Monday, May 19, 2008

Interwoven Case Study on WorkSite 8.3

I was asked to speak about The Firm's Worksite 8.3 implementation. Kevin Hicks from Interwoven was able to supply the technical side of information. My main focus of presentation was on the user interface and user experience.

Everyone asks us for Google. "Why can't we just have Google search our documents?" Larry and Sergei are billionaires because they figured out the special sauce for searching and ranking webpages. What our people are asking for is a simple interface that returns documents in a meaningful way. Instead, with Interwoven we give a lot of fields to search in very database look with documents returned in a flat result list.

Before throwing Interwoven under the bus, there are four types of searches and Interwoven does two of them very well. The four types are fetch, recall, research and precedent. Interwoven excels at the fetch and recall search. These are by far the most common searches run at most firms.

It is the research and precedent that deliver the knowledge management value by allowing attorneys to find and reuse relevant content.

Until Worksite 8.3 and Express Search, they did poorly at research. Interwoven Express Search now delivers on research. Nobody does a precedent search. That is one of goals for enterprise search.

A deeper discussion of the four types of search.

With the fetch, you have exact identifying information. For instance, with a document in the document management system you have the document number, or you have a filename and path, or a URL. This is core document management activity.

With the recall search, you have some distinct information about the nature of the item. You remember a matter it was associated with, who created it, when it was created, etc. With this type of search you typically get back several or many items and you need to sort through the results to find the item you were looking for.

The research is the type of search that an enterprise search was built for. You want to find information on a topic and you may have no idea if the enterprise has any information on that topic. Information could be stored in a variety of sources/databases.

With a precedent, the information that makes the item relevant is generally not in the text of the document. For instance, if I were looking for a purchase and sale agreement for a retail shopping center in Florida that is buyer favorable. The words "Florida" "retail shopping center" and "buyer favorable" may not appear in the document and if they do they may only appear once or twice. To enable this kind of search you need to harness the document collection to another database of information.

1 comment:

  1. I enjoyed your presentation. I know I am a bit late to post, but better late than never! Thanks for sharing your implementation story with us.


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