Critical Chain Challenges: Fever Chart

In Sydney (Australia), there is currently a perfect case demonstrating why Fever Chat could be misleading.

The Fever Chart is a primary method in Critical Chain delivery approach. It is used to control buffer consumption.

Fever Chart is based on the crucial assumption that project contingency needs to be equally distributed across the project duration. This assumption is relevant for many projects but not for all. Some projects, by nature, have more risks at the end (or start) of delivery, sometimes just before the end.

In this case, if the project spends the allowed contingency but significant risks are still ahead, the Fever Chart may show that the project is not in the Red Zone when, practically, acceleration actions are needed.

Sydney’s new A$21.B Metro line was not opened on the announced day, August 4. The opening has been delayed to wait for the national rail safety regulator’s sign-off. A new date has not been announced yet, which demonstrates the severity of the issue. The final Safety test was the last piece of the delivery puzzle.

Leaving aside the reasons why the test failed and which delivery methods were applied in this mega project, I wanted to demonstrate that a project may have a risk that:

• cannot be avoided;
• is just at the end of delivery;
• If materialised, it has a significant impact.

Risks and Uncertainties are not distributed equally along the project journey.
So, the distribution of project contingency should not be linear. Accurately calculating planned contingency consumption is a complex mathematical problem, so an average consumption rate is usually used as a proxy.

The ‘Fever Chart’ method addresses this challenge by creating a wide Red/Amber/Green zone, acknowledging that just an average line could be misleading.

It works in some cases but not when projects have a significant disbalance of risk over time. In such situations, the Fever Chart creates an illusion that the project has a sufficient outstanding contingency. It happens when the contingency has already been spent, but significant risks remain.

What is an alternative to the Fever Chart that can correctly identify such a problem?

The Success Probability Trend Method shows the current chance of meeting the project targets and how probability has changed over time. If the trend is negative, the project is losing contingency too quickly, and corrective actions are needed. Compared to the Fever Chart, it is sensitive to changes in risk profile. Also Probability Trend shows the probability of meeting any target, not just time.

Fever Chart and Probability Trends methods perfectly complement each other!