September 02, 2021

 Dr. Daniel Martin Katz

legal tech ai enterprise legal management elm legal data strategy legal data ai and law legal ai legal platforms legal analytics

Every day, legal organizations create massive volumes of data exhaust, just as a byproduct of completing their underlying work. Many corporate law departments and law firms understand the intrinsic value of this data and its potential to help support data-driven decision-making. Nonetheless, “data exhaust” can be difficult for an organization to harness effectively, given the daunting landscape of technologies, disciplines, and human capital.

Harnessing data exhaust and integrating new technology tools with existing technology and processes require a strategic and tactical perspective. Many organizations struggle to develop both a successful strategy and the operational capabilities to achieve their desired results.

The first step in becoming a data-driven organization is to assess the current state of the people, processes, and technology. A Legal Data Strategy relies on a thorough assessment of an organization’s current maturity to articulate a set of data objectives. These data objectives can then form the basis for establishing a roadmap and charting a course forward.

The Current Information Technology (IT) and Data Landscape 

Both law departments and law firms have begun to embrace new service models and procure new kinds of software products. In particular, in the past decade, we have witnessed an explosion in the number of legal technology suppliers and offerings. This proliferation in tools has created meaningful opportunities to work differently.

The forecast is not entirely sunny, though. Many software tools that have come to the market in recent years have the same central problem: they are typically individual point solutions designed to solve relatively specific problems. Therefore, while they may be suitable for their particular purpose, they help contribute to what might be called the Island of Unconnected IT Toys.

By their very nature and design, point solutions cannot holistically solve problems. An organization with multiple point solutions will quickly find itself working in several independent, siloed work streams, probably with numerous IT systems, none of which are well integrated or connected.

A law department or law firm might have the following unconnected IT systems: document management systems, contract drafting tools, e-signature add-ons, billing systems, spend management systems, and matter management systems — all of them with layers of permissions and rules-based protocols. Together, this results in an unmanageable number of moving parts that don’t always move in sync, creating issues all day, every day. Everyone wants to be data-driven, but these unconnected, isolated point solutions constantly throw up roadblocks in an organization’s data environment; easy integration and communication within and across platforms become difficult, if not impossible.

It is often while on this Island of Unconnected IT Toys that law departments and law firms express a desire to implement AI-enabled processes. While the desire for powerful Artificial Intelligence (AI) tools is understandable, the precursor to AI is often the difficult task of solving the more fundamental problem of a balkanized data infrastructure.

Targeted Questions Organizations Often Want to Answer Require Cross Module Data 

When we talk about Legal Data Strategy, we discuss a comprehensive, top-down approach of delving into your data to achieve greater transparency and predictability. Data on matters and clients, personnel and communication, resources, risk management and uncertainty, and data within documents (as well as metadata) – any record of fact within an organization can be leveraged to elevate your organization.

Collecting and organizing your data will quickly reveal patterns to make inferences and plan for the future. But where to start?

Here are purportedly straightforward legal business questions that far too often require a herculean effort to answer rigorously:

• How should the work be priced?
• How long will the work take?
• What are the optimal resources for this work?
• Are the optimal resources available?
• Will we ‘win’ the matter?

The Path to an Enterprise Legal Management (ELM) Platform

The good news is that it is possible to connect strategy and tactics to holistically repair the enterprise legal data environment. Legal organizations who proceed down the path of building out their medium- to long-term data strategy will see the value in connecting their currently unconnected information technology environments.

This thesis is core to the vision behind Elevate’s ELM. Multiple modules share structured data objects throughout the system, where data can be more easily leveraged to support insights.

This blog series will highlight some key attributes in Enterprise Legal Management platforms, including interoperability, the need for common data models, extensibility in and across core common modules, and other important topics. Stay tuned for more!