In today’s data-driven world, almost every aspect of business is being revolutionized by the power of analytics. The legal field is no exception. Organizations are increasingly turning to legal data analytics to gain deeper insights, make more informed decisions, and ultimately achieve better legal outcomes. What exactly is data analytics in the legal realm, and how are organizations putting it to work?
What is legal data analytics?
At the core, it is applying data analysis methods to legal information. This data originates from diverse sources, both internal and external to an organization. Internal sources include case management systems, litigation and contract records, legal spend information, and compliance data. Externally, organizations leverage public court records, legal research databases, data on past litigation outcomes, and data housed with legal service providers By analyzing the information in these systems, organizations can identify patterns, trends, and correlations that can inform (and accelerate) their legal strategies and business decisions.
AI, including generative AI, are considered a powerful and increasingly integral part of data analytics. In fact, AI is often the driving force behind many of the advanced analytical capabilities used by legal teams today. When discussing data analytics in the modern context, it’s often synonymous with leveraging AI-powered tools and techniques to extract valuable insights from legal data.
How do organizations use legal data analytics?
Organizations that effectively leverage legal data analytics and AI are experiencing substantial benefits across their legal functions–from reduced legal costs through enhanced decision-making and optimized legal spending to improved risk management by enabling the proactive identification and mitigation of legal risks.
With the myriad potential benefits, in-house legal teams are increasingly adopting data analytics and AI to enhance efficiency in routine tasks. This allows for a strategic redeployment of in-house legal expertise and external legal spend towards more impactful business initiatives.
The applications of legal data analysis, and AI in particular, are vast and continue to expand, with more than 70% of in-house legal teams focusing on analytics and AI adoption for modernization, according to a recent litigation modernization survey. Here are some key ways organizations are leveraging this powerful tool today.
Litigation strategy and risk assessment
Legal data analytics empowers organizations to make more informed decisions across various aspects of their cases. For instance, in litigation strategy and risk assessment, using AI to analyze historical litigation data can help predict the likelihood of success in similar cases, allowing for a better assessment of potential risks and more accurate estimation of potential costs.
Furthermore, by identifying trends in litigation, such as recurring issues, jurisdictions with higher litigation rates, and the most prevalent types of claims, organizations can proactively address potential risks. Data analytics also plays a crucial role in evaluating settlement strategies, providing insights into past settlement amounts in comparable cases and the anticipated likelihood of success at trial.
eDiscovery and investigations
Data analytics plays a crucial role in eDiscovery and investigations by providing powerful tools for sifting through vast amounts of electronic data. By applying analytical techniques, organizations can quickly identify key documents and custodians relevant to a case, significantly reducing the time and cost associated with manual review. This includes identifying patterns, anomalies, and communication patterns within the data, helping to uncover crucial evidence and potential areas of concern.
Furthermore, legal data analytics can assist in prioritizing documents for review and even time-intensive privilege logging—an area where 50% of in-house teams plan to use AI/generative AI–streamlining the review process and ultimately leading to more efficient and targeted eDiscovery and investigation outcomes. (The Electronic Discovery Reference Model (EDRM) provides an overview of how legal teams are using AI in the eDiscovery process.)
Contract management and compliance
Legal data analytics offers significant advantages in contract management and intelligence. By analyzing contract data, organizations can effectively identify contractual risks, pinpointing potentially problematic clauses, detecting areas of non-compliance, and gaining a comprehensive understanding of their overall contract risk profile. Moreover, insights derived from analyzing past contract terms can improve contract negotiation by providing valuable benchmarks and data-driven insights for securing more favorable agreements in future dealings.
Legal operations
Legal data analytics significantly enhances legal operations by providing valuable insights for optimization and performance measurement. By analyzing data on case lifecycles and resource allocation, organizations can effectively optimize legal workflow, identifying bottlenecks and improving overall operational efficiency. Furthermore, data analytics offers crucial metrics for measuring legal department performance, including case resolution times, cost savings achieved, and compliance rates. Finally, the analysis of legal spend data also contributes to optimizing legal spend, enabling the identification of overspending, the tracking of outside counsel performance, and the negotiation of more favorable rates.
Intellectual property management
Legal data analytics provides significant value in IP management. For example, by analyzing patent data, organizations can conduct patent portfolio analysis to identify their most valuable patents, assess the overall strength of their patent portfolio, and make informed decisions regarding the filing of new patents or the abandonment of existing ones. Similarly, through patent landscape analyses, IP teams can quickly get a holistic view of a technology area to help assess its innovation strategy and competitive advantage.
Risk versus reward: getting started with legal data analytics
As organizations seek to integrate analytics and AI into their legal workflows, they are focused on understanding where to use analytics internally, or through external service providers, for the biggest bang for the buck—and starting with those processes first. For example, a corporate legal team could employ AI to review supplier contracts, recognizing that a potential 5% error margin is a worthwhile trade-off for substantial improvements in efficiency and cost savings compared to manual review.
At the same time, when exploring the use of generative AI in particular, legal teams must place a strong emphasis on accuracy, data privacy, safeguarding intellectual property, and seeking expert advice to effectively manage risks and realize the technology’s full potential. Several key areas warrant careful thought and attention, including hallucinations and output validation, data privacy considerations, data privacy and ownership, and the expertise needed to guide teams through the process, address technical challenges, and assess potential risks.
Finally, effective implementation of analytics and AI requires a strategic approach. Teams should begin with pilot projects to evaluate accuracy, speed, and performance. A phased rollout, starting with limited deployments, allows for gradual integration and optimization of workflows to align with AI capabilities. And like any new skillset, legal professionals should be trained to effectively use these tools.
Conclusion
The legal landscape is set to be transformed by the continuous development of analytics and AI; its integration is a foregone conclusion. To harness the benefits of this technology, including innovation and efficiency, legal teams must adopt a cautious yet practical strategy. This involves focusing on concrete applications, such as automating routine processes, and proactively addressing potential risks.
UnitedLex partners with legal teams to align legal excellence with business objectives leveraging modern, tech-enabled legal services.
