Like innovation, data has become a bit of a buzzword for legal. But, unlike innovation, data analysis has long been critical to legal services, as firms record time and billing data. While practice management systems and business intelligence dashboards have given firms the ability to analyse real-time matter, pricing and billing data, many legal businesses have also, in the past few years, taken a deeper dive into leveraging data to improve their systems and services, drive innovation and productise data services.
Mixing in data
As law firm systems moved into the cloud and tech giants developed affordable data analysis tools, data projects previously only undertaken by the biggest and most technologically advanced firms became accessible to all, and firms recruited data scientists and analysts with the skills to deploy them. This change has transformed the law firm back office and enabled firms of all sizes to build bespoke data services for internal users and clients.
But where do firms start, and how should they put data to use? Anthony Vigneron, director, legal technology solutions at Clifford Chance, outlines three core use cases for data analytics: optimising business processes and decisions; improving processes and workflows; and managing pricing and billing expectations and understanding client needs, which can be extrapolated to create bespoke client services. “Cross-functional data becomes more interesting when you want to understand why something is happening, or what you should be doing. For example, if you want to understand why some teams are performing better, or some practice areas are more profitable than others, you need to think more creatively and use different data sets, usually in different systems, and apply different methods and technologies,” he adds.
“Cross-functional data becomes more interesting when you want to understand why something is happening, or what you should be doing. For example, if you want to understand why some teams are performing better, or some practice areas are more profitable than others, you need to think more creatively and use different data sets, usually in different systems, and apply different methods and technologies”
Anthony Vigneron, director, legal technology solutions, Clifford Chance
“We are constantly looking to merge data from different systems in ways that add value,” says Simon Rees, head of data architecture at Bird & Bird. He continues by explaining how he applied his real estate background to rebrand the firm’s internal reporting, thereby better reflecting the flow of data around the business, and enabling the production of reports in real time.
The firm is also upgrading its finance system to reflect its growth from three to 30 offices: “We have introduced many small data-related changes to help us manage our business better, and together they are having a huge impact on reporting. We are leveraging more financial data to display in dashboards and help partners manage their clients and matters – instead of running multiple reports, we display financial and other management information visually. Dashboards have reduced feedback loops as they refresh a couple of times a day, rather than weekly or monthly.”
Microsoft Power apps add functionality to Power BI beyond data visualisation. “This means we can leverage Power BI across other Microsoft products like SharePoint and Office 365,” says Rees, who is also looking at combining Microsoft tools with legal-specific systems, for example from Aderant, Thomson Reuters and Intapp.
He adds that data integration has helped the firm manage its financial system upgrade, using visualisation for testing processes and tracking progress across different stages of the project. “In terms of teams within the business, we are using Power BI to help visualise time utilisation data – how busy people are and expect to be in future.”
Weightmans has long been pushing ahead with developing business intelligence tools, having used a data warehouse to bring together data from all the firm’s business systems, including financial management, case and matter management, HR and CRM (customer relationship management) for some 15 years. “This enables us to slice and dice all our business information by client, case, office, team, segment and even software,” explains chief innovation and technology officer Stuart Whittle. Most clients are interested in case management information from MatterSphere, which is delivered via an extranet, an SSRS-style report or data visualisation dashboards that are created using Tableau.
Building on data foundations
Big tech platforms – particularly Microsoft systems – are providing the infrastructure for more advanced legal data analytics. As Daniel Hoadley, head of data science and analytics at data-driven boutique Mishcon de Reya explains, the core infrastructure for data analytics and visualisation across the firm is Microsoft Azure, including Power BI, and although the more advanced data science projects that Hoadley and his team are applying to the firm’s contentious practices were built in Amazon Web Services (AWS), the plan is to migrate the entire stack to Azure.
And at Clifford Chance, cloud-based systems and visualisation tools have enabled the firm to leverage data across its global offices and build on top of existing systems. “Although we have enterprise resource planning (ERP) systems for core business functions, and we use Tableau and Power BI for presenting standard reports and descriptive analytics, Microsoft Azure is our work bench in the cloud for cross-functional data, where we synchronise the datasets we need for each use case without touching the source systems,” says Vigneron.
He adds: “We use Azure to deliver individual use cases and, case by case, we are building a utility platform that serves the whole firm. It is lighter and cheaper to operate because we aren’t trying to solve every problem at once. We don’t need investment planning or the ability to anticipate potential use cases. It is incredibly agile.”
“Clients are generally interested in matter data – the total reserve on certain claims, how many claims have gone to a tribunal this month, for example. Those with large portfolios often want high-level data that they can then filter by segment, matter or geography, using interactive Tableau dashboards.”
