New Frontiers in Data Analytics

Data analytics has been hot in large law firms for several years. Much of the activity has been focused on improving law firm business, for example, better budgeting and pricing. Can we use data analytics to improve the advice we give to clients? To reduce the risk of malpractice? We will examine new data analytic frontiers with three short case studies. Case studies will include uses of firm, client, third-party, and public case law data that drive better outcomes and surprising insights.

These are my notes from the Strategic Knowledge & Innovation Legal Leaders’ Summit (SKILLS 2021), a private gathering of large law firms. As with all live-blogging, there will be inevitable errors so please excuse them. My editorial comments are noted in brackets.

Three Types of Data

There are three key types of data: firm data, client data, and third-party data.

• Firm data enables operational efficiency.
• Client data combined with firm data provides matter intelligence.
• Firm data combined with third-party data provides environmental intelligence (i.e., how we conduct our business and benchmark it against various industry sectors).
• Client data combined with third-party data provides tactical insight and enables client service enhancements.

Critical First Steps

• Win hearts and minds within your firm to gain a commitment to data cleansing. This requires committed investment and focus. You will not obtain useful insights unless the data is usable.
• There will always be tactical pursuits and quick wins for data analytics. But make sure they are aligned with your long-term vision for data analytics in the firm.
• Use the PPDAC Framework:
  • Problem
  • Plan
  • Data
  • Analysis
  • Conclusion

Recommended Data Practices

• Don’t rush to data analytics. Start with data mining. Then build your data models.
• Model explainability is key. Use a combination of text and excellent visuals to make your models more comprehensible to decision makers.
• Data Trends to Watch
  • Natural language processing (e.g., text processing, text generation, Legal BERT)
  • Differential privacy — more effective than anonymization for masking identifying data. It works by “adding noise” to the data, thereby obscuring the critical data.
  • Client delivery

Learnings from Case Studies

• Data analytics allow more sophisticated matter pricing and budgeting.
• Data analytics can drive legal strategy — what patterns emerge across matters? How do these patterns inform business choices and client choices? (Clients now expect to be able to get this kind of data from their law firms.)
• Predictive analytics / machine learning: Some examples are using advanced machine learning algorithms to tackle complicated business problems; using statistical analysis to identify impacted groups; doing predictive pay analysis for groups that have experienced discrimination.
• Using data to manage the workplace: this allows clients to mitigate risk in their own workplace. This could involve combining legislative updates with focused analysis of the client’s own data.
• Create tools that help clients identify trends that are critical to their business and workplace.

[Photo Credit: Franki Chamaki]