Schedule Risk Analysis with Risk Drivers
A second way to determine schedule activity duration uncertainty is to analyze the probability that risks from the risk register may occur and what their effect on schedule activities will be if they do occur. With this approach, a probability distribution of the risk impact—expressed as a multiplicative factor—on the duration of activities in the schedule is estimated and the risks are assigned to specific activities in the schedule. If a risk does not occur in an iteration, then the scheduled duration does not change for that activity. In this way, activity duration risk is estimated indirectly by the root cause risks and their assignments to activities.
A risk can be assigned to multiple activities and the durations of some activities can be influenced by multiple risks. This risk driver approach focuses on risks and their contribution to time contingency as well as on risk mitigation. The risk driver method can be used to examine how various risks may affect the house construction schedule. Table 3 shows a subset of possible risks associated with the construction.
Table 3: Some Identified Risks for a House Construction Schedule
| Optimistic | Most Likely | Pessimistic | ||
|---|---|---|---|---|
| Design is incomplete | 80% | 95% | 125% | 150% |
| Site investigation is inadequate | 30 | 100 | 120 | 135 |
| Material is unavailable | 25 | 100 | 125 | 130 |
| Material is late or defective | 35 | 95 | 110 | 130 |
| Inspectors are unavailable | 30 | 125 | 150 | 200 |
| Rework will be necessary | 25 | 100 | 110 | 135 |
| Materials are purchased incorrectly | 10 | 100 | 110 | 130 |
| Soil conditions are poor | 25 | 100 | 115 | 135 |
| Owner makes changes | 50 | 95 | 110 | 130 |
Source: GAO | GAO-16-89G
According to table 3, we can suspect that the biggest risk in the construction schedule involves design and that the plan may be too aggressive in assuming that the design will be completed early. Moreover, late or defective materials and changes by the owner are also likely to affect the schedule.
In addition to including discrete threats and opportunities, we can include risks that represent ambiguity about the future. The existence of these ambiguities is known (their likelihood is 100 percent) but their effects are unknown. For example, we know that the productivity of labor will affect the duration of many activities, but whether the overall effect is positive (an opportunity) or negative (a threat) is unknown. We can also include some element of general uncertainty. For example, we know that natural variability surrounds each of our duration estimates, so we include an uncertainty to represent a global estimating error. Table 4 identifies some uncertainties for the house construction schedule.
Table 4: Some Uncertainties for a House Construction Schedule
| Optimistic | Most likely | Pessimistic | ||
|---|---|---|---|---|
| Productivity of labor | 100% | 95% | 100% | 110% |
| Efficacy of general contractor | 100 | 90 | 100 | 125 |
| Schedule estimating error | 100 | 95 | 105 | 115 |
Source: GAO | GAO-16-89G
With the risk driver method, the risks shown in tables 3 and 4 will appear as factors that multiply the durations of the activities they are assigned to, if they occur in the iteration. Once the risks are assigned to activities, a simulation is run. The results may be similar to those in figure 38.
Figure 38: House Construction Schedule Results from a Risk Driver Simulation
In this instance, the schedule date of February 10 is estimated to be less than 1 percent likely, based on the current plan. If the owner chose the 70th percentile, the date would be April 14, representing a 2-month time contingency. Notice that the risk driver method has caused a wider spread of uncertainty between the 5 percent and 95 percent confidence dates compared to the three-point duration method. By combining the two methods, three-point estimates may be used to represent bias and uncertainty, while risk drivers are used to represent identifiable risk events that may be mitigated.