This is a bit of an experiment. I’m at the Ark KM conference in Chicago now and am taking notes and will post in real time with little editing. The current session (10am Central) is The Expanding Surface of KM by Brent Kidwell of Jenner & Block. 

Kidwell takes a very broad view of KM. His team will not work on infrastructure but he suggests they will work on anything that has a practice-facing element. Kidwell offers a five-part definition of KM:
1. Mine existing data
2. Collect new data
3. Manage or manipulate the data
4. Deliver back the results
5. Refresh and update

Examples of recent projects at Jenner & Block. Some are traditional KM, some are not – that’s part of the point Kidwell is making that KM is not that well-defined:

  • Marketing: This example is close to core definition of KM. Kidwell’s team helps collect the core information that marketing needs. For marketing to be able to find and mine data (e.g., find a blurb from a one-year old RFP) is critical. The firm has an internally-built tool called KMDocs; it allows easily foldering documents into categories. All contents is full-text searchable and browsable via a taxonomy. By putting all content into this system, marketing is able to find and re-use its content. Search results show all locations of where a document resides, which helps provide context to understand what a search hit is really about. So this is an example of “real KM” that mines existing data and manages them with a taxonomy. Other marketing support includes CRM and full-text search support.
  • Docketing: The firm had a long-standing docketing system. Kidwell’s team decided to mine the data. First it had to be “groomed,” then it was made searchable. Now, users can, for example, find out colleagues who have argued cases in front of the same judge. Searches can be narrowed by judge, jurisdiction, type of matter. This serves as a form of experience location. This system also has marketing functions because it allows answering prospects about types of cases and jurisdictions worked in. Kidwell calls this traditional KM because it mines and then delivers existing data.
  • Accounting: This example moves a bit away from traditional KM. Practice group leaders needed specific information to help them assign lawyers to matters. They need real-time information on who is busy, stratified by number of years of experience. Kidwell’s team developed a list of business requirements by talking to practice group leaders. No commercial product met the requirements, so the firm created its own tool. The tool also allows comparing each lawyer’s budget for hours against new requirements so that work goes to lawyers who need work.
  • Legal Recruiting: The Recruiting department talked to Kidwell – they wanted to deliver recruiting information to law students digitally, on USB drives, rather than on paper. Why did recruiters go to KM? First, the recruiters knew KM would say yes. Second, the KM team has developers. And third, recruiting has data that they need managed and re-used. The KM team developed a “web page on a stick.” It includes detailed information on the firm. The information is customized for each law school that the firm visits (for example, bios of lawyers visiting that school and alum from that school at the firm). Kidwell puts this in the KM model: mine and re-use existing data. Perhaps a couple of years ago, we would not call this KM, but now most of us would call this KM.
  • Summer Program Support: It’s hard to manage work assignments and evaluations for summer associates. The managers of the summer program wanted an online work flow management system. The development team went through a requirements definition, created wireboards to sketch out functionality, then built a system. The work flow includes : 1. Submit Request. 2. Assignment approved or returned. 3. Summer associate can review available assignments and request one. 4. Assignment approved (or not). 5. Evaluation process kicked off. The tool lets summer associates to put their work product into the system so that the actual work is sent to the right lawyers for evaluation and review. Kidwell has a hard time squeezing this into a traditional KM model.
  • Professional Development: PD digitally tapes all inhouse education programs. The KM team posts all recording on the firm’s portal, along with accompanying materials.
  • Litigation Support: Kidwell, in addition to KM, also manages the firm’s lit supp (and EDD) department. The volume of potentially responsive data in discovery requests is enormous. Kidwell says he cannot distinguish EED challenges from KM. Both involve large volumes of data from mulitple sources and the firm has to do something with the data to make it usable to lawyers. For EED, the firm has to collect, filter, de-duplicate and analyze the data. Lawyers then need to review it for responsiveness and privilege – is there knowledge in the documents useful to the case. So this is similar to creating a precedent library for a practice group. The shared challenges are: 1. Expansive collection efforts. 2. Large data volumes. 3. Processing to usable formats. 4. Mining for knowledge. 5. Providing a robust review environment.

My one immediate editorial comment is that this supports a topic I presented at a prior Ark conference – Is KM Morphing into Practice Support. Kidwell presented a range of what I would consider more traditional practice support than traditional KM.

Originally posted at 10:55am Central