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1.   “Here There Be Dragons”

The world in the pre-maps era was a rather static one: people were born and died in the same place. Lacking any reliable data on the territories they were about to venture to, people could not properly plan the journey: they did not know the expedition’s duration, the supplies needed, and, most importantly, the dangers they would encounter on the road.

The only sensible solution for them was to hire navigators: people who had gone there before. Nevertheless, that meant the travellers were awfully reliant on the navigators’ subjective experience, where factual reality would be intertwined with personal wisdom and anecdotes. But the plural of anecdotes is not data[1].  Therefore, before maps were created, traveling was risky, expensive, and rare.

However, in time, these journeys started to be recorded, traded, and eventually displayed on paper. Essentially, people would start to aggregate these experiences into the early maps. This opened an entire field: cartography. Yet, old maps had their limits. The areas where information was scarce or lacked altogether were marked by cartographers with graphic imagery of giant snakes, dragons, or other fantastic beasts and were labeled with an extreme warning: “here there be monsters” or “here there be dragons.” That sealed the limit of human knowledge.

But, in time, cartography has improved, all due to better technology and increased capabilities. Granted, the two world wars in the 20th century sped up the process as accurate maps became strategic assets. Regardless, in the end, maps democratised traveling. All thanks to data gathering, processing, extrapolation, and analysis.

The world is becoming increasingly quantified. The legal industry is not immune to this tendency, but it is still lagging most other sectors. In our sector, like in many others, the intrinsic value within collected data is directly proportional to data volume, storage medium, and retrieving capacity. Law firms that fail to collect and peruse the right kind of data will lose major deals. Intrinsically, they will miss out on opportunities to improve the client experience, mitigate risk, and maximise their profits.

On the other side of the table, clients take data analysis seriously. Some progressive corporate legal teams have already created formal roles for legal data scientists and are even working with multidisciplinary teams to devise strategies and techniques aimed at harnessing value from data. Concurrently, law firms will find themselves in a dangerous position if they fail to invest in areas that are compatible with client interests and requirements.

So, either by strategy or force of gravity, law firms will eventually need some command in the data realm.

In this article, I will not so much focus on technicalities, but rather make a case for data analysis implementation at law firms’ level. Accordingly, I will analyse:

2.  Data Sciences and Essential Skills

By and large, data science implies using various analytical techniques to better comprehend, diagnose, forecast, and anticipate business outcomes. For the legal industry, data science is new and unexplored, but its importance has started to become clear for the stakeholders so much so that it has now become a hot topic. It was about time, though: many companies from all across the market spectrum collect data about their activities in an attempt to mark milestones and correct errors.

This increase in data analysis presupposes ample applied mathematics and statistics prowess.

Some top skills for data analysts include:

  • Structured Query Language (SQL)
  • Microsoft Excel
  • Critical Thinking
  • R or Python-Statistical Programming
  • Data Visualisation
  • Presentation Skills
  • Machine Learning

This does not mean that lawyers should automatically start to expand their skills portfolio, nor should it be a deterrent for the intrepid few. The legal data analysts can be either bred in-house or imported.


3.   “Lobster Law”

The legal industry is still a few steps behind many other critical trades that understood the edge given by data sciences. Why is that so? Here are a few reasons to consider:

  • Limited data collection efforts, which in turn led to failure in depicting the leverage created by this emerging field;
  • The limited number of lawyers with a quantitative/science background, which not only contributed to rigidity towards added value brought by data analysis but also influence data-driven training;
  • The legal industry is atomised which generates heterogeneity in how law firms (regardless of size) and legal departments organise their activity.

We all agree that the status quo is changing. But we don’t seem to concede as to how the change will be deployed.

Whether a corporate lawyer, a family lawyer, contract lawyer, or anything in between, you always face the same type of quantitative questions from your clients:

How much is my case worth? What are my chances of success? Is this clause a standard one? How much should I offer in a settlement? What are my chances of winning this litigation?

It’s all about pricing the risks.

Lacking a centralised database for their decisions, lawyers more often than not decide based on hunches, something a data analyst or a statistician would consider blasphemy.

