MONTE CARLO SIMULATION CHALLENGES Monte Carlo Simulation is a very powerful and recognised risk analysis method that could increase the chances to deliver projects on time and on budget. Inaccurate or Misleading? George Box, a British statistician said: “All models are wrong, but some models are useful. So, the question you need to ask is not ‘Is the model true?’ (it never is) but ‘Is the model good enough for this particular application?’ In the application of project management, it could be rephrased as: “Is the Project Delivery Plan good enough to explain the impact of risks and uncertainties by applying the Monte Carlo Simulation method correctly?” Figure 13 - Activity Lead. Missing Corrective Actions When our project is late and over budget, usually corrective actions are taken. So, the Monte Carlo model should simulate these corrective actions in the respective iterations. It means that the project model must include conditional branches “if .. then" and risk simulation software must automatically select the right branch based on the predefined conditions. For example: if the project is more than 20 days behind schedule, then extra resources are going to be added to speed up delivery. Any project delivery model is just a proxy and it is never precisely accurate. We use it, as it still helps to drive project decisions. However, misleading forecasts are dangerous, as they may drive wrong decisions. The challenge is to understand where to draw a line between ‘inaccurate’ and ‘misleading’. Monte Carlo Simulation is a very powerful and recognised risk analysis method that could increase the chances to deliver projects on time and on budget. The method needs to be applied correctly and with the project delivery tool that supports the critical functionality, we covered in this article. 00:0 9
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