UniCourt Influencer Q&A with Lisa Mayo of Ballard Spahr LLP

on Topics: Future Law | Influencer Q&A | Legal Tech

UniCourt Influencer Q&A with Lisa Mayo of Ballard Spahr LLP

A “lifelong, adaptive learner” with a computer programming and database development background, and over 20 years of experience as a legal technology manager at a large AmLaw 100 firm, Lisa Mayo has seen first hand the growing impact legal tech and data management have had on law firms.

Lisa has a front row seat to the changes taking place in the legal industry in her role at Ballard Spahr LLP as the Director of Data and Analytics, and we were fortunate to sit down with her, learn more about her career, and get her insights on the future of data analytics and business intelligence for law firms.

We hope you enjoy learning from Lisa’s perspective as much as we did!

UniCourt: Tell us your story. What is your background, and what led you to what you are doing now?

Lisa Mayo: My background is very different. My LinkedIn profile refers to me as a “lifelong, adaptive learner.” What that means is that I am mainly self-taught and this preference started at an early age when I skipped a grade and had to learn 4th grade reading and math over one summer. My family also moved often in my formative years, which resulted in new schools where I would have to tell the teacher “I used this book last year,” so I was often on my own when it came to learning in those early years. Following high school I spent a couple of years performing volunteer community service work, and I opted for an Associate’s degree first in Computer Operations and then later in computer programming (COBOL and Assembler language). Upon graduation, the school hired me as their Computer Operator. I was promoted to teach DOS Operations, and finally became a COBOL Instructor where I quickly tired of grading 30 portfolios at one time.

As a voracious reader with an appetite for independent learning and putting new concepts into practice, I have had several roles at Ballard where I have worked for the past 33 years. My first major role involved converting the firm’s mainframe systems from COBOL to a client/server model. From there, I moved into database administration and development, and eventually the firm promoted me to Director of Firm Applications, where I led a department that developed and maintained web applications. 

Because I handled the integrations for many of our core systems, I was directly involved in firm mergers as they related to incorporating multiple systems into our environment, and in recent years I transitioned to focus solely on data and analytics. I have been in a legal technology management role for over 20 years, and enjoy leading the efforts to develop new data tools for our clients, partners, and firm management so that each has the insights and analysis they need to make strategic decisions.  

For the past few years, I have been a member of the Client Value and Innovation (CVI) department where we create bespoke solutions in partnership with our clients and with strategic practices at the firm. 

At present, I am also enrolled in a Wharton executive program for advanced analytics. In short, I have never been bored because I have never stopped learning!

UC: Over your career at Ballard Spahr LLP, you’ve held a range of positions from Programmer/Analyst to SQL Database Administrator, Financial Applications Manager, Director of Firm Applications, and now Director of Data and Analytics. From your experience on the tech and data side of large law firms, what do you see as some of the most important aspects of a successful data management program?

LM: It certainly helps to have institutional knowledge of past and present enterprise systems. I like to say, “I know where all the bodies are buried,” simply from being at the firm for so long. A successful data management program takes a lot of planning. We started with a weeklong data workshop, where we identified what data we wanted to manage initially. We started simple with financials around clients, matters, and people. We then mapped out the attributes we wanted to capture for each entity, and established systems of record for each data element. It’s also important to enlist other data stewards in your organization especially when they live in departments other than IS (or in our case CVI). Finally, we identified the additional tools and resources we would need and by the end of the week, we had a room filled with papered walls, and more importantly, we had a plan.

Another thing I would recommend is benchmarking your organization’s data maturity. Be honest. Many firms are at “Level One” where they are using reports and dashboards to look at what has already happened. Establishing your starting point will allow you to measure your growth going forward. Create a three to five year roadmap to data maturity (evidenced by automated decision-making and deep data analyses), and socialize those goals.

Think about the barriers that may be standing in the way of those objectives. It could be a lack of staffing, funding, skills development, or more. Once you identify those obstacles, create plans to remediate. We were able to get project approval and our program really took off when we branded it as a “Firm-wide Data Literacy” initiative. Brand your program with what resonates most with firm management and allows you to garner executive support.

Once you have core enterprise data, ask “what else?” There are a variety of third-party data resources available, which will supplement your internal data. With that extraneous data, you can really begin to build out capabilities such as predictive (“What will happen?”) and prescriptive analysis (“How can I make it happen?”), in addition to creating artificial intelligence and machine learning models that merge structured and unstructured data from disparate sources.

Leverage your vendor relationships. We enlisted Microsoft’s help to ensure we handled our confidential and private data using best practices for data masking and encryption. Finally, don’t forget about data governance to ensure your data is timely, accurate, relevant, complete, and secure.

