Track and analyze the “surface area” of your lawyers’ contacts with individual clients

Legal managers look for available but overlooked data that can sharpen their business judgment.   One data set that might be new is “surface area”: how many individual clients interact with lawyers during a period of time, either within the organization for law departments or at organizational clients for law firms.  Surface area doesn’t just track senior clients, it tracks all clients.  The more clients who have dealings with a lawyer each quarter, the larger the contact surface area and presumably the better the law department or law firm both knows and responds to clients.  Widespread connections – a large surface area for the law department or law firm – assures that clients are finding the lawyers valuable.  It also keeps the lawyers more in touch with business realities, rather than lost in the myopia of purely legal developments.

True, the lawyers might need to tally a few individual clients on their own, but tools exist to capture much of the data.  What comes to mind is software that extracts names of clients in emails of the lawyers.  For a partner in a firm, email traffic with [name]@[client].com would be fairly easy to keep pull out and keep track of; for an associate general counsel in a company, the same type of filter would be even easier to spot and count internal email traffic.  Another source could be invitation lists to meetings.

Analyses of data on client contacts would focus on changes over time and distribution, and could also allow fuel social network insights.   For the network graphs, it would be useful to categorize clients by level or position.

Law departments and law firms could create data profiles for key clients

To understand a client better, legal managers could generate what we might call “data profiles.”  The initiative can benefit law departments, but let’s use a law firm example.  The profile would assemble several kinds of figures for a client for each of the past three years.  That trend data could include what kinds of work the client generated based on types of matters (and maybe sub-types) including counts, hours and fees.  It could show the number of partners and associates who recorded time on those matters.  It could tally who at the client called to give assignments and their level.  Perhaps there could be data on the email traffic or the conference calls associated with the client.  The profile could extend to fee write offs and discounts and to margins.

A finance group or practice group that researches, ponders, and assembles such data will be able to create client profiles, akin to dashboards, and probe trends over time.  All kinds of analyses would be invited once the data set has been pulled together.

A “client profile” would be a guideline for the kinds of services the client needs, who its key players are, the direction its business initiatives are going, preferences for firm lawyers, and anything else that would enhance client service and client satisfaction.  It could lead to better cross-selling, better use of associates and paralegals, proposals for fixed fee billing, increased client satisfaction, and more.  With data profiles, the firm could segment client groups into categories, such as “high maintenance” or “risk embracing” or “transactional.”  Once you collect the data, your firm will be able to mine it!

Data analytics (NLP) to boost knowledge management efforts

Knowledge management for law firms and law departments has been pursued for decades, but the overall success given the investment seems debatable.  It has been proven difficult to collect the unstructured text of lawyers in a system that others find useful enough to justify the cost.

Perhaps machine learning and natural language processing will replace the older paradigm of contributions by lawyers of their work product, often with key words extracted or sometimes with full-text searching, by a paradigm of software sifting through everything that is saved on a firm or law department’s servers, enriched by  semantic networks or taxonomies created by software.  Natural language processing (NLP) can create the infrastructure of knowledge without lawyers taking any of their time.  Stated differently in the words of the lead articles of a recent publication, data analytics is potentially a “powerful force for increasing knowledge management by amplifying existing data.”  If you can parse and organize and enrich material collected in the ordinary course of legal business, you can boost KM efforts enormously.

These dots connected for me as I read KMWorld, Oct. 2016, at S18 of its white paper on cognitive computing best practices.