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Litigation Analytics: The Types of Data You Need in Court

April 03, 2023 (8 min read)
litigation analytics icons hover over a laptop and gavel

Summary


This article was originally published on March 6, 2019, and was updated on May 17, 2023. 

Technological advances are revolutionizing the process of litigation. The challenge — and opportunity — of exploding data volumes is everywhere, and the legal arena is no exception. There is so much unstructured, unconnected, yet potentially critical information that it can feel impossible to make sense of it all—or even know where to begin.

The good news is that attorneys who can harness these masses of data into valuable insights through litigation analytics can create a competitive advantage — and cutting-edge litigation tools are helping them do just that. 

Analytics can help attorneys describe and understand what happened, predict what will happen, and ultimately prescribe the best path forward. In this article, we explore the different types of data you can harness in your own litigation strategy and discuss how various analyses can be applied.

But first — what is litigation analytics?

What is Litigation Analytics?

Litigation analytics — sometimes referred to as legal analytics — is the process of analyzing data related to past cases and legal proceedings to help inform and guide decision-making in current cases. Data can be available in a variety of forms and is often spread across disconnected sources; this can include:

  • Case law
  • Court records and dockets
  • Regulatory content
  • Public records

Litigation analytics tools help attorneys sift, sort, connect, contextualize, analyze, and even visualize massive amounts of this data in powerful, productive new ways, offering the following types of insights:

  • Court trends
  • Fact patterns
  • Case outcome analytics
  • Behavioral insights on key case players like judges, opposing counsel, and experts 

These insights fall into several different categories of litigation analytics, each with its own unique applications and benefits. We'll discuss each type briefly below.

(Subcategories of Litigation Analytics; Click to Enlarge) 

Court Analytics

The process of using information about past cases to make inferences and predictions about the court system is court analytics. Data used can take the form of case outcomes, judges’ decisions, and the length of time it takes for cases to be resolved. There are several key applications, including:

  • Identifying trends and patterns in the court system
  • Predicting the likelihood of success in future cases
  • Spotting potential weaknesses in a case

Overall, court analytics is a valuable tool for lawyers looking to gain insights into the court system and make more informed decisions in legal proceedings. By leveraging data and insights, lawyers can increase their chances of success and achieve better outcomes for their clients.

  • Ready to try court analytics for yourself? Check out Verdict and Settlement Analyzer and see how you can start evaluating the success of your future cases.

Judicial Analytics

Judicial analytics is similar to court analytics; however, it focuses specifically on the behavior and decision-making patterns of individual judges. This type of analytics can help lawyers understand how a judge is likely to rule on a particular issue or case and can help inform their strategy accordingly.

For example, tools like Context® can analyze a judge’s past ruling behavior, make predictions, and even provide samples of a judge’s exact language, ultimately increasing chances of success in the courtroom. 

Take a Free Guided Tour of Context

Attorney Analytics

Attorney analytics involves analyzing data related to individual attorneys, including:

  • Success rates in previous cases
  • Types of cases typically handled
  • Areas of expertise

This information can be used to help lawyers choose the right attorney for a particular case or to identify potential weaknesses in the opposing counsel’s case.

Law Firm Analytics

Law firm analytics provide similar insights as attorney analytics, with the key difference being that the data is used to examine an entire firm, as opposed to an attorney.

While some of its applications overlap with attorney analytics, law firm analytics can also be used to identify trends and patterns in the legal market. By analyzing data on the performance of law firms across the market, lawyers can gain insights into which areas of law are growing or declining — and which firms are the most successful in those areas.

Types of Legal Data Analysis

As mentioned above, litigation analytics can help with anything from describing what's happened in the past to making inferences about what should happen in the future. The varying ways to conduct an analysis fall into four different categories, each of which we've detailed below.

(Types of Data Analysis; Click to Enlarge)

Descriptive Analytics: Describing the Past

Data is just data until you learn something from it and use it; one way to do this is to use data to describe what's happened in the past. Descriptive analytics sifts through large volumes of historical legal data to identify trends and patterns of behavior. The resulting content helps attorneys:

  • Identify emerging legal trends
  • Understand how a judge typically rules in a specific type of case
  • Analyze the success rate of adversaries or potential outside counsel over time
  • Flag potential issues within legal briefs or motions
  • Understand the other jurists and opinions your judge cites most often to ensure your arguments are aligned

Complex patterns, trends, and relationships can be further condensed into easily accessed and understood visuals, such as charts and graphs. These visualization tools allow you to, among other things, map search terms, see case connections, or literally see and compare settlement valuations.

