Managing Project Contingencies

In this blog, we will discuss project contingencies and how they can be developed from the results of the analysis. Project contingency (also referred to as margin or management reserve) is additional time or budget that can be added to the project plan to account for the possible variance from uncertainty and events and ensure that the project has a high probability of success. Before we discuss how we should set contingency, let’s take a look at two common practices that we don’t recommend:

  1. Project planners are often motivated to create shorter and less costly schedules to win a bid or get a project approved. For example, you are much more likely to have a project approved if you provide an estimate of $700 M as opposed to $1 Billion without reducing scope. So how can they reduce estimated costs without reducing scope? It’s very simple actually, just assume that there will be no unexpected problems and reduce contingency accordingly. This approach to project planning is a very common phenomenon for large infrastructure projects; as the scope is so large it can be easier to hide the true cost of risk. We don’t recommend this approach as it tends to lead to large cost and schedule over runs.
  2. Project planners in small projects may just choose to add additional contingency to account for all possible issues and therefore they will not be blamed if project is delayed and overtime. If you use unrealistically high contingencies, either as schedule margin or management reserve, this requires your organization to hold back resources and results in inefficient use of scarce resources and the inability to take advantage of opportunities.

So, if you cannot use these methods, how can we determine a realistic contingency for a specific project? The answer, as you can probably guess, can be determined using the results of the Monte Carlo analysis. Remember, the analysis takes into account risks and uncertainties and provides statistical distributions that tell us what the chance is that we will get a certain result.
So we can extend this to generate risk adjusted contingency. For example, we could determine our contingency based on p80 for cost and schedule. To do this, we would run the Monte Carlo risk analysis and calculate the contingency based on the difference between the original project plan and the P80 results.

Once we have calculated this contingency, we would put them into the plan as buffers. During project execution, we would manage the project using the original plan and monitor the buffers. As risk and uncertainties occur, it will consume the buffer, but as long as the buffer exists, the project would be completed on time and schedule. This approach is part of Critical Chain Method. In our next post, we will look at another output of simulations: sensitivity analysis, tornado and scatter plots.