There is a lot of chatter these days around the increasing use of data to inform and drive business decisions within law firms. To that, I say, Amen.
But the ability to effectively analyze data and put it to good use is directly related to the quantity and quality of the data being analyzed. Lawyers will stare awestruck at a colorful stacked bar chart, but the smiles quickly turn to frowns when they realize that the data being depicted is just dead wrong.
Law firms grappling with how to capture better data should consider hiring a data quality specialist. These individuals can own the processes for gathering, organizing, and cultivating quality data, which allows others in the firm, such as analysts or data scientists, to create accurate reports. Although data quality is often viewed as a less interesting topic than data analysis and visualization, it is a critically important area to tackle for law firms looking to build a more data-driven culture. In fact, you can’t have effective analytics without quality business data.
Capturing and organizing quality data is a tricky endeavor, however. The continued evolution of artificial intelligence (AI) and machine learning is an important piece of the puzzle. We are already seeing impressive advances in the litigation space where technology tools are extracting rich data points from public records and other documents. The advancements to date look to be just the tip of the iceberg, but we are still a long way from a world where machines instantaneously extract quality data and organize it into neat tables that are ready for analysis.
Human coding is still how most law firms build core client and matter data sets. For example, classifying matters is the primary way law firms go about understanding the types of work they handle. Questions like, “How many IP litigation matters have we handled in the Eastern District of Texas?” or “How much do real estate joint ventures typically cost?” are asked daily. Most firms gather matter classification data through an intake process during which legal assistants enter information about the new matter. This process includes choosing a code indicating the type of work being performed. Unfortunately, many law firms do very little beyond intake to gather additional data points (i.e., case outcomes, deal size, etc.).
Some firms have invested in more robust processes and technology designed to capture additional matter meta-data well after matter opening. Many of these processes involve workflows that ask members of matter teams (often junior lawyers or paralegals) to provide information based on pre-defined triggers or at the conclusion of a matter.
With human coding comes challenges with quality and consistency, of course. When dozens (if not hundreds) of people are selecting codes, quality and consistency often suffer. Moreover, when those making selections are not properly trained or do not have the skills and experience required to make accurate selections, the issues are compounded. Add to all of that the struggle with incentivizing people to take the time to make a proper selection, and you have a situation fraught with potential error.
The simplest example of this dynamic is a file opening. An attorney wants a new matter opened as soon as possible, but does not provide his or her legal assistant with proper guidance on selecting a matter type. The legal assistant is left with the choice of delaying opening and pushing the attorney for more information, or just taking a best guess at a code and getting the matter opened. Let’s face it: the latter is usually a far more attractive option.
In the world described above, law firms are spending a lot of time on training, re-coding inaccurate data, and finding ways to incentivize lawyers to put more care and diligence into the coding process. In a word, it’s a slog.
Enter the Data Quality Specialist
At a high level, the data quality specialist’s role is to ensure that the firm is capturing quality, relevant data, and that the data is ready for use. This responsibility is distinct from data analyst roles which typically focus on using data to produce outputs that help inform and drive business decisions. The data quality specialist is all about giving those downstream users the clean, rich data they need to be successful in their own roles. Put another way, the data quality specialist becomes the data analyst’s new best friend.
The exact role will vary from firm to firm, but core responsibilities of a data quality specialist might include:
1. Classification and Code Selection — Instead of just reviewing selections made by others, the data quality specialist role could take the lead in data creation in targeted areas. For example, take client and matter classification codes obtained during matter opening — one path would be to encourage robust matter descriptions from attorneys and have the data quality specialist select the matter classification after the file opening based on the matter description. This process would: i) speed up matter opening; ii) reduce the information requested on the opening form; and iii) ensure consistent and accurate coding. The extent of the data quality specialist’s role in actual code selection would depend on several factors, including the size of the firm and the specific data points being captured.
2. Drive Quality — As part of this role, periodic quality control reviews would be done to identify any missing or inaccurate information and resolve any inconsistencies. Part of the quality review would involve working with key stakeholders that use the data, such as practice area or industry leaders, in order to best confirm accuracy.
3. Help Develop Processes for New Data Capture — This task involves the data quality specialist working closely with the business operations professionals (and potentially, the attorneys) who are analyzing the data. These people might include pricing and business development professionals, practice managers, or financial analysts. These stakeholders would confirm whether the right data is being captured and could identify new data to capture based on business needs. The data quality specialist would then drive developing processes for gathering the new data.
4. Data Taxonomies and Data Structure — The data quality specialist would work collaboratively with IT to ensure captured data is structured properly to allow for easy extraction and use by end-users. Initiatives to standardize classification taxonomies, like work done by the Standards Advancement for the Legal Industry (SALI) Alliance, are a big step in the right direction and provide a great roadmap for defining fields, setting the broader data taxonomy, and potentially even building a data dictionary.
5. Automation of Data Capture — As key data points are being identified, the data quality specialist would assess opportunities to automate data capture. For example, can a client’s industry be fed directly into a data table from another third-party source? Can technology read a matter description and select a classification?
6. Report Creation — This role might have the data quality specialist also work on developing reporting of the data to help ensure that the correct data is being captured and to help identify any gaps in the data as well as any potential data enrichment opportunities.
How Do I Find a Data Quality Specialist?
Data quality specialists are not a staple, stand-alone role at law firms, and there is room for healthy debate on the skills and experience that would drive success in this role.
In addition to being detail-oriented and facile with data, successful candidates will have strong interpersonal skills and the ability to work collaboratively with attorneys and business operations professionals from across the firm. Like with many other growing legal operations roles, change management would be part of the data quality specialist’s role, so being able to motivate people and drive change also will be a key component of success.
On one hand, experience working with data, defining data structures, and the more technical aspects of the role would be beneficial; on the other hand, experience working with lawyers and having a baseline understanding of legal work would also be extremely beneficial. The skills that are most important will depend on the particular circumstances and culture of the law firm, what other roles already exist within the firm, and the specific areas of responsibility for the new role.
There will not be a single formula that will guarantee success in bringing on a data quality specialist, but ignoring gaps in this critical function will guarantee headaches for law firms looking to extract real meaning from their rich data.