Deriving competitive advantage through knowledge management, information governance & data analytics

Whitepaper

Practical use cases to help define a roadmap for developing a robust Knowledge Management (KM) and Information Governance (IG) program in your law firm.

August 26, 201612 mins
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A well-designed knowledge management (KM) strategy, built on demonstrated information governance (IG) principles, allows law firms to make data-driven decisions and better optimize resources. This report offers practical advice to help promote knowledge management, information governance (IG) and data analytics to the executive management team/board of directors at your law firm.

Executive Summary

This paper is written for strategic leaders including chief operating officers, chief information officers, chief information governance officers, chief marketing officers and anyone else looking to define a roadmap for developing a robust Knowledge Management (KM) and Information Governance (IG) program over the next three to five years. It explores practical use cases for leveraging data analytics and cites relevant case studies to help promote KM, IG and data analytics to the executive management team/ board of directors within a law firm.

Effective knowledge management, the sharing of organizational knowledge, is dependent on sound information governance practices. Data analytics allows a firm to understand its intellectual assets and find the hidden gems that may be buried deep within the organization’s knowledge collections. The goal is to ensure that content is searchable and available, yet properly managed.

A well-designed knowledge management strategy built on demonstrated information governance principles provides a foundation for intelligent decision making and the optimization of firm resources. Information governance initiatives reap the benefits of the collaborative and integrated aspects of data analytics and knowledge management by engaging participation and adoption of everyone throughout the firm.

Introduction

Lady Justice is the iconic symbol of law and legal systems throughout the world. Her image is displayed at almost every courthouse on all seven continents. Her scales of justice are most commonly known to represent fairness in evaluating the claims of each side. Her sword represents enforcement measures and her readiness to gain respect for the decisions that she makes. The blindfold represents objectivity and her impartial decisions.1

Each of Lady Justice’s classic symbols can be extended further and directly applied to the principles of IG and KM within a law firm. Any administrator working in the legal industry inevitably encounters situations where he or she has to “balance” the needs of the legal practitioner to preserve prior work product for future re-use against client expectations to properly secure, protect and manage their information. The administrator is expected to make informed and objective decisions surrounding access controls, data retention and disposition. Policies, procedures and technology including data analytics are used to enforce the decisions that are made. This paper provides a framework to help firms achieve such a balance within their own organization.

There are tremendous benefits to be reaped by taking a strategic approach to leveraging information assets by balancing information governance principles with knowledge management fundamentals. Building upon that, knowledge management and data analytics are enablers for broader initiatives in correlating disparate data.

1 The Lady Justice Story, Fountain at the Bexar County Courthouse, San Antonio, Texas, Gilbert E. Barrera, Sculptor/Author

Information governance allows firms to understand what data they have and where it resides. Analytics provides the ability to glean insights into the value and meaning of information that can aid in making key business decisions, building efficient processes and implementing fluent workflows.

In the article “Knowledge Management is Dependent on Effective Information Governance,” Bill Tolson states, “The creation and dissemination of knowledge within an organization is impossible without the ability to create, store and share useful information while disposing of useless information.”2 A strategy for using big data and analytics can help us finally break the historic tug-of-war between the “save-everything” culture and those promoting defensible disposition and compliance within a law firm.

Effective IG places three characteristics on information assets: value, risk and cost. When choosing a technology, it is important to balance the priority of each characteristic with the intended goals and outcomes that a firm wants to achieve. Throughout this paper, reference is made to various specific technologies merely as examples and not as an endorsement for any particular product. The intent is to provide awareness of the type of technology available to perform targeted research, conduct independent analysis and select the product best suited for a firm’s business needs.

Like any other initiative that requires adoption, participation and change across the organization, the way in which new IG concepts are introduced can be the differentiator between success and failure. Proper planning and preparation must take place before any action is taken. Starting small and identifying areas in need of change helps demonstrate tangible, measurable results that create a clear illustration of the bigger picture. Regardless of firm size, starting with small initiatives is a sound rationale that not only promotes success for the initiative itself, but aids in building a springboard to launch larger initiatives.

2 Knowledge Management is Dependent on Effective Information Governance, September 24, 2012, Bill Tolson.

How We Got Here: A Brief Recap

The legal profession is in the midst of a paradigm shift. It began in 2006 when the United States Federal Rules of Civil Procedure (FRCP) changed to include electronic records in discovery and continued through the Great Recession of 2008 when an unprecedented number of law firm employees lost their jobs. Law school enrollment has been declining since 2010 and many predict that the number of lawyers hired by law firms will never fully recover to pre-recession levels. Within corporate legal departments, employment has grown, but not enough to compensate for the job losses in the law firm sector. Meanwhile, corporate legal departments have been focused on cutting costs associated with outside counsel and other legal services as never before.

