Adoption of Contract Analytics All Comes Down to Trust
As part of the Legalweek 2020 Q&A series, Legaltech News speaks with Eric Falkenberry, partner at DLA Piper, on the opportunity for lawyers to become part of development teams, standardization in contract APIs, and more.
January 28, 2020 at 07:00 AM
3 minute read
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Contract-centric artificial intelligence and analytics platforms are all the rage these days, but it takes more than throwing technology at a problem to solve it. To truly leverage technology in a new school transactions practice, it takes one of the most old school legal disciplines: transparency.
As part of the run-up to Legalweek 2020, Legaltech News is chatting with a number of speakers from this year's sessions to know. Today's Q&A is with Eric Falkenberry, a partner at DLA Piper. His Legaltech session "Moneyballing with a Killer Contract Analytics Department" will take place on Wednesday, February 5, at 3 p.m.
Legaltech News: What do you think legal tech looks like in 10 years? What will be the biggest opportunities and challenges?
Eric Falkenberry: Rather than focusing on products which seem likely to appeal to the broadest range of customers, legal tech developers (data scientists and computer engineers) will work more closely with subject matter experts (experienced lawyers) to build and test tools which are tailored to particular legal tasks and produce demonstrable increases in efficiency and quality.
This will create a huge opportunity for lawyers to become integral parts of development teams, with the greatest challenge being whether enough experienced lawyers will choose to take time away from busy practices to provide expertise. With large concentrations of SMEs, law firms which invest in technology are particularly well positioned to take advantage of this evolution.
What are the biggest barriers to legal teams to leverage contract analytics?
One of the biggest barriers to the adoption of analytics is trust in their accuracy. Machines are classifying and aggregating huge amounts of data which form the basis of the analytics, and a lack of understanding regarding the manner in which the machines are performing such tasks leads to skepticism.
Legal tech developers need to be transparent about explaining how the sausage is made and what limitations exist, and legal teams need to take the time to ask questions and understand the technologies analyzing the data so that they can determine which analytics should be relied upon, and to what extent.
Is there standardization in terms of the core KPIs used to assess contract performance industry?
KPI standardization for contract performance was slow to develop before things like machine learning and natural language processing enabled companies to analyze and draw analytics from sufficient amounts of contract data to determine which indicators have the greatest predictive power.
What is the biggest misconception you think still persists about legal technology?
That robots will put most lawyers out of work. Technology will make, and has already made, certain legal jobs obsolete, but it is also creating a number of jobs which focus on legal data, analytics and automation. Lawyers which pivot toward technology will find themselves in demand.
What do you hope attendees take away from your Legalweek session?
I hope attendees will not only learn about the various analytics that can be drawn from contracts and how they can form the basis of actionable intelligence, but will also leave with a better understanding of the particular technologies which produce the analytics, something that is critical to widespread adoption.
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