Can we anticipate lawyer’s know-how needs? That is, can we push information to them rather than asking them to pull it.

At the Knowledge Management in the Legal Profession by Ark Group on October 22, 2019 in NYC, a session I lead will address this question. My panelists and I will not answer the question. Rather, we will lead an audience interactive discussion. And we may not reach conclusions – we view the session as part of a journey to richer KM.

I set out below some ideas and questions and an example use case. I hope readers – Ark KM attendee or not – will offer input in advance. If you have suggestions or feedback, please contact me. The panelists are

I have appended the session description at the end of this post. If you would like to attend, contact me for a discount code.

Why Anticipate Lawyers’ Know-How Needs? Why Push?

Knowledge management today mainly relies on lawyers seeking out know-how resources such as precedents, relevant work product, or colleagues with experience. This may be changing. At Ark KM 2018, two sessions discussed anticipating needs:

  • Nicky Leijtens, Board Advisor Client Experience & Innovation, NautaDutilh NV presented The Netflix Way: A Data‐Driven Approach to Engagement. Though her presentation focused more on delivering clients information that would engage them, the meta-theme was anticipating needs and interests.
  • Jeff Rovner, Managing Director of Information, O’Melveny & Myers LL presented Redesigning Law Firm Knowledge Management. Noting that adoption of KM systems remains a problem and that lawyers remain unaware of useful tools, Jeff explained a OMMnicisent, system that pushes information to them at exactly the time they likely need it.

The common element of both presentations focused on how companies like Netflix and Amazon sell more by anticipating what viewers and shoppers want. And how accurate anticipation means the recipient is ready to pay attention to and engage with the information. And they don’t have to seek it out.

Can we do something similar in law firms and law departments? And if we can, how do we make sure we don’t deliver too much, that is contribute to information overload. The nightmare scenario I want to avoid is the equivalent of too many device alarms in a hospital. Several articles have reported that nurses and doctors usually ignore alarms because so many devices sound so many and so few actually matter much.

Questions re Anticipating Lawyers’ Know-How Needs

  1. CONCEPTUAL QUESTIONS
    1. What is the precise problem to solve?
    2. Are there vendor products that solve the problem (at least in part) and, if so, what can we learn from them?
    3. Can we make sure we deliver the right amount of information? (Avoid “too many alarms.”)
    4. How does design thinking inform the answer?
      [This section courtesy of Monet Fauntleroy]
      The 5-stage model (originally proposed by the Hasso-Plattner Institute of Design at Stanford)
      1. Empathize (learn about the people for whom you are designing)
      2. Define (construct a point of view based on user needs and insights)
      3. Ideate (come up with creative solutions)
      4. Prototype (build a representation of the ideas to show to others)
      5. Test (return to your original user group and testing your ideas for feedback).
    5. Do we need to define a set of common KM and external information use cases to begin addressing the question here. (See an example potential use case below.)
      1. Is this a people, process, or tech question?
      2. Privacy or Big Brother issues?
  2. EXECUTION QUESTIONS
    1. Are there good examples of systems in the legal market that already do this?
      1. See discussion above from Ark KM 2018
      2. See also Mallesons’ PeopleFind, from my 2008 blog post. Mallesons used multiple data sources to direct incoming calls to lawyer for that client. 
    2. Do we have the data we need or can we infer it from existing systems and processes? 
      1. What data?
      2. Are those data already cleaned and normalize?
    3. What will drive solution(s): rules, data analytics, AI, other?
    4. How should we think about delivering information?
      1. Intranet, email, mobile notifications, other?
      2. If lawyers live in Word and Outlook, do we need to deliver there?
      3. Where will lawyers “live” in the future?
    5. Are there building block we can or should work on?
      1. Capture more metadata
      2. Profiles of information consumers
      3. Discrete tools

An Example / Use Case of Anticipating Lawyers’ KM Needs

Consider a litigator who needs to answer a motion. To anticipate what that lawyer needs, the system should know:

  • How much experience this lawyer has generally.
  • How much experience with this type of motion she has.
  • What the matter is about.
  • If the firm has done similar matters.

Would it then be helpful to offer:

  • Potential sample documents.
  • References to forms.
  • A prioritized list of peers who have worked on similar docs in last quarter and/or have relevant expertise
  • Court rules for that jurisdiction
  • A link that automatically accesses the docket for that case

Endnote: Session Description

Session Title: Anticipating Users’ Information + Know-How Requirements

Across KM resources and a variety of internal information sources (as well access to multiple external databases), law firm staff typically wait until lawyers or managers ask for information to fulfill a request and deliver documents, analysis, or connections to colleagues with know-how. Last year at Ark KM we heard from two speakers about using internal and external data to anticipate requests and deliver users what they need – before they may even recognize that need. What will it take to engineer a shift so that a growing portion of information and know-how (support or results) are delivered before users request them? As the legal profession continues to become more data-driven, now is the time to start figuring out the answers. This panel will lead an interactive discussion to elicit examples of systems that anticipate future needs, define requirements (user, tech, and data), and discuss potential approaches. This will be an audience interactive session—panelists will offer ideas but will not come with fully-baked answers. We will depend on audience know-how and participation to whiteboard what this future might look like.