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While risk analysis won’t predict the future, combined with one’s own experience and good judgment, it can help make some strong educated guesses. Imagine that you are the captain of an expedition climbing Mount Everest. You are responsible for keeping up with supplies, monitoring the weather, and keeping your team healthy. Above all, you have to make the decisions that will keep your team together and on schedule, in spite of illness or foul weather. Make a bad call and you can often be putting your team at risk. Now that is accountability and while projects are not a case of life or death, it can often result in levels of stress or anxiety for projects when bad decisions are made. Wouldn’t it be nice to have good information in making those life or death decisions?

The rationale behind risk analysis is simple and is three words can be … knowledge is power. The more you know about what could happen, the better equipped you will be to make decisions about what to do. Making good decisions is at the heart of risk analysis. While risk analysis won’t predict the future, combined with one’s own experience and good judgment, it can help make some strong educated guesses. This is the power of knowledge and in turn that power can drive a shared understanding of what may or may not be realistic.

To the project manager, risk analysis should means a better, more realistic project schedule, project budget or whatever the project is been measured by. That’s because risk analysis is more than a blind guess about how long a project will take. It is a calculated estimate based on verified data. An­alysing risk can also identify problem areas that have caused delays on projects in the past and may slow things up again. The result is a schedule, or any other metric that is a concern for the project manager, is more accurate data. Based on this, then a project manager is equipped with a forecasting tool that allows the project with a better chance of being delivered within its tolerances..

When it comes to analysing risk, managers currently have a number of options available to them. The method that provides the most detailed information is computer modelling or simulation. This involves the creation of a computer program that performs tasks in a particular order, much like they would be performed in an actual project execution. Inserted into the program are three possible times that may be necessary for the completion of each task: a realistic estimate, a pessimistic estimate and an optimistic estimate. Once the model is determined to be fair and accurate, it is set in motion for a number of iterations. The simulation randomly selects a time for each task from the range of possible values provided. The program then combines these times, along with other factors, to produce a single iteration of the model.

Right now we are finding the two most popular pieces of software to run these simulations are:

These tools are not the solution but do provide the vehicle to identify, analysis and understand the data that drives the decisions. We should never get sucked into a tool to determine needs and want but rather to understand the source of the same needs and want. Effective decision-making should not just focus on the way risk is to be dealt with or indeed the risk log, but rather risk optimisation in pursuit of business objectives. The business concepts used in risk management decision making processes should eventually blend into everyday business decision making.

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