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5 Litigation and AI Trends to Watch in 2024

Dynamic Data Platforms Up-level Corporate Lawyering

The job of corporate General Counsel (GC) can be reduced to three aims: protect the business from unacceptable legal risk, help the company achieve success, and spend the legal budget cost-effectively. However, the GC faces one central challenge: how to hire, equip and deploy the legal team to achieve these aims in a balanced way. The “digital GC” seeks to put data at the heart of these decisions, and in doing so they may radically change how the corporate legal function operates.

In recent years the legal industry has been taking steps towards this data-driven decision-making approach. With corporate legal departments that focus heavily on transaction support, traditional contract lifecycle management (CLM) systems have been deployed as the foundation for this approach, but clients often find in practice, the technology lacks real transformational impact. In contrast with classical CLMs, a dynamic data platform brings together the systems, processes and people to deliver insights that will enable the GC to fully optimize the legal function. While it is possible for a legal department to procure and interconnect the right products for the overall technology solution, engineer the legal function processes correctly, and deploy some of its staff into operational roles that support the solution, the dynamic data platform we are talking about here is essentially an eco-system, that is best delivered to legal as a service.

Let’s look at the functional capabilities of this data platform. Essentially, there are three levels of insight that the GC is seeking:

  • Activity Landscape

    At the most basic level, the GC needs to understand the core features of how the legal team operates—what commercial activities are being supported by the staff and the principal patterns of that activity. This would cover, for example, how many deals are being handled in a given time period, for which locations, business units, value thresholds etc. In other words, classical CLM information.

  • Service-level Profile

    This next level generates at least a preliminary view as to the functional quality offered by the team, by reference to some basic service levels. These include the number of working hours taken to acknowledge a client instruction, turnaround time for a first-pass contract review and so on. This is valuable information for the General Counsel, providing a degree of insight into the level of operational excellence performed by the department. This information can enable leadership to highlight to their clients how the legal function contributes to the “commercial success” element of the department’s core charter. Many corporate law departments are now deploying combinations of CLM and workflow reporting systems to produce such data.

  • Risk Alignment

    This is where a dynamic legal data platform comes into its own and addresses the question of ‘How can the GC know?’—that department resources are being intelligently aligned with the areas of most significant legal risk for the corporation.

    Take the case of a sales-driven organization supplying services that range from basic to highly tailored for customers. Here, the legal department will typically deploy a significant proportion of its legal spend on supporting contract negotiations. This is a logical decision for the GC because revenue-generating activity aligns with the “commercial success” driver, and protecting the company against “bad” contracts aligns with the risk reduction aim.

Yet although the alignment of resources may be logical, that does not mean it is properly informed. The function of the data platform is to allow the GC to dig deeper into the question of whether legal resources are actually being deployed in the right way, relative to risk and commercial benefit.

As a first step, the data can be used to track the most frequently negotiated contractual topics (MFNs). Over the course of a year, the GC will be able to acquire a fully informed view as to both the MFNs that absorb the most time in negotiations and the gap between the company’s standard positions, and those compromises that are approved by way of exception. This then allows the legal team to adjust standard terms, playbook content and technical training—all with a view to reducing time spent on contract pursuits and proactively shifting the allocation of legal resource to the areas of maximum pain.

But the insights do not stop at this point. A truly holistic, end-to-end data platform utilizes information from both the pre-signature and post-signature phases of a contract. Because what is the point of signed contract terms if not to minimize a company’s risk once the deal is being delivered? For this, the data platform needs to connect seamlessly to a contract management system, which has been calibrated to capture information and patterns emerging from transactional disputes. What sort of information would this connected platform reveal? Here are some examples:

  • What are the most common causes of contractual dispute between the company and its customers?

  • What is the settlement profile for these disputes (say, over a 12-18 month period)? For example, what proportion of disputes reach formal litigation, or are settled with some sort of price reduction or financial compensation impacting the company?

  • What role do the terms and conditions play in these disputes? For example, during the dispute, how often do the signed front-end terms and conditions come into play–the cap on liability, say, being relied upon by the company to reduce the exposure presented by the dispute?

These and related data points provide the General Counsel with an unparalleled level of insight as to legal function activity and how it aligns (or mis-aligns) to corporate risk and reward. This is what “digital” really means to the corporate law department.

For more information on data contract platforms, read our whitepaper Data-Driven Commercial Contract Review.

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