The risk and uncertainty for a single task may well be known with reasonable accuracy with respect to its cost and its proposed completion end date.
For a very simple project with 2 tasks we may have.
TASK ACost = £50,000 | range: £40,000 - £60,000 |
Duration= 6 weeks | range: 5 weeks – 7 weeks |
Cost = £20,000 | range: £15,000 - £25,000 |
Duration= 8 weeks | range: 7 weeks – 9 weeks |
The controlling body (steering committee) want to know what is the cost of the total project and what is the completion date?
For the simple project above with the tasks running in series i.e. the second starting after the first has completed, the project summary would be:
Cost = £50,000 + £20,000 = £70,000
Duration = 6 weeks + 8 weeks = 14 weeks
These are the figures that would appear in the project ‘base’ plan and would be reflected in the schedule.
However, if both tasks go really well then durations would be less and so would the total costs.
If the tasks are not likely to complete on time then key criteria activates the trigger and the contingency comes into play leading to the maximum times and durations.
So, the potential range is:
LOW:Cost = £40,000 + £15,000 = £55,000
Duration = 5 weeks + 7 weeks = 12 weeks
Cost = £60,000 + £25,000 = £85,000
Duration = 7 weeks + 9 weeks = 16 weeks
Overall range:
Cost = £55,000 - £85,000
Duration = 14 weeks – 16 weeks
Thus, by combining these two simple tasks (assimilating or aggregating) by adding the ranges of the individual tasks you can arrive at a summary for the whole project.
However, this simple scenario represents ‘full positive correlation’ seen earlier.
Some of the techniques referred to elsewhere [see Monte Carlo simulation] can help in combining (aggregating) risks to get to a summary position for the project.