Legal Business

You’re gonna need a bigger boat! – big data and the modern law firm

Big data has been hailed as the next big thing to hit legal tech and has already become a force in US litigation. Legal Business assesses the prospects for the analytics-powered law firm

In 2011, McKinsey defined big data as ‘datasets whose size is beyond the ability of typical database software tools to capture, store, manage and analyse’ and hailed big data analytics – applying algorithms to crunch together numbers from disparate sources to uncover new correlations, patterns and trends – as ‘the next frontier for innovation, competition and productivity’.

Although big data analytics have been successfully applied in other industries, such as retail and healthcare, law firms have only relatively recently shifted this topic from the conference agenda to the boardroom table.

In an article last year, McKinsey highlighted some of the critical questions that leadership teams should be asking about technology strategy. They include asking how IT will help the organisation recognise the competition and compete successfully; exceed customer expectation in a digital world; improve performance and agility; and identify and act on opportunities and threats. For many law firms, the answer involves analysing big data sets residing outside the firm, together with internally generated management and client information.

According to Derek Southall, partner and head of strategic development at Wragge & Co, there are a number of areas where law firms are applying big data analytics to address these issues, such as interrogating internal information to improve the firm’s understanding of its clients and develop better ways of addressing their needs, and leveraging external information to enhance client service, including using publicly available information to advise clients on sector developments.

And while law firms are relatively new to this area, some are leading the way, using tried-and-tested techniques that have been given an innovative twist, or others that are truly pioneering.

Age of discovery

E-discovery is where it all began. Sifting through thousands of documents in a case necessarily involves big data techniques and increasingly sophisticated technology is helping lawyers extract relevant evidence from electronically-stored information.

Tracey Stretton, legal consultant and e-disclosure specialist at Kroll Ontrack, says there are a number of data technologies that have shifted specifically from e-discovery to mainstream legal IT. These include machine-learning technology for determining relevant documents for a case (this even pre-dates big data); applying predictive coding and artificial intelligence techniques to billing data; and financial metrics to project litigation costs and bring efficiency to the discovery process.

According to Stretton, e-discovery applies big data technology to unstructured data in different media and on different platforms. Big data will foreshorten the litigation process so that matters may be resolved by early case assessment. Law firms have also discovered that the data tools used for e-discovery can be applied elsewhere in the business. They are starting to invest in these tools and bring the e-discovery process back in house.

At Eversheds, chief information officer (CIO) Paul Caris is looking at using big data techniques to find ways to make e-discovery more accessible and cheaper. While e-discovery is becoming more sophisticated and effective, the costs involved are prohibitive for employment cases, for example, where compensation is capped. Nonetheless, Eversheds is working in partnership with CCL Forensics on an e-discovery proposition for smaller, lower-risk cases.

Ultimately the use of big data analytics in the context of e-discovery has limitations. As Janet Day, director of IT at Berwin Leighton Paisner (BLP), observes: ‘Most e-discovery is not classic big data analysis because it is searching for a known or semi-known quantum. Big data focuses on the unknown unknowns.’

While e-discovery involves interrogating client and external data, law firms themselves hold vast amounts of information on various platforms. Sophisticated search engines, many of which originated in the e-discovery space, are enabling firms to apply basic big data techniques across their internal systems to glean business and client intelligence.

DW Reporting advises firms on deploying business intelligence and data visualisation tools. ‘It is important for any organisation to understand where business-critical information resides and develop an effective data management strategy,’ argues managing director Dan Wales. ‘It is about bringing together data sources from around the firm.’ Law firms increasingly employ business analysts to interrogate their internal data and deliver business process improvements, often utilising data mining techniques such as interactive dashboards and data visualisation to present the findings.

Wales advocates creating an ‘organisational data map’ to deliver operational insights and identify where the firm derives its competitive advantage. ‘Cross-referencing internal data, for example in client relationship management (CRM) systems with publicly available data, can give firms a better understanding of client organisations and the sectors they operate in,’ he observes, adding that this type of approach is commonly applied to M&A due diligence, where internal data is cross-referenced with external business databases such as Dun & Bradstreet and presented using real-time interactive dashboards.