Diagnostic Analytics: Understanding the Past

Diagnostic analytics is similar to descriptive analytics in that it utilizes data to better understand historical trends and patterns. However, while descriptive analytics focuses on questions like what happened, how many, where, and when, diagnostic analytics focuses on answering questions like why did this happen and what caused it? 

Attorneys can apply diagnostic analytics by analyzing case law, legal briefs, contracts, and other legal documents to identify patterns, trends, and anomalies that provide insights into legal issues and outcomes. 

  • Hone your legal brief with the help of Brief Analysis, which can help you quickly spot winning arguments similar to your own 

Predictive Analytics: Forecasting the Future

While understanding the past is an important first step, the real value in analytics is in gaining insights into future implications. Predictive analytics, as the name implies, aims to predict what is likely to happen in the future. It does so using a mixture of innovative methods—machine learning, predictive modeling and intelligent algorithms—as well as enormous volumes of rich and varied data.

Drawing from past behaviors and current data, predictive analytics can address a range of questions and provide valuable insight for decision-making. For example: 

  • Cases with similar fact patterns: If your client faces a liability claim around a product, predictive analytics can use cases with similar fact patterns to predict the case’s timeline and likely award. These predictions can go into a cost analysis to drive better litigation decisions.
  • Judge behavior: While the decision-making pattern of a judge is always subject to change, analysis of their track record and how they respond to certain motions can indicate probable patterns of behavior. Attorneys can then leverage that insight to create a winning strategy.
  • Language patterns: Sometimes it’s not just what you say but how you say it. By analyzing the language that is most commonly used by a particular judge in granting or denying motions, you can better predict the language that will be most persuasive in your motions, driving up your probability of success.

Of course, predictive analytics cannot guarantee the outcome of a case or provide 100 percent certainty. However, it can make intelligent predictions on potential or even likely outcomes. And with visualization tools that can map potential outcomes and probabilities in a range of scenarios, the most likely result becomes easier to see.

Prescriptive Analytics: Identifying the Best Path Forward

This category of analytics goes one step further than predicting an outcome. Prescriptive analytics suggests a specific direction to follow based on likely outcomes. This method compares and contrasts multiple outcomes based on different actions and recommends the best path forward to attorneys.

In many ways, prescriptive analytics is the technological equivalent of the seasoned attorney who counsels less-experienced attorneys based on historical data and experience. This “trusted advisor” can access and analyze far more data far more quickly than any human, providing insight and guidance never possible before.

Cognitive Analytics and Artificial Intelligence

As technology continues to advance, each type of analysis mentioned above becomes more accessible to attorneys looking to make data-driven decisions. Cognitive analytics, which can impact each of the four types of analysis, involves the use of machine learning and natural language processing to mimic a human's decision-making power and problem-solving skills. 

To many, this type of analytics is known as artificial intelligence (AI) — and its capabilities can provide large benefits to attorneys who are willing to learn to embrace it. Developments in Generative AI, specifically, are pushing cognitive analytics and artificial intelligence forward, and attorneys have more options for using this technology than ever before. 

From Law Office to Courtroom: Integrating Litigation Analytics into Your Strategy

There is no doubt that data and advanced analytic technologies will have a significant impact on the practice of law, from how legal research is conducted and strategies are defined to execution in the courtroom. Lawyers and legal departments are in a transformative period in which data analytics, machine learning, natural language processing and other deep-learning technologies can have a profound impact on how lawyers like you work. The competitive advantages in mining data for knowledge and insight will inevitably make analytics a must-have tool in the workplace. The question is no longer whether legal firms will adopt these new technologies, but rather, how fast and who will get there first.

LexisNexis® is here to help you as you incorporate litigation analytics and generative artificial intelligence into your courtroom strategy with AI-enhanced Lexis+® and NEW Lexis+ AI™Contact us to learn more about the tools at your disposal or click below to access a free trial of Lexis+.