Understanding nPlan Projections

Interpreting distributions - individual activities

Aggressive Planning

Explanation

This activity has a low (33%) likelihood of completing on time which indicates it has been planned aggressively. Additionally, if the activity is delayed the delays will likely be impactful. There is a 50% chance of 5 days or more of delay, and a 20% chance of 21 days or more of delay. The key action here will be to understand the delivery team’s confidence of meeting the planned duration and any systems of work that are in place to ensure this. If the team is not confident in delivering the work within the planned duration then the actions become focused on identifying if the duration can be extended and the impact this will have on successor tasks.

Characteristics:	Low likelihood to meet planned duration Significant delays at P50, P80
Actions:	Check delivery team confidence in meeting
Planned duration	Are there best practices in place to ensure this duration? Are the team experienced in
Delivering this type of work?	Can the activity duration be increased? If duration is increased, what is the impact on the successor activities and float erosion?

Opportunity

Explanation

This activity shows a high (73%) likelihood of finishing on time but also demonstrates an opportunity to finish early. In this case at P30 the duration is 4 days shorter than planned. The initial actions will be with the delivery team or planner to understand whether there is capacity and appetite to accelerate the planned duration.

Characteristics:	High likelihood to meet planned duration Meaningful saving at lower P-values
Actions:	Discuss with planner/delivery team whether resources are available to accelerate this activity Discuss with the planner/delivery team whether there is a schedule benefit to be realised if the activity finishes early?

Bimodal/Trimodal

Explanation

Most activity duration distributions consist of a peak around the planned duration with a longer right tail. Multimodal distributions consist of multiple distinct peaks that represent likely ‘good day’ and ‘bad day’ scenarios. In this example there is a 31% likelihood of completing the activity on time, but if the activity is delayed it is likely that the actual duration will end up being in the region of 68 days (~3.5x originally planned). In order to mitigate the risk to this activity a focus on the risks that could cause a ‘bad day’ scenario should be taken.

Characteristics:	Multiple peaks in the distribution representing distinct good / bad day scenarios The planned duration will likely be the taller first peak, with ‘bad day scenarios’ further to the right of the distribution
Actions:	Discuss with project team the potential for significant delays Workshop mitigations and identify root causes of bad day scenarios

Low probability, high impact risks

Explanation

This activity shows a medium likelihood of meeting its planned duration (43%) but shows a long fat tailed distribution. This means that if the activity completion is delayed, it is likely to be significantly delayed - here the P90 duration is 4.5 times the planned duration. The first action would be to identify any low probability high impact risks in the risk register, followed by workshopping risks and mitigation plans with the project team. If the risk cannot be terminated then investigating the available float and capacity to absorb delays is key.

Characteristics:	The P90 delay is > 3 x Planned duration Long fat tailed distribution
Actions:	Check if there are any low probability high impact risks in the risk register? Workshop mitigations to potential low probability high impact risks with team Contingencies if activity is significantly delayed & asses the knock-on impact (driving paths/activity neighbourhood)

Interpreting distributions - Target Milestones and End Dates

Explanation

The probability density on the left y-axis corresponds with the blue shaded area and can be interpreted as the frequency in which we see certain dates achieved. The dates are shown on the X-axis. The cumulative distribution to the right shows the probability of the corresponding date not being exceeded. In the middle of the S-curve we can see the impact of blocked out days in the calendar over the holiday period. The circle to the right at the end of the distribution shows that there is a very low probability of very high delays.

Forecast Comparison - Pre and Post Mitigation

Explanation

Here we can see the distributions of two forecasts, the forecast to the right is the unmitigated scenario where all of the forecast uncertainty in the project is considered. The forecast to the left shows the potential to improve the forecast outcome through mitigation of the top 10% of threats identified by nPlan’s algorithms. Note that in the mitigated scenario the forecast end date at P50 is within 17 days of the planned date shown to the left, which is close to an 8 month improvement over the do nothing scenario. For a more risk adverse approach you might consider the P80 values.

Interpreting individual insights

When reviewing individual insights they can be ranked by importance by checking the potential savings. The higher the potential saving the more attention it should receive. Following this we can then interpret the distribution, the one below has a P51 likelihood of meeting its planned duration and contains a thicker than normal tail indicating a greater chance of high impact delays. The possible delay causes to the right can then be reviewed. If these delay causes are relevant we then add an action to them in the section below. To gather further context we can navigate the activity neighbourhood to understand which activities will be impacted by the projected delay. Linked insights also give context and as we can see below they show similar procurement activities.

Interpreting grouped insights

Explanation

When there are large numbers of insights or similar activities repeatedly show as being risky we can pull these together as a grouped insight. These are valuable as it allows you to assign actions to multiple activities for easy wins and calculate what the potential savings are at each p-value. The criticality of each individual activity and it the likelihood to meet its planned duration is also provided to give context to the sub elements of each group. The potential savings achieved at the target milestone for mitigating the entire group is shown at the top left and should be considered in addition to the criticality of the activities. The higher the criticality the higher the likelihood of the group driving delays.