Big data techniques are also helping firms develop and deliver services tailored to specific industries and practice areas. ‘Many firms are taking a lead role in using big data analytics to drive internal efficiencies and deliver better services to clients,’ says Sheila Doyle, global CIO at Norton Rose Fulbright. ‘Organisations may be overwhelmed with daily feeds of data from different sources. The challenge is to find ways to turn these rich sources of data into meaningful insight that will be of value to clients.’

DWF, for example, uses big data analytics to deliver a specific service to its insurance clients – its specialist fraud team deploys it to uncover potentially fraudulent insurance claims. ‘We cut together data on our Lexis Visualfiles case management systems and other financial systems with information provided by our clients to identify potentially fraudulent claims, using IBM i2 Analyst’s Notebook visual intelligence analysis software, which collates, analyses and visualises data from different sources, presenting a visual representation of patterns and correlations,’ says DWF chief technology officer Richard Hodkinson.

This process is currently ‘on premises’, but DWF is considering migrating to a hosted cloud as the volume of data continues to grow. ‘We use it to find information within the data that we would never know otherwise,’ says Hodkinson, who is also working with IBM on the use of artificial intelligence to introduce more automation around the firm’s handling of fraud cases.

Another area of exploitation is defendant insurance work, where DWF handles high volumes of small cases with similar traits. Data tools are used to compare current cases with previous ones to predict which are likely to require the input of a lawyer. Hodkinson recognises that sophisticated data analytics require particular expertise and as a result DWF employs specialist software engineers and fraud analysts.

Another major insurance adviser, Weightmans, is using data analytics to streamline its volume services and give clients real-time access to its information. Information systems and operations director Stuart Whittle says the firm captures management information relating to a wide range of clients in the public sector, as well as insurance industries and other corporates. ‘We create interactive client dashboards so clients can access their information on our system and make it meaningful. For example, some of our real estate clients manage large property portfolios, so we can show them on an interactive map where all their properties are, how long the leases have to run, what the repair covenants are and so on. This resource is extremely popular with clients who are giving us additional data so they can include it in their analysis – which is not necessarily data we would normally have.’

Weightmans is also supporting its insurance clients by visually presenting large amounts of data about their claims portfolios in a format that allows them to interrogate it in different ways. ‘We help them manage their information and suggest strategies for minimising claims,’ says Whittle. ‘The interactive dashboard allows us to cut the data in different ways, plot trends and identify patterns,’ he explains, adding that while the technology is relatively straightforward – SharePoint Web Parts or QlikView – the interpretation is critical.

He adds that data analysis depends, for example, on whether the client is the insurer or the insured. ‘We use our understanding of the information, its context and the client organisation to spot patterns and trends.’

The next step will be to apply statistical rigour to the findings based on the Lean Six Sigma principles that Whittle is applying to other business processes within the firm. ‘We have sufficient data points to apply correlations, hypothesis testing and regression testing to uncover patterns and trends. It is also about looking at outliers to find out, for example, why some cases take twice as long as others.’

The firm is recruiting a statistician with an insurance background to introduce more complex analysis to client datasets. ‘The idea is to combine data analytics with our knowledge of our clients’ business and the challenges they face, and identify new ways to advise and help them,’ he adds.

Although big data will find correlations that are meaningless as well as useful, already the data visualisation dashboards are helping Weightmans win new business from existing clients, asserts Whittle.

Tailor made? Legal big data products in the UK

Nearly all of the big data innovators in the legal sector are using non-legal-specific software: from Radian6 social analytics, IBM i2 Analyst’s Notebook and QlikView data visualisation, and e-mail platform Mimecast, through to e-discovery tools Kroll Ontrack and Recommind, all have general business application and none take into account the vagaries of the legal profession.

DW Reporting offers law firms a vendor-neutral strategic data management and reporting consultancy, helping firms apply the right software to the data residing within their various systems.

The latest practice management offerings from the big players in legal IT, notably Thomson Reuters and LexisNexis, and newer entrants such as Peppermint Technology, are built on a single database that feeds all of a firm’s various tools and applications. This makes it easier to apply big data tools and methodologies across all its information resources, as well as adding external, publicly available or purchased data – from legal and business information providers – to the mix. In February it was announced that LexisNexis would partner with The National Archives in the UK for Big Data for Law, a project to use analytics to study the law and legislative process.