Another more pervasive driver of change has been the adoption of technology. The so-called information age has had a profound effect on both the work that lawyers do and the way that they do it. Information and knowledge are both the drivers and the object of the legal enterprise. The adoption of technology-enabled business processes has led to a vast increase in the amount of information and data that people consume, along with an acceleration of the business processes that technology now supports. We are in the age of Big Data, which is characterized by ever increasing volumes of data in a larger variety and an acceleration in the velocity at which data is created, shared and used.

The legal profession, along with the service and software providers that support it, has had to respond to these changes. Some level of technical expertise and understanding is now a nonnegotiable area of proficiency for most lawyers. In fact, in 2012 the American Bar Association changed its definition of competency in Model Rule 1.1 Comment [8] Maintaining Competence. It now states, to maintain the requisite knowledge and skills, a lawyer should keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology, engage in continuing study and education and comply with all continuing legal education requirements to which the lawyer is subject.3 Most states have adopted some form of this Model Rule change.

The daily business of corporations and governments generates vast amounts of data which must be understood, made secure and controlled. The practice of law itself is now dependent on electronic sources of knowledge and expertise, along with software that helps practitioners organize, protect and make decisions about their work. The legal domain has long been the focus of automated decision making: artificial intelligence (AI) and law has been an area of academic focus for over 25 years. The new generation of AI, so-called smart machines such as IBM’s Watson, are being trained on the automation of legal decision making and expertise. At a practical level, the sheer volume of information that must be considered and analyzed in even moderately complex legal proceedings requires some level of machine analysis, if only to try and focus the human legal experts on the ‘right’ documents when engaged in the finding of facts.

In order to cope with these changes effectively, law firms, as well as corporate and government legal departments, must re-focus on how data, information and knowledge are created, captured, organized, accessed, used, shared, made secure and stored. It is time to re-visit the two foundational legal information disciplines of IG and KM in order to move away from the traditional document-based practices which rely on a great deal of manual intervention and into the era of big data, smart machines and cognitive analytics.

3 Model Rules of Professional Conduct

Defining Information Governance And Knowledge Management

In order to develop a common understanding of terms used in this paper, industry standard definitions developed by Gartner, a leading technology research and advisory firm, have been adopted.

Gartner defines “information governance” as the specification of decision rights, and the use of an accountability framework to encourage desirable behavior in the valuation, creation, storage, use, archiving and deletion of information. It includes the processes, roles, standards and metrics that ensure effective and efficient use of information, so that an organization can achieve its business goals.

Gartner defines “knowledge management” as a practiced view of organizational knowledge in the context of regular activity. Knowledge management not only formalizes the enterprise’s intellectual assets. it also enables effective action through their use. Knowledge management as a practice promotes collaborative and integrative approaches to the creation, capture and organization of enterprise intelligence — including what is known but not necessarily documented.

The Relationship Between Information Governance and Knowledge Management

Information governance is the unifying or umbrella concept. All information, no matter what its category or form, must be governed. In other words, it must be valued, created, stored, used, shared, protected, archived and deleted or in rare cases, preserved in perpetuity.

A word of caution here: it does not matter how a firm classifies data, records, information or knowledge. There are no hard and fast rules for making these distinctions. The idea of ‘tacit and explicit’ is a useful one, with tacit knowledge being that which resides in the heads of people and explicit being that which is captured externally in some form. Not all tacit knowledge can or should be captured explicitly, but tacit knowledge can always be shared between people, a principle which is the foundation of all teaching and learning. It is not worth spending a lot of time making these distinctions. Instead of defining these terms, focus on how important the intellectual property is to the business, how many or few people have access to it in some form and how easy or difficult it is to capture, share and use.

Building Blocks That Advance Information Governance and Knowledge Management

Both IG and KM should be regarded as programs, i.e., an ongoing set of tasks, carried out by accountable and responsible individuals who are measured on the business outcome of the tasks. It is necessary to distinguish programs from projects. The former are ongoing and permanent, the latter have a beginning, middle and end.

The following “MOVES” are required to advance IG or KM :

Metrics

how progress or success is measured

Organization and Roles

who carries out the tasks

Vision

why the program exists and the desired outcome

Enabling Infrastructure technology that supports the program

Strategy what needs to happen to realize the vision