic of such an assignment—ranging from panel, process and layout studies, fixture design, review of design with simulation and client teams, design quality control, preparation for assembly through to final quality control. For each of these activities, the study considered the impact of eight key risk triggers such as lack of clarity on project requirements from customers, skill resource availability, environmental risks and technology.

“We chose @RISK for its ease of use and compatibility with Microsoft Excel,” said Deputy General Manager and Faculty, L&T Institute of Project Management, DrChakradharIyyunni. “@RISK imports all the analysis into Excel, which means that we can use all the formulae in the software alongside all the @RISK features—a powerful combination for statistical analysis.”

Three Point Estimations Help to Evaluate Business Scenarios

Using a three-point estimation (optimistic, most likely and pessimistic) for each of the 15 activities, the team was able to construct probability distributions in @RISK to represent the uncertainty around each activity. They then conducted simulations consisting of 15,000 iterations each as part of the experiment. This means the team was able to examine 15,000 different scenarios with the click of a mouse.

This study concluded that this kind of three-point estimation using Monte Carlo simulation was a better way of creating robust project delivery schedules as opposed to a detailed risk analysis exercise, especially for short duration projects that are the norm in the engineering outsourcing industry. This is also a more vigorous way of deriving risk schedules. For instance, it takes into consideration the risk perception and control available to the teams, which are mostly seen as ad hoc methods in other risk analysis methodologies. Furthermore, this approach would not put additional burden on delivery teams to conduct detailed risk analysis. Based on the success of this experiment, the Institute is looking to use @RISK to develop an approach that helps outsourcing project teams to develop risk mitigation strategies.

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