April 8, 2023
How legal data can supercharge your work as a lawyer
As an assistant attorney, I saw data as mere facts, but now technology lets lawyers harness it to streamline workflows, reduce unbillable hours, and enhance client value and efficiency without needing full-scale AI.

During my time as an assistant attorney, I rarely thought about the sheer amount of data I processed to provide a legal conclusion. No, I am not talking about personal data, nor is this another piece about GDPR or Schremms II (note: it is entirely possible and probably unavoidable that personal data is part of the aforementioned data, but I digress).

However, I viewed everything as facts, part of the legal dogmatic theory I applied to get a result rather than processable data. The same method I learned at the university. Looking back, it seems a bit laughable since I literally wrote a master thesis on the topic of data (and taxation), but it also clearly illustrates the gap between the industries.

Perhaps the issue is trust; after all, how can a computer process data in a manner that makes me certain that nothing important is overlooked?

But that highlights an important and – in my opinion – very interesting situation. It seems that lawyers look at legal tech solutions in an absolute way: either we imagine document automation, or we imagine a full-scale AI lawyer.

But there is a happy medium:

As a lawyer, you can use technology to supercharge the data that you already possess and use in your daily work.

Teaser: one firm that we worked with has removed up to 15 hours of unbillable work per week with data analysis and digital legal processes.

Wait, what data?

Usually, when talking about data, we think about some form of quantitative information. For example, sales numbers, hours billed, etc. would be great examples of such measurable information that – when broken further down – can be used to leverage increased profits, etc.

However, data is not only quantitative; it could also be any qualitative data – or any data no matter the form. Many also define data as digital information, but I would argue that any information is data IF it can be converted to a digital form, and that would be any information with today’s computer power. A doctor’s notes from 1990 to 1999 must be considered data, albeit in a very raw unprocessed form.

As an extension, legal data is any of the above data when it relates to legal ops or is used for legal ops.

This could be:

(a)  client data;

(b) data from or about the case, e.g., the facts of the case;

(c)  data about data (“metadata”); and

(d) data created from other data (which I will, for the purposes of this article and for lack of better, call “output data”).

In the above, letters c) and d) are the most overlooked in the legal field, but it doesn’t make them less valuable. While they require a little bit of thought and work to incorporate into the legal ops value chain, it is not far from how other industries utilize data already.

Metadata is data about data. For example, the title of the Word document can be considered metadata. For example: “CN35-20430 Sales Purchase Agreement (Law Firm Name DRAFT 21 July 2022).docx” provides both parties with more information about the file. This data could be split into:

What: Sales Purchase Agreement

Case:  CN35-20430

Who:  Law Firm Name

Status: Draft

Date:  21 July 2022

If you look closer at the file metadata, it often shows the author, edit history, and other data that the software has saved to the file (albeit many law firms delete such information with specialized software before sharing the file with other stakeholders).

There are many more examples of metadata. In many digital photos, for example, there are “hidden” data about which camera type took the photo, where the photo was taken, and with which settings – sometimes even the photographer who took it!

Output data is data or information that is produced by the processing of other data.

Example A: A clause commonly used in your contracts is suddenly being red-flagged more often. While the wording of the counterparty suggestions varies, the purposes and reasons stated are all similar. This data could be extracted or saved to a knowledge bank with one single click via software and by (1) applying natural language processing models (machine learning), and (2) comparing the results to client and case data, it would be possible to understand the trends better and, thus, predict and mitigate risks.

Example B: Before starting litigation processes, the lawyer has compiled and analyzed verdicts and court orders from the specific jurisdiction. The analysis shows that the court in the jurisdiction tends to favour certain arguments. As such, the lawyer can prepare the case better.

Of course, a great and talented lawyer can see some of these trends just by working with them, but the power lies in numbers and computers – even in jurisdictions based on civil law. In this case, the purpose of the software is not to replace any work, but simply to highlight certain factors for you to review – which should be the point of advisory-focused legal tech. The possibilities are endless, and it is becoming more popular. We have already spoken to several law firms of all sizes that are now starting to incorporate such data analysis.

To be usable, data must meet certain criteria: (1) the data must meet a specific level of quality (“quality threshold”); (2) there should be enough data to perform the specific purpose (“quantity threshold”); and (3) the data must be usable for the specific purpose.

It would be possible to write a myriad of articles about this topic, especially from a legal point of view, and there are many more (sub)characteristics/criteria.

Metadata is especially usable in workflows, hereunder building automatic processes that can give you more time. For example, imagine if your email software could automatically sort emails, documentation, etc. into specific folders and present it to you when you need it. That is possible by utilizing metadata.

Output data is especially usable for the analysis and production side of legal ops, i.e. the work that you do on a daily basis.

But it is the combination of the two that can supercharge your workflow and give you more time to provide client value.

“But it is probably expensive. Or difficult to implement. Or both!”

With today’s technology, it is not. A lot of possibilities are already “baked into” your existing solutions – they are just not being utilized yet – and many smaller software vendors are already coming to market.

In reality, the legal tech transformation is somewhat comparable to the Internet’s transition from Web 1.0 to Web 3.0 – from one-way communication to understanding data with a “human-like” approach. One could argue that the legal industries are a little bit behind: we have only now started to shift from a single-lane approach to embracing client-facing tech services, like client portals, etc.

The process was also slow for the financial sectors, however, fintech has now completely disrupted the financial sectors. From only-digital banking to open and international data APIs, technology has come to stay – and it all starts and ends with data.

When you start thinking about data, envision what knowledge you would like to have.

You already have most of the tools to build robotic process automation (“RPA”) or simple data analysis workflows.

You already have the data.

It doesn’t have to be a full-scale AI lawyer - and if you’re in doubt, you can always reach out. I would be happy to personally give some input or tools for you to get started.

Not only could it make your work more fun and give you time to focus on more important stuff, but there’s also always the financial upside.