The web contains an enormous amount of information, and Google has helped to make that information more easily accessible by providing pretty good search facilities. But not everything is written nor is everything well organized to make it easily discoverable. There are millions of people who possess useful knowledge that they would love to share, and there are billions of people who can benefit from it. We believe that many do not share that knowledge today simply because it is not easy enough to do that.
Google Knol is initially being portrayed as a Wikipedia killer and perhaps a threat to Yahoo Answers, but there is a key difference that worth noting. Wikipedia is a community effort. Google Knol will highlight authors. If John Doe is an expert on something he can share that knowledge through Google Knol.
That author distinction makes me wonder if Google Knol could really become more of a knowledge management application. Knowledge management software has been around forever in the enterprise, but never quite caught on en masse. The biggest reason: Employees like to hoard knowledge and don’t want to share much because they become less valuable.
For companies, however, collecting institutional knowledge is critical. If you’re a utility that has one third or more of your workforce retiring in the next two years, you better figure out how to store key information. Most of this information isn’t textbook material–it’s little day to day workarounds that make the business more efficient.
I’ve only come across a few companies that really made knowledge management work and the big secret is rewarding employees for sharing.
That’s why Google Knol could be interesting. Of course, not all of the content will be worthy, but Google’s approach–if it works–may be worth adopting in the enterprise somehow via an API and a filter that aggregates employee expertise.
On the more consumer side, Google could use the atomized bits of knowledge (knols) created by authors to fuel a more semantically rich Web of connections. With tags, ratings, comments and other rich metadata and Semantic Web technologies, or even just the statistical approach Google prefers, knols could provide a framework for more complex and even natural language queries.