But legal services based on hunches are expensive, tedious, and prone to mistakes. Lawyers are limited by their own expertise.

Ed Walters, CEO & Adjunct Professor of Law, Fastcase & Georgetown University, introduces a comparison to better understand how volatile in terms of variables legal industry really is.

Imagine, he says, that you go to a restaurant and order lobster. Only that, upon inquiring as to its price, you receive a very vague answer: the price depends on the day the lobster was caught, it depends on the tides and the waves, on the cost of fuel for the boat and for the truck for shipping the cargo to the restaurant, it depends on the natural gas for cooking the poor animal. But not to worry, says the waiter, you’ll get the price when we bring the check. Would you order lobster in these circumstances? Probably not. In fact, people might order something more expensive on the menu simply to avoid the risk of uncertainty. Why, then, paying for legal services that follow the same rationale: “it costs you x Euros times the hours required for completing the project”? True, nowadays, lawyers have moved to price-per-project and have generally repudiated hourly rates. Even so, the client oftentimes ends up paying more than initially agreed. Why? Because lacking centralised and perused data, lawyers could not price the risks from the very beginning.

Ironically, we lawyers try to help people navigate unexplored terrains with no maps, and no data analysis to back our decision, frequently basing our rationale on simple hunches and gut feelings. Thus, clients face this lobster-like risks. Legal services are risky, costly, and conjectural: that is why people opt for them as a last resort. They would try solving their problems otherwise and contact a legal professional when all other options become futile.

How can we overcome this impediment?

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One solution would be to map up the legal terrain by extracting and processing legal data so that it can answer to the practitioners’ requests. Each information in a legal document is a node. If analysed carefully, the examiner can decide the links between these nodes and, by extrapolation, determine graphs within the system. Using this data architecture, the practitioner can easily interpret, connect, infer, and conclude based on a piece of legislation, law court decision, authorities’ acts of any sort. This way, the professional and the client can transgress the limited, anecdotal experience of the lawyer. Although today data-driven questions are resolved based on personal, limited experience, in the future, these questions will receive data-backed answers.

And the first steps have already been taken. From FastCase to Lex Machina (of Lexis Nexis), even with Sintact Analytics in our CEE area, legal tech innovators understood that the future is data-driven law.

So, a law firm that says to its client: “from our experience and data, settlements just like this vary between x and y, with a median of z” will steal the spotlight and push old-school, anecdotal law firms into anonymity. That is why we should stop practicing lobster law and start practicing data-driven law. We should answer data questions with data answers.

Data analytics represents a map of legal matters. Unsurprisingly, though, maps can sometimes lie because they are representations of truth, yet not necessarily the truth. From Spanish-generated misconception that California was an island, to some (tragic) comic cases of people driving directly into lakes after their GPS misdirected them, we can see that applied data analytics is far from flawless. Traffic congestion avoidance apps that redirect all users towards the same detour prove that over-reliance on data analytics can lead to erroneous results. But that does not mean we should halt the effort altogether.

The legal industry is in a relatively early state. More and more law firm or corporate legal department leaders currently acknowledge the importance of optimum (and more thoughtful) data collection and analysis. The majority of these leaders also understand that focus in this area should expand beyond mere financial data and include the capture of new and relevant input about the practice of law itself.

Another solution to the “lobster dilemma” resides in systemic and process analytics. As for law firms, apart from a few pioneers, the vast majority are focused on modernising reporting. Or, in some cases, they have specific clients driving activity. But strategic, orderly investment has been limited. For instance, I haven’t managed to find a firm that systematically tracks results and settlement data for all its litigation work (if I omitted anyone, please reach out to me; happy to update this statement ?). And even if some are aiming for such solutions, they only collect and analyse the data at sub-practice or key account level. However, it is precisely this absent aftereffect tracking that is the cornerstone of future data efforts. Ultimately, law firms without outcome data are like sports teams that don’t keep score.”

Not everything is lost, though. The legal industry still has many realities to acknowledge and decisions to make to push itself forward. But concepts like “big data,” “data analysis,” “risk pricing,” and “predictive analytics” have begun to gain traction in legal professionals’ discourse. Most firms are still in the planning stage, but the industry seems to be going somewhere.  Although at a slow pace, the prospect for technology, human capital (including upskilling), and process evolution is encouraging.

