The Successful Collaboration of Intuit’s In-House Legal Team and Data Scientists

"Data Represented in an Interactive 3D Form", Image by Idaho National Laboratory

“Data Represented in an Interactive 3D Form”, Image by Idaho National Laboratory

Intuit’s in-house legal team has recently undertaken a significant and successful collaborative effort with the company’s data scientists. While this initiative got off to an uneasy start, this joining (and perhaps somewhat of a joinder, too), of two seemingly disparate departments has gone on to produce some very positive results.

Bill Loconzolo, the Intuit’s VP of Data Engineering and Analytics, and Laura Fennel, the Chief Counsel and Head of the Legal, Data, Compliance and Policy, tell this instructive story and provide four highly valuable object lessons in an article entitled Data Scientists and Lawyers: A Marriage Made in Silicon Valley, posted on July 2, 2015 on VentureBeat.com. I will sum up, annotate, and pose a few questions of my own requiring neither a law degree nor advanced R programming skills to be considered.

Mr. Loconzolo and Ms. Fennel initially recognized there might be differences between their company’s data scientists and the in-house Legal Department because the former are dedicated to innovation with “sensitive customer data”, while the latter are largely risk averse. Nonetheless, when these fundamentally different mindsets were placed into a situation where they were “forced to collaborate”, this enabled the potential for both groups to grow.¹

Under the best of circumstances, they sought to assemble “dynamic teams that drive results” that they could not have achieved on their own. They proceeded to do this in the expectation that the results would generate “a much smarter use of big data”. This turned out to be remarkably true for the company.

Currently, the Data Engineering and Analytics group reports to the Legal Department. At first, the data group wanted to move quickly in order to leverage the company’s data from a base of 50 million customers. At the same time, the Legal Department was concerned because of this data’s high sensitivity and potential for damage through possible “mistake or misuse”. ² Both groups wanted to reconcile this situation where the data could be put to its most productive uses while simultaneously ensuring that it would be adequately protected.

Despite outside skepticism, this new arrangement eventually succeeded and the two teams “grew together to become one”. The four key lessons that Mr. Loconzolo and Ms. Fennel learned and share in their article for teaming up corporate “odd couples” include:

  • “Shared Outcome”:  A shared vision of success held both groups together. As well, a series of Data Stewardship Principles were written for both groups to abide. Chief among them was that the data belonged to the customers.
  • “Shared Accountability”:  The entire integrated team, Legal plus Data, were jointly and equally responsible for their outcomes, including successes and failures, of their work. This resulted in “barriers” being removed and “conflict” being transformed into “teamwork”.
  • “Healthy Tension Builds Trust”: While both groups did not always agree, trust between them was established so that all perspectives “could be heard” and goals were common to everyone.
  • “A Learning Curve”: Both groups have learned much from each other that has improved their work. The legal team is now using the data team’s “rapid experimentation innovation techniques” while the data team has accepted “a more rigorous partnership mindset” regarding continually learning from others.

The authors believe that bringing together such different groups can be made to work and, once established, “the possibilities are endless”.

I say bravo to both of them for succeeding in their efforts, and generously and eloquently sharing their wisdom and insights online.

My own questions are as follows:

  • What are the differences in lawyers’ concerns and the data scientists’ concerns about the distinctions between correlation and causation in their conclusions and actions? (Similar issues have been previously raised in these six Subway Fold posts.)
  • Is the Legal Department collecting and analyzing its own operation big data? If so, for what overall purposes? Are the data scientists correspondingly seeing new points of view, analytical methods and insights that are possibly helpful to their own projects?
  • What metrics and benchmarks are used by each department jointly and separately to evaluate the successes and failures of their collaboration with each other? Similarly, what, if any, considerations of their collaboration are used in the annual employee review process?

1.  Big data in law practice has been covered from a variety of perspectives in many of the 20 previous Subway Fold posts in the Law Practice and Legal Education category.)

2.  For the very latest comprehensive report on data collection and consumers, see Americans’ Views About Data Collection and Security, by Mary Madden and Lee Rainie, published May 20, 2015, by the Pew Research Center for Internet Science and Tech.

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