“Information seeking has [thus] generally been done in a rather unconscious or automatic way.” — Marcia Bates
In his seminal paper “The Nature of the Firm”, Nobel laureate and economist Ronald Coase posits that firms will grow in size if they can lower procurement costs and internalize as much of their production as possible. To understand this in the context of the legal industry, law firms are in the business of procuring knowledge workers (lawyers) and other explicit forms of knowledge (databases, secondary sources etc.) and repackaging, value adding to, and selling this knowledge in the form of services and other work products.¹
Applying Coase’s theory to the practice of law, firms which can accrue large cost savings relating to knowledge aggregation will develop a competitive advantage. Hence, developing an ecosystem of tools and procedures that can help redistribute or reuse parts of existing knowledge becomes an essential driver of law firms’ profitability.
Transforming knowledge into reusable intellectual assets will take the following steps:
Capturing or documenting knowledge,Packaging knowledge for reuse,Providing access to knowledge, andReusing knowledge.
This article explores the principles that firms should keep in mind when putting together a solution to tailor to the needs at different stages.
The first steps are always the hardest
Principle 1: Knowledge should be stored consistently, in a way intuitive to users
While certain types of knowledge are still bound in physical volumes (such as older law reports and textbooks), the bulk of law firms’ knowledge base is now in a digital form. Storing knowledge work in a central electronic repository is a necessary — though insufficient — step towards knowledge management. In fact, a rudimentary form of digitization may create unintended and indirect costs for firms.
When we move from a paper-based storage system to an electronic system, it is not only a change in the medium of storage; the model of storage also changes. In a paper-based storage system, libraries are organized by subjects and topics. Likewise, law firms precedents are curated, printed and filed in the same way. However, when it comes to electronic systems, such a filling model breaks down. The nested folder structure is too hierarchical and rigid for multidimensional files. Consequently, we organize our files by keyword labels and access them by keyword search functions.
Unfortunately, this manner of organisation is counter intuitive to the human mind. Our brains still rely on subjects and topics to maintain a mental map of where our information is stored. For example, a corporate lawyer might recall having been involved in a shareholder agreement [subject: document type]done for a client in the technology industry [subject: sector] which contains a list of pre-emptive rights [subject: legal topic]. While trying to find this precedent in the firm’s electronic repository, s/he will either search for the keyword ‘pre-emptive rights’ (which will likely surface too many results), or will have to navigate through the nested folders (with the matter ID or client name as the most frequently used identifier for a top-level folder). One wrong turn down this hierarchical structure may deem the entire effort a wild goose chase.
Further, incorrectly naming a file or saving it in the wrong place can mean spending hours repeating work which has already been done. An International Data Corporation 2012 study found that a knowledge worker spends, on average, 4.5 hours per week² just searching for documents. This means that on average, a law firm would bill $80,000 less per lawyer per year because s/he was spending valuable time on unbillable knowledge aggregation³.
An efficient electronic repository should not only capture data, but needs to be able to package data into knowledge that is usable and easily accessible.
Strong packaging, clear messaging
Principle 2: Knowledge Bank = Electronic Repository + Classification Schemes
Packaging data into knowledge is the process of culling, cleaning , structuring, formatting, and/or indexing documents against a classification scheme.⁴ A well-developed classification scheme is especially pertinent to the legal industry, given the complex relationships between legal principles, concepts, cases, institutions, legislation, regulations, and the different types of documents produced by a lawyer.
In our experience, this is often overlooked by law firms in their search for an electronic repository suitable for knowledge management (KM). Few firms have actually developed their own classification schemes, even if they have identified KM as one of the key strategic drivers for their business.
We at INTELLLEX envision KM to be one of the drivers for the future law practice. Through consultation with academics and practitioners, we have developed our own classification schemes for different types of legal documents. From our work, we found that there are at least 60 ways which a legally-relevant document/concept could be linked to another, that there are at least 100 classes (not types) of legally-relevant documents/concepts which a law firm would have, and that on average, there are 6 different kinds of links which could be drawn between legally-relevant documents/concepts. We translate this understanding to training our A.I. classification algorithms, which are deployed on our platform to intelligently profile documents along their important legal dimensions.
Building an electronic legal knowledge bank requires multiple approaches beyond just document capture. Having classification schemes appropriate for the legal industry complete with superior index and search abilities are the essential next steps.
Ask and it shall be given; search and you will find
Principle 3: Search must be tailored to the knowledge re-user
It has been noted that one characteristic separating experts from novices is that experts know what questions to ask. A novice will require more guidance in forming their search queries while experts look for more context around documented knowledge. Experts also like to have updates ‘pushed’ to them so they can be on top of their game. We differentiate experts and novices not by their seniority in the practice but by how familiar they are with a subject matter or the knowledge base: a senior partner could be a novice when looking for information in an entirely new area whereas a junior associate who has worked tirelessly on just one type of transaction could be considered an expert.
So depending on where users are on this spectrum of knowledge-distance, the search tools available will determine the degree of success of knowledge reuse. To that end, we invest tremendous resources into improving our platform’s search mechanism. Our search engine is designed to allow a combination of full-text keyword search, faceted search, relationship search and full sentence query. Machine Learning capabilities are also built into the platform for the purpose of allowing knowledge experts to discover inferred relationships between different sources knowledge. Our goal is to deliver a personalized answer engine (and not simply a search engine) for our users.
In conclusion, facilitating knowledge reuse can contribute directly to law firms’ profitability. When considering KM technology solutions, law firms need to consider the efficacy of search, the flexibility of file storage architecture, and the appropriateness of the classification schemes when selecting their platform of choice.
We all know that every law firm sits on an oil field of knowledge. The challenge is to use the best extraction tools to turn this knowledge into your intellectual capital.
1: “Search, Knowledge Management, and the Practice of Law”, The Digital Business Law Group, 2009
2: “Information Worker Survey”, Information Data Corporation, 2012
3: Calculated based on average hourly billing rate of $350
4: “Towards A Theory of Knowledge Reuse: Types of Knowledge Reuse Situations and Factors in Reuse Success”, M. Lynne Markus, 2001
Written by Ellery Sutanto
Ellery heads up Business Development at INTELLLEX. Knowledge is a key asset to organizations, thus we want to build technological tools to help better manage it.