Interacting with data and technology solutions requires a different set of communication skills. This might be uncomfortable for many. That is because, while lawyers talk in beautiful words, the rest of the world talks in charts and numbers. It will be up to specially-trained lawyers to build a bridge between the two worlds and turn words into data.

Legal data analysis should go from “nice to have” to “ready to run.” Legal data is such a powerful tool that it would be a waste of resources not to make the full use of it: from managing costs, to risk assessment, all the way through system, process, and working environment improvement.

Suggesting that data analysis skills be included in modern lawyers’ skills portfolio might seem surprising yet is in no way an exaggeration. But how important is it? What should it include? Can the implementation be done smoothly so that lawyers are not overburdened? In the end, what is the return on data-related investment?


4.   The Importance of Data Analytics for Law Firms & Legal Departments

Historically, legal data analytics has been used to determine external legal spending: to know which law firms are used, how much they are paid, and, probably, how long it takes for them to finish a task. As straightforward as it may seem, many large companies have difficulties expressing even this information. Splintering this data into spend by work types, business division, or type of results is even more strenuous. Casting transparency on the legal costs is a significant step toward controlling them, achieving lower rates, and redirecting work, when necessary.

Legal data analytics should take the analysis a step further so that the interested parties can measure a law firm’s costs against the value delivered. This analysis reveals how complex relations with law firms are since it’s not only the efficiency that matters but also their responsiveness and the confidence they pass on to their clients. This analysis has another significant advantage: it avoids false economy and sub-optimal legal results by deterring the clients from cutting costs without compensating the law firms that bring added value.

Although essential, tracking external legal costs is but one aspect of the work undertaken by a legal team. Data metrics have other use as well. In fact, in many corporate legal departments, up to 80% of the work does not involve external law firms. For this part, data analytics plays a major role in enhancing the visibility of progress and workload not only within the team but also for the decision-makers. Visual representations of the projects completed, the type of work, hours spent, and end results can just as well demonstrate to the board how much added value the legal department brings. Moreover, a quantification speech can streamline discussions about how work can be distributed, resourced, eliminated, or reshuffled so that the legal team’s work can better integrate with the business zeitgeist. This approach plays a vital role in enabling the role of lawyers and ensuring that they are valued adequately by both their internal and external clients.

Law firms and legal departments now have the necessary tools to ensure resource management and legal innovation. But knowing whichever of these instruments to adapt and, more importantly, in which manner is no simple task: you must start with understanding where bottlenecks, chasms, opportunities, and resources lay within the team and organisation. The data can provide the bedrock for informed decisions on the topics we analysed in our previous posts: metrics can yield valuable intelligence about work that can be commoditised, automated or outsourced, about resources that must be rerouted, about people that need reskilling or redirected to another role. Such changes move beyond simple cost savings and are sure to influence business growth.


5.     Conclusion

Before the maps, people traveled less: many were born, lived, and died in the same place. Travel was expensive, risky, and, therefore, rare. The legal industry today is in the exact same spot: our legal professionals don’t have maps, our clients are forced to rely on our anecdotal, subjective experiences as guides. But it doesn’t have to be that way, and surely the future will introduce structural changes in how legal services are provided. The only question is how the legal industry will react and implement the necessary reforms.

Data should no longer be a scarecrow to legal professionals out there. Ideally, collecting data should be straightforward, and data visualisation should be clear. A data-driven discussion brings forward topics such as return on technology investment, motivates a team to undertake changes, and overall brings success. Thus, data analytics should extend beyond cost control and cover information about the legal function as a whole. Ultimately, legal teams would be able to pivot their focus from “cost savings” to “value creation”.


[1] Frans de Waal, “Are We Smart Enough to Know How Smart Animals Are?”, W. W. Norton & Company; 1 edition (April 4, 2017), Chapter 2


This post is a part of the series called #FutureProofLegal in which we describe the skills and roles/jobs that future legal professionals (lawyers and beyond) shall acquire. To learn more or read other articles in the series go to our #FutureProofLegal page

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