Stuart Whittle, chief innovation and technology officer, Weightmans
Actionable insight
However, just because data is available doesn’t make it relevant, and much of firms’ recent efforts has encompassed ways of ensuring available data becomes useful data. “One key thing when thinking about which systems and data to integrate is what we actually want to achieve, and what meaningful value we can add to our clients, our business and our people,” says Emma Sorrell, innovation manager at Burges Salmon. “If you’re going to integrate systems, it’s important the outcome is actionable insight and not ‘data for data’s sake’. Alongside this, there is a need for data governance processes and data quality capabilities, with appropriate new roles and disciplines required.”
Vigneron highlights the importance of resourcing specific skillsets that can make the most of that data, such as those possessed by Clifford Chance’s data team in Hyderabad: DevOps engineers, data engineers, data architects, visualisation and UI (user interface) specialists. He also cites the value data scientists offer in creating actionable insight. “One of our teams was trying to predict pricing so they could give clients a more precise view of the costs involved. Previously they would have used historic data and recent experience, but that is not a scalable solution,” he explains. “Initially, the team gathered 80 data points to assess and predict pricing, but our data scientists then found that we only needed seven data points. By identifying what really mattered, we could give teams an easy-to-use interface to make pricing predictions.”
Mishcon de Reya data scientist Amy Conroy applies similar criteria to developing predictive analytics for litigation. “We use data to ask the questions that people historically ask fee earners around time and cost. The data is there, but it is not always easily surfaced or searchable. In the first instance, we consider the data we have, how to expose it and what sort of system we should apply to it.”
Mishcon de Reya uses matter data, time records, claim forms and billing data for expertise location to identify the right solicitors and barristers for each case. “The goal is to automatically capture information, for example to capture the value of claims by building a machine learning model that extracts the value from each claim form. We put a lot of work into building the right data sets,” adds Hoadley.
Weightmans combines its data warehouse with data visualisation to give large insurance company clients a real-time overview of all their matters. “We use the same data lake for internal (financial) reporting and reporting to clients,” explains Whittle. “Clients are generally interested in matter data – the total reserve on certain claims, how many claims have gone to a tribunal this month, for example. Those with large portfolios often want high-level data that they can then filter by segment, matter or geography, using interactive Tableau dashboards.” Combining multiple perspectives can reveal hidden insights – for example, one hot spot of tribunal claims was found to be due to increased trade union activity, which could be mitigated by earlier negotiation.
Data analytics are not always about predicting costs or supporting decisions – they are also used to control quality and consistency across larger matters where wrong or incomplete data early in a process can cause issues further down the line. “For example, some lawyers ignore key data points when filling in their timesheets. Data analytics can identify and address those issues, before billing,” says Vigneron.
Hoadley at Mishcon de Reya agrees. “Early matter onboarding is critical, and our data scientists in partnership with our practice transformation team have been working on ways to help lawyers quickly identify the most salient information for each case.”
Improving client outcomes
Data analytics that help firms better understand their clients is a significant area of development. In 2021, Clifford Chance rolled out a globally scalable customer experience system based on Adobe Experience Manager. “We wanted a complete view of the customer journey across all our digital platforms, and the only way to achieve that was to use a big tech platform such as Adobe,” explains Vigneron. “The data enables us to see what is and what is not being used, and what we can stop doing.”
“We wanted a complete view of the customer journey across all our digital platforms, and the only way to achieve that was to use a big tech platform such as Adobe. The data enables us to see what is and what is not being used, and what we can stop doing.”
Anthony Vigneron, director, legal technology solutions, Clifford Chance
Conversely, Bird & Bird selected Intapp’s CRM, which integrates directly with its Intapp Open business intake system. “This will allow the CRM to tap into our existing marketing data,” explains Rees. “CRM is a challenge for law firms, so we are moving to a system that will integrate more closely with other legal software. We are also looking at how we can add more data structure around referrals, and include them in the data flows across our systems,” he adds.
At Mishcon de Reya, data innovation is focused on creating capabilities that improve case win rates, says Hoadley. “For example, our litigation support hub provides hands-on matter lifecycle support. A lot of data science work is designed to trigger alerts to the practice transformation team.”
While many firms are using data analytics to provide faster, more accurate services, and presenting financial and matter data back to clients, Kennedys IQ is leveraging claims data to create bespoke services for insurance companies. As product and innovation director Karim Derrick explains, while the starting point was standardising processes to enable non-experts to run a defence, they are now focused on optimising outcomes. “This means examining the data [claims processes] generate to optimise offer strategies and determine market trends and claimant solicitor behaviours.” Another project brings in data science even earlier, at the underwriting stage, with a view to applying machine learning to prevent claims and coverage disputes.
While the overall direction of data innovation is towards improving the client experience and creating data-driven bespoke services, the big change recently is the strong presence of non-legal-specific technology in legal innovation – so it seems law firms are only at the start of their data journeys.