Here’s a really interesting post on newscientist.com.

The article itself discusses the potential of using email data to predict a business crisis within an Enterprise. The example used is Enron. After the demise of the company in 2001, federal agents gained access to the email records for 150 senior staff during the last 18 months. Ben Collingsworth and Ronaldo Menezes at the Florida Institute of Technology in Melbourne identified key events in Enron’s demise, such as the August 2001 resignation of CEO Jeffrey Skilling. They then examined the number of emails sent, and the groups that exchanged the messages, in the period around these events.

The results were profound and it really is worth checking out the post.

The really interesting thing is that the insight gained by researchers looking at the email data was achieved without even using the content within the emails. It was developed simply by looking at the networks of connections between different senders.

The exciting thing for us (and our customers) here at KnowledgeMill is that our KMCS product is designed from the ground up to provide business insight from day one. The researchers at MIT, Carnegie Mellon, and the Florida Institute of Technology had to take an existing set of email data, massage it into various database models, and carry out a mining exercise that was probably fairly arduous. The practical advice that really comes out of this research is that large enterprises must focus on putting their email data into the right place – this has to be a scaleable, searchable, and intelligent email repository. This means that business intelligence can be extracted in real time the moment the first set of emails are added.

In the Enron example, the email data was only a small subset of the real data set (18 months, 150 staff) but has been shown to have huge business value. Imagine the power of having all of your companies email within a single repository, or perhaps even better, all of your most valuable email data, but also being able to search and interpret the content. Predicting a crisis is just one possibility as shown in this article, but there are many others – reusing knowledge, tracking down experts, locating the most influencial people, tracking down key contacts at customers, identifying the most profitable deals when comparing effort, to name but a few. Avoiding marketing nonsense, this really does provide key differentiators for businesses who adopt best practice.

We really don’t like using this particular blog for any kind of sales purpose (it’s more for industry-related thoughts) – but somehow we couldn’t resist the alignment with our core KMCS platform. Business Intelligence has always been a forefront element of the KMCS design and is baked in at the lowest level (within the database repository). We hope you’ll forgive us for mentioning it Below we’ve added an example screenshot from the KMCS Business Intelligence functionality. We have the ability to show many different dimensions of the data through the UI to visualise communication patterns and business influence at the individual, team, department, context, regional, and enterprise level both inside and outside an organisation. The screenshot shows the influence that an individual (Joe Bloggs) has with different customer organisations. The closer the organisation, the stronger the influence (based on the amount of email correspondence and number of related documents). The data is entirely fictional and not related to any of KnowledgeMill’s real customers.