Recently I watched a Ted Talk from Erik Brynjolfsson: The Key to Growth? Race with the Machines. Although it was a broad discussion on the history of the growth in technology and machine learning, it hit a point that is relevant to the issues that we face in the legal industry. Data volumes in any given organization continue to grow at an exponential rate and likely will continue to do so past our lifetimes. The impact of this growth is crippling efforts to find relevant data by deploying the archaic linear mindset/model to approach the review.
We have TAR and variations of analytics that help address and organize the data for review, but we are still reviewing in case-by-case silos rather than using methodologies that utilize the technologies, which can leverage the collective intellectual energy spent on all case by any given organization. Some corporations are addressing all of their matters by working with technology to deploy better strategies, but they are currently few and far between.
Current Industry Standards
Without a doubt, we work in an industry with brilliant people, technology and processes. The arguably unintended disconnection between legal departments and legal service providers creates walls that at times partition these brilliant people from each other. This is a challenge that seems to perpetuate the case-by-case reactive mode in which the discovery machine creates. Let me illustrate what I mean by quickly looking at a general litigation lifecycle.
The Exponential Equation
As Brynjolfsson mentioned in his talk, the Big Data growth trajectory creates a surprise to our industry and we are scrambling to solve it. Data will continue to grow at an exponential rate (N x N x N) instead of incrementally (N + 1 + 1). Our current mindset perpetuates a pushback from using technology to solve growing legal discovery data while preserving the business model of attorney review hours. I believe this is why the discussion around AFA in corporate RFP’s is starting to really have traction amongst the tier 1 law firms.
The size of data is growing per matter across the board, but a general trend still seems settling early because of the cost of review, eDiscovery and/or analytics for smarter review. This is bad for all business lines, but can be normal in many cases involving a lower economic claim compared to the expense of litigating. Ralph Losey expands on this issue and it makes sense to conclude that there can be strategies that involve discovery in a way that allows the use of technology to make nearly all cases involving ESI. This allows corporations to discover, defend and make decisions to settle or litigate on the merits of the case rather than economics.
Additionally, it should be fair to argue if the strategy from the defending corporation was to leverage collective case intelligence through the aggregation of all cases for a federated search across all matters. This is a growing trend where corporations prone to regular defensive litigation could settle or litigate based off of their empirical case decisions. This is only possible if they are collecting most all data across custodians and leveraging analytics to cluster the concepts rather than key word filtering before review.