The data management journey never ends, and a successful program should always be evolving.

UC: What are citizen data scientists? How can law firms identify, cultivate, and support their own citizen data scientists?

LM: Gartner defines citizen data scientist as “A business user capable of combining his or her expertise with the principles of Data Science, without a deep knowledge in mathematics or statistics.” At our firm, we have identified several citizen data scientists in our legal and administrative departments. As the definition implies, these business and legal professionals usually want the raw data so that they can perform some sort of self-led data exploration.

We give our citizen data scientists additional training and each becomes the resident data expert in their group. This helps to ensure each group has the data they need at their fingertips, which further advances data literacy.

UC: You recently presented at ILTACON 2022 on a panel titled “What Is a Data Scientist and How Firms are Using Them.” What are some of the key takeaways from your presentation and the core benefits law firms can realize by developing a good data science program?

LM: Key takeaways are that you do not need to have pure Data Scientists on staff in order to branch into data science concepts and processes, at least not initially. Many BI tools such as Qlik Sense and Tableau have advanced tools for things such as Key Influencers and Root Cause Analysis. In addition to those features, Microsoft’s Power BI allows you to incorporate algorithms from Azure Cognitive Services along with capabilities such as Sentiment Analysis, Key Phrase Extraction, Language Detection, and Image Tagging.

Some additional takeaways:

  • Focus on solid financial data first 
  • Partner with the right people
  • Be patient
  • Grow Citizen Data Scientists
  • Incorporate external data points 
  • Embrace third-party data in the form of APIs and big data tools and techniques
  • Find executive sponsorship and additional champions

The benefits are innumerable as you see your hard work in action. The data you provide should inform and justify an organization’s actions. You will spot trends sooner than your competitors and you will know that your data literacy program is working when your firm begins to make data-driven decisions.

UC: Where do you see the future of data analytics and business intelligence heading for law firms? What roles do artificial intelligence and machine learning have to play in developing the next generation of analytics and intelligence? 

LM: Artificial intelligence and machine learning (AI/ML) will fuel innovation for the near future. I anticipate that use cases for automated decision-making will increase, along with natural language processing (NLP) which could include conversational AI, sentiment analysis, language translation, and more. Additionally, it will become routine to use AI for things like document and contract review, and we will see increased reliance on machine learning for its predictive and prescriptive capabilities. 

Graph technology is gaining momentum as well. It involves finding previously unknown relationships between data, and people. This technology could be useful in business development efforts along with client and employee retention efforts.

UC: What are some of your favorite sayings? What are some real-world examples of how you’ve seen those sayings come to life?

LM: My two favorites are from Maya Angelou: “Do the best you can until you know better. Then, when you know better, do better.” My life has been a journey of self-exploration and growth, both personally and professionally. This adage really resonates with me as a lifelong learner. 

Another one of Ms. Angelou’s quotes is equally impactful: “People will forget what you said, people will forget what you did, but people will never forget how you made them feel.” Again, whether in our homes or our workplace, be kind and show empathy, even when delivering unpleasant news. Empathy is a key factor in Design Thinking Methodology, which fuels many of our innovation efforts. We have to meet people where they are and understand their obstacles before we can offer creative solutions.

UC: What are your goals for the rest of 2022? What projects are you working on? Are there any events in the legal tech and legal innovation space we should know about?

LM: My goal for the remainder of 2022 is to get funding to move our Enterprise Data Warehouse into the cloud. That will be our entry into Azure machine learning for which we have developed a number of use cases. We have had several AI/ML engagements in recent years, working with our consulting partners. We want to be able to develop and gain agility with a variety of additional, self-led use cases.

Automation using low code or no-code solutions is also a focus as we look for inefficient, routine processes to automate so that staff can focus on higher value work, to the firm’s benefit.

Finally, we have been kicking around the idea of hosting a hackathon with other innovation and data teams at local firms. If anyone is interested in participating or planning for such an event, please contact me.

UC: Where can we learn more about you and your work?

LM: Follow me on LinkedIn (http://www.linkedin.com/in/lisammayo). I usually post about upcoming speaking engagements and/or new articles I have authored. Feel free to reach out to me and talk through your ideas. As with other professions, it is vital for data professionals to build internal and external networks and continue learning from one another. 

The Future of Law with AI and Data Analytics

As we’ve learned from Lisa Mayo, developing a successful data management and analytics program within a law firm requires building an environment grounded in empathy for the challenges and obstacles legal professionals face and actively encouraging a culture of adaptive learning and constant evolution.

We loved hearing from Lisa on the future of law with AI/ML, empathy in design, and developing the next generation of citizen data scientists, and we’re excited to see where her journey as a lifelong learner will take her next!