However, it is surprising not to find more vendors offering legal-specific data analytics software to the UK legal market equivalent to those available in the US. This is probably because larger UK law firms until only recently put less of a premium on litigation than their US counterparts, so big data has developed more on the business intelligence side.

However, this is likely to change as more US vendors adapt their products to the liberalised UK legal sector. One of the first to cross the pond is Manzama, which offers firms a ‘listening’ service – a cloud-based software engine that collates and aggregates unstructured data from external business, news sources and social media to provide firms information about their clients and competitors, and the industries they work in. As Miles McGoun, senior vice president of global sales comments, information can be filtered by user interests – by sector, industry, geography – and by ‘trusted sources’, ie differentiating between leading publications and, for example, blogs. It includes the capability for users to personalise information by individual and practice groups, and share it with their peers and clients. Users can focus on current awareness and can filter the information they receive by adding parameters that are incorporated into an algorithm that brings together relevant information that reflects the interests of individuals and groups.

These include legal-specific filters, such as legislation and regulation, but also legal terminology. Interestingly, many US law firms are using this tool to produce competitive intelligence reports that bring together information about what their peers are doing in particular sectors, ie their press releases, the clients they represent, the cases they take on and win/lose, the publications and blogs they produce and contribute to, and even the events they organise and attend. The system is also suggestive – highlighting trending topics related to users’ interests.

Understanding clients

By combining internal information resources with external data, including sector analysis and social media analysis, law firms are identifying meaningful correlations to help them align their advice more closely to their clients’ business, enhancing their service lines as well as developing new offerings that bring in work.

Stuart Walters, CIO at Taylor Wessing, does not accept the generalisation that law firms do not have big data; Taylor Wessing has 130 million e-mails in its Mimecast archive. ‘We started using our e-mail archive as our big data repository and the Mimecast platform for our analytics,’ he says. ‘We started by applying simple queries to extract a subset of the data and then using Excel to do basic analytics around referrals between different parts of the Taylor Wessing network. For example, we used keywords to extract the e-mails during a particular timescale.’

Walters and his team are looking at data analytics in the context of the firm’s profitability – querying the e-mail archive to discover whether, for example, profitable matters have more or less e-mail traffic and fewer conversations than less profitable matters.

The same principle also applies to business development. ‘The idea is to identify our strongest client relationships and inform pitches, so that before pitching to a new client, we can query our e-mail records to find out whether anyone from our firm has previous experience with our prospective client. So we get business intelligence and business development information out of data that we hold in a place and a format that is easy to access and analyse.’

Daniel Pollick, director of business infrastructure and CIO at DLA Piper, is also focusing on e-mail. ‘You can learn a lot from e-mail data and we have found analysing e-mails more successful than analysing documents to work out how matters progress,’ he says. ‘E-mail is dynamic and also more structured as e-mails include from, to, date and subject fields. We use InterAction in combination with Exchange to analyse communication. The value in this is understanding who we know, how we know them and what the networks of connections are. We use it for CRM – to discover how to leverage relationships.’

DLA has some 70,000 client records, many of which are interrelated. ‘We look at industry data – such as Bureau van Dijk – about client organisations alongside client records in our finance system to learn the true extent of our client relationships,’ adds Pollick. ‘This represents a powerful CRM tool allowing us to understand which clients are more profitable and focus our efforts accordingly. It’s about taking a more holistic approach.’

However, he questions whether this counts as big data analysis. ‘It’s data analytics and whether the data concerned is big or less big is less important than what we’re learning from it,’ he adds.

In 2012, Eversheds was the first law firm to use social media analytics to advise clients in different sectors, introducing Samsung interactive touch tables for presentation and analysis. These Surface devices visualise the big data experience, mapping data and behavioural patterns in real time. This includes bringing together publicly available data sets that relate to the industry segments that involve and interest the firm’s clients with sentiment analysis – using social media data to visualise the geographical perceptions of a business or brand.

As Caris says, this enables the firm to leverage its existing clients and attract new ones. ‘For example, we are using big data analytics and sentiment analysis to help a high-profile celebrity promote and monetise his online presence and YouTube channel. We are applying big data algorithms and technology to the principles of online reputation management.

