Give Probability a Chance: ES Stats in Action
Statistical variance is not just an academic exercise. You can apply high and low bounds to actually manage schedule performance.
Here's how.
Start with the nominal Estimate at Complete for time (ES/SPIt). Find the high and low bounds of the estimate.
(The math behind the calculations is daunting. Save time and headache by using an app. Both freeware and commercial software are available to do the calculations. For info on ProjectFlightDeck’s solution, click here.)
Now, look for trends. What's a trend? It's three or more consecutive measurements headed in the same direction.
What does a trend tell you?
For Walt Lipke, the direction of the trend tells you the likely duration, given historical performance on the project.*
Here’s a trend we like to see: high and low bounds converge symmetrically on the nominal. The nominal, in turn has a flat trajectory. The interpretation: estimates will be fairly close to the actual outcome. No further action is required.
By contrast, here's a pattern we don't like to see: high and low bounds suddenly diverge. That means performance is erratic. The estimates are not reliable indicators of final duration. As soon as the trend emerges, take action to recover the project.
If there is a synchronous downward trend, that means performance is improving over time. The low bound will be slightly lower than the actual outcome. That's often viewed positively, but it has a downside. It might indicate padding in the schedule. Maybe, it's time for action.
Finally, see if there is a coordinated upward trend in the estimates. That means performance is worsening over time. The high bound will likely end up slightly higher than the actual outcome. Again, maybe it's time for action.
When performance is stable, trend analysis signals the likely outcome. But when does the signal call for action? Too early, you lose credibility. Too late, you lose recoverability.
For an answer, you need two things.*
First, the performance baseline. That's the Planned Duration. And, second, performance thresholds—limits of acceptable performance.
One form of threshold is a fixed percentage of the Planned Duration. It's usually set by governance documents, project or program plans, or contracts. In our practice, we have used ±10% as the fixed rate.
Another form of threshold is a variable percentage. In our practice, it's derived from uncertainty allowance.
Uncertainty leads to risk, and the risk needs to be mitigated. Some uncertainty arises from a lack of knowledge. It creates reducible risk. You buy down the risk with scheduled tasks that fill in knowledge gaps. Contingency covers the buy down.
Uncertainty also arises from the randomness that occurs naturally on projects. You can't buy down that kind of risk. It's irreducible. You can only buffer it through Reserve.
Add or subtract the uncertainty allowance to or from the Planned Duration. That sets performance thresholds.
Next, assess the variance of estimates from the baseline (or the total commitment). If the variance trends towards a threshold, prepare to take action. If the variance breaches a threshold, it's time to act.
Finally, use high and low limits to assess the reliability of the nominal estimate. A wide range means you should be cautious about depending on the nominal. A small range, especially later in a project, warrants more confidence in the nominal.
Watch for our video, Marie Gives Probability a Chance. It drops next week.
*References:
Videos: Making (Common) Sense of ES Statistical Analysis Building Blocks Build the Bounds Apply the Bounds
Blog: Statistical Analysis Revisited (2021) Statistical Analysis Deep Dives Background How it works Steering the Project Example Pro/Con |