Scientists examining the email recovered from Enron suggest that we can can predict corporate meltdowns by looking at communication patterns within the organization. Others suggest counting the number of emails that read, “Oh sh-t!”

What the scientists found most interesting was that communications changed dramatically a month before Enron’s collapse. Their goal is to help predict when a company is in crisis before a major meltdown.

The emails examined include those of 150 senior staff members of Enron spanning an 18-month period. The logs include over 517,000 emails to Enron’s 15,000 employees, giving rare insight into communications at the troubled company.

In the months leading up to the Enron scandal, communications within the company became segmented into cliques. These cliques began communicating intensely with each other and stopped sharing information with the larger population.

The size of these segmented groups grew from 100 to 800 people on average before the crisis. This means that each of the 800 or so people communicated directly with each other during that month period.

The scientists attribute these patterns to human nature. Their theory is that in times of high stress people are likely to interact closely with the people they’re most comfortable with and otherwise stop sharing information.

Menezes and Collingsworth hope to apply their research to predicting distress within other companies. That way they hope to avoid other such corporate catastrophes.

The only problem with this theory is the highly confidential and proprietary nature of a company’s email communications. Most companies would be highly unlikely to open their email servers up for scientific research, especially the communications between top executives.

Besides, if you have access to the emails themselves, they are likely to provide dozens of other cues. Messages with such heartwarming titles as, “Shred everything,” or, “I’m not going to jail for this,” could turn out to be better predictions in this case than charting the social graph.

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Entry was posted on Tuesday, June 23rd, 2009 at 11:02 am under Scams, Social Media, Technology.

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