Cassandra Syndrome framework

The Cassandra syndrome, also known as the Cassandra complex, presents itself when a person’s warning goes unnoticed and is disregarded. This is a very familiar situation for consulting roles, and especially true for competitive intelligence professionals who try hard to get their insights acted on.

The term is derived from Greek mythology. Cassandra was a beautiful woman whose beauty seduced Apollo into granting her the gift of prophecy. However, when Cassandra refused Apollo’s romantic advances, he placed a curse on her. The curse was that nobody would believe her prophecies and Cassandra was condemned to a life of knowing future dangers, yet being unable to do much about them.

The Cassandra syndrome is something I learned about when reading the book Warnings, by Richard Clarke and R.P. Eddy. As the book explains, it is evident that real-life Cassandras exist, too. These are people with foresight who able to see the trend of where things are headed. More so, competitive intelligence professionals know very well the feeling of recommending executives and decision making stakeholders, while action from our insights is not implemented.

A Cassandra is not someone who simply is not heard. It has two important requirements:

  1. They are not heard and the advice is not followed.

  2. They can project their minds into the future, based on substantiated data and analysis.

The second one is very often absent, and we look for excuses of why are recommendations not heard. It might be obvious, but our recommendations need to be supported.

Let me list, two of the most well know examples of catastrophe that were predicted and substantiated with proper proof, yet no prevention was done in order to avoid greater damage.

Hurricane Katrina and the flood of New Orleans

Bernie Madoff’s Ponzi scheme (2002-2008)

Cassandra Coefficient

The Cassandra coefficient, is a technique, not really a coefficient, for identifying predicted future disasters that are being given insufficient attention today. It was Invented by Richard Clarke, and R.P. Eddy in their book, to describe the patterns from the different personas involved in the Cassandra situation. Once you identify the patterns for each persona, you can understand their motivation, situation, and take action to avoid the rejection.

Below is a table with the 4 personas in the process, and a list of those patters.

I won’t define them all here, but here’s a few example:

The Warning | Erroneous consensus: When disaster is heading our way, not all experts agree at the same time. If the issue at risk defies a long-standing consensus because of new evidence, it should be further examined despite being a minority view. Therefore our action should be to take time, seek agreement between experts, before moving forward.

The Decision Maker | Agenda inertia: Many organizations are fanatically devoted to an agenda, and yearly initiatives and objectives. They want to stick with the plan, no matter what. Our action should look to comply with the existing processes and procedures that stick or are included in the original agenda. Small incremental deviations from such agenda are preferred.

The Cassandra | Data Driven: Cassandra’s warnings are typically not generated on the basis of intuition. They are driven to conclusions by empirical evidence. Many competitive intelligence professionals are obsessed with the data that supports the conclusion and they clearly see it. However, don’t forget that the evidence is never in question, it is the interpretation of the data. Focusing on how to interpret the data and communicate the recommendation, can carry a heavier weight for the decision maker. Leverage story telling of that interpretation.

Important note: the warning is not the recommendation.

How to avoid becoming a Cassandra

  1. Scan for problems. Reliably listening for and identifying warnings is a dedicated function, and requires an institutional solution. This means that a CI team should have, as part of its charter and core responsibilities,  scanning and looking for early warning to, not only detect impact as early as possible, but also have options ready.

  2. Full Self Awareness. Leverage the Cassandra Coefficient, to understand the threats of falling into what can position you wrong, or have critics attack more easily, or the decision maker misinterpret the data. Separate the signal from the noise with data from all angles: The recommendation, the warning, the decision maker, the critics, and yourself.

  3. Respond appropriately. There are 4 types of possible responses to these catastrophes and VUCA events, with different levels of effort required: Surveillance, hedging, mitigating, and preventing. These can also be interpreted as a Maturity Model for Cassandra avoidance.

  4. Persuade. Focus on successfully recommending and implementing the response strategy, one that might be controversial, expensive, disruptive, or perhaps all three.

Happy convincing others!

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