Web 2.0 has created massive amounts of content, much of it user generated and unstructured, making information overload grow exponentially. Now as Enterprise 2.0 infiltrates organizations, the potential for content overload is reaching into new spaces. At the same time, many researchers and analysts are saying that there are great opportunities to take advantage of this growth in information by finding relevant meaning in the mass of content both on the Web and within the enterprise.
For example, research by MIT’s Erik Brynjolfsson and colleagues support the business value of “data-driven decision making” for management as organizations adopting this model achieved higher productivity rates. Many are now looking the voice of customer on the Web. The same need lies within the enterprise - see Forrester’s Leslie Owens on the importance of listening to the voice of the employee.
However, we are at risk to miss many meaningful conversations with the current options to deriving meaning from the massive new content. Old school approaches can conceal much of the potential value, hide anomalies, and mask innovation.
This danger is that many of the traditional approaches to finding useful content and making sense of this information explosion require you to predetermine too much of your investigation through taxonomies and/or focused search queries. These approaches the unexpected unexplored and the meaningful anomalies undiscovered. They will not provide the full range of content that management needs to take advantage of the explosion of unstructured content both within the enterprise and on the Web and find all that is relevant to make informed decisions.
We recently ran a six part series on the Darwin Awareness Engine™ Blog exploring this issue in more depth. Here are links to the series. Let me know what you think.
Enabling Content Discovery: Part 1 – Introduction
Enabling Content Discovery: Part 2 - Web Search
Enabling Content Discovery: Part 3 - Semantic Technology
Enabling Content Discovery: Part 4 - Semantic Tech vs. Human Cognition
Enabling Content Discovery: Part 5 – The Awareness Engine™
Enabling Content Discovery: Part 6 – Practical Example
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