‘We originally started using it for online reputation management and brand protection. Now it has evolved into online brand promotion,’ he adds. ‘We also use it as an early warning system – to detect when one of our clients’ brands might fall victim to negative sentiment and make sure they are properly prepared to deal with this – in the same way as T-Mobile was clearly prepared to deal with the negative tweets following a recent outage.’

Eversheds is also developing an algorithm to predict positive sentiment – if a client is starting an ad campaign, is it possible to predict which of the ads will go viral and when social media activity might generate business activity – for example, how soon will a dress sell out after someone famous is seen wearing it? New product lines in social media monitoring are continuing to attract corporate clients too.

Taylor Wessing carries out sentiment analysis for luxury brand clients using the Salesforce social analytics product Radian6 to set up queries to identify negative social media sentiment that may require action. ‘Sentiment is about analysing the content to find positive and negative trends,’ explains Walters. ‘It can be hit and miss, but so is big data. We have to accept that it is about identifying influencers and this is becoming more important as businesses sharpen their focus on social media.’

Although this application of big data is more prevalent in the US (see ‘Tailor made? Legal big data products in the UK’), the UK is starting to catch on with legal-specific US data software vendor Manzama, which established a UK presence in September 2013, already working with some large UK advisers.

In the US, big data analytics are used in litigation to underpin decision-making, with several products combining publicly available sources, including court records, to predict litigation outcomes. The most successful types of cases for these techniques are those with a degree of specialism, and insurance – including medical negligence – and patent litigation are leading the way. Lex Machina deploys legal analytics to support IP transactions and litigation, analysing court records and other publicly available information in order to predict the likelihood of winning a case. They plot patterns of success in a similar way to Taylor Wessing’s profitability analysis, so if the factors suggest that litigation would be risky, it might make more sense to advise the client to settle.

LexisNexis offers a range of similar litigation products focusing on smaller and mid-market US firms. Some are standalone and relate to particular practice areas, such as MedMal Navigator for medical negligence. LexisNexis applies a similar approach to fees and billing. As Marty Kilmer, vice president of product platforms, says, a recent release, Counsel Benchmarking, draws benchmarking data on firm rates from its matter management solution CounselLink to inform litigation strategy. However, there are no current plans to extend these products to the UK market.

Bradford & Barthel in San Diego was among the first law firms to go public about using big data. As well as using a social-media style client interface to share case and billing information in real time, the firm’s spin-off consultancy, Spherical Models, leverages client and case information to predict the probability of case outcomes. This speeds up decision-making and shortens the litigation process.

Although this has not taken off to the same extent in the UK, it could potentially change the way litigation is handled with big data combined with process automation, creating new approaches to dispute resolution. In terms of litigation outcomes, Weightmans’ Whittle says this could be done without big data analytics, and he has a point – in 2005 he wrote about applying decision-tree analysis to professional indemnity claims.

Skilling up

Do lawyers have the right skills to transform their firms into data-driven organisations? Daniel Martin Katz, associate professor of law at Michigan State University and other academics currently offer courses in computational legal studies. Lawyers have also realised that they need to work with other specialists. In e-discovery, Stretton refers to early case assessment teams that include litigators and technologists working with the client to work out the best approach. At BLP, Day has assembled a cross-business group to consider the firm’s approach to big data. The firm already leverages its internal information, using QlikView to create client and management data visualisation dashboards.

The challenges are less about managing data volumes – every business has to deal with this – than risk management, including data protection, privacy and security. According to Wragges’ Southall, a game-changing concept such as big data cannot simply be left to IT functions. ‘Technologists can help to change the future but this will also require firm-wide engagement and perhaps a new breed of expert,’ he says. Consequently, more firms are recruiting statisticians and data analysts.

In today’s digital economy, data integrity is a critical success factor. ‘In a law firm, people will always be important, but firms need to appreciate the increasing value of their internal data and other available datasets,’ observes Southall. ‘The reliability of any firm’s data collection process will also become business critical. Any inadequate processes will quickly give rise to poor decision making and a lack of competitive capability. Firms with poor data integrity processes may simply fail.’

Although big data is one of this year’s hot topics, the concept of integrating data analysis into legal services has been around since at least 1897, when Oliver Wendell Holmes Jr wrote in The Path of the Law: ‘For the rational study of the law, the black-letter man may be the man of the present, but the man of the future is the man of statistics and the master of economics.’

It has taken over 100 years for this prediction to become reality. LB