Laptop with analytics

Wouldn’t it be nice to be able to accurately predict the outcome of a legal matter? To be able to really get a sense of how long it will take to complete a case, how much the budget should be, and which law firm partners are best suited to litigate the matter?  

These are questions that corporate attorneys and claims managers have wrestled with for years. Typically, they base their answers on gut feelings or instinct. They rely on their personal experiences or expertise. They may choose law firms based on which partners they’ve worked with in the recent past, a phenomenon known as “recency bias.” Or, they may use elementary tools that limit them to estimating new budgets, staffing levels, and cycle times based on past data, a process called historical extrapolation.  

These strategies do not use reliable results because no two matters are alike. Attorneys and claims professionals need a better way to make more accurate decisions that will positively impact the way they approach matter management. 

Using predictive analytics is that better way.

What is predictive analytics

Predictive analytics combines historical and current data to provide accurate predictions of future outcomes. The process arms corporate attorneys and insurance claims managers with actionable recommendations that help them make better decisions pertaining to their matters. 

There are many use cases for predictive analytics in both corporate law and insurance claims departments. A corporate attorney might use predictive analytics to estimate how long it will likely take to resolve a legal matter based on data pertaining to cycle time trends in the past six months for the particular law firm litigating the case. A claims manager may use predictive analytics to make an informed decision as to which law firm partner to use or eliminate firms that may not be appropriate for a particular matter.  

Regardless of the industry or job title, predictive analytics offers legal and claims teams the ability to make better decisions, faster—by putting data and analytics to work. 

Providing context to data 

Predictive analytics takes away the guesswork and replaces it with data-driven insights. It provides context to your data by layering it with actionable insights originated by an artificial intelligence (AI) engine. These insights are continuously improved by machine learning algorithms.  

AI and machine learning technologies can dig through the mounds of valuable data that companies have accumulated and use that information to provide guidelines for how to approach a matter in a new, more strategic way. AI analyzes vast amounts of information and detects patterns in the data that may be undetectable to human beings. Simultaneously, machine learning—a branch of AI—analyzes this data. The technology provides users with recommendations they can use to make better decisions that are tailored to the specific needs of each matter and becomes smarter over time.  

Putting predictive analytics into practice

Harnessing the power of predictive analytics has been a long-term goal for many corporations and insurance claims departments. It’s been something to strive for yet has always seemed just over the horizon. 

The good news is that we’ve now reached the horizon. Predictive analytics is real and is here today. 

The bad news is that many organizations aren’t quite sure what to do with it, or how they can put it into practice. For them, we’ve created a new eBook, Putting Predictive Analytics to Work for You.

In this eBook, my colleague Jeffrey Solomon and I take readers through a deep dive into predictive analytics and its potential for corporate legal and insurance claims departments. The eBook covers a range of topics, including:

  • How predictive analytics is impacting businesses 
  • The definition of predictive data modeling 
  • How to employ predictive analytics in your organization 
  • Predictive analytics use cases 

Putting Predictive Analytics to Work for You is for anyone who wants a better understanding of how to put data to work for them to make their decision-making processes more accurate, efficient, and effective. Be sure to download your copy today.


About The Author

Vince Venturella

Vince is the product manager responsible for the development of Wolters Kluwer's ELM Solutions insurance market offerings for claims and staff counsel. Vince is a strategic, results-oriented legal technology leader with a consistent record of improving processes, developing innovative solutions, and leading diverse product teams. He has worked in legal management consulting and technology solutions within the insurance market for almost a decade. Vince is a graduate of The Ohio State University in Columbus, Ohio.