It is still true to say that many lawyers do not understand the value of analytics nor the value which an external consultant can bring to their use.

Xavier Diokno is Senior Director, Data Analytics at Consilio. In this interview, he explains some of the difficulties which stand in the way of a clear understanding of analytics, and explains how Consilio’s analytics team can help.

There is a growing awareness of the purposes and value of analytical tools which support and extend the lawyer input into document review.

Consilio increasingly meets lawyers who have been to a seminar or read an article and develop a fear of falling behind their rivals. Some have ideas of their own as to how analytics can improve their practice; some have merely heard some buzzwords and want to know what they mean; some are extremely well-educated on the subject. They come to Consilio looking for advice.

Consilio’s analytics team is consultative in nature. It includes lawyers with technical experience so that clients are not just dealing with an IT person but with someone who can empathise with their position. Sometimes, they may be looking for explanations which they can take back to their clients, the opposing party or the court.

Lawyers are risk-averse in nature, and they appreciate having someone to hold their hand in this area. Consilio’s experts are often asked “how many times has this been done?” They show what will happen if the clients were to choose this path or that; next time they will be prepared to use the tools.

There have been successful arguments for the use of technology-assisted review in courts of multiple jurisdictions and clients are less concerned about their case being the first one.
The new iterations of TAR are more interesting to clients than the earlier flavours. The process has become less complicated and you do not need to be a mathematician or statistician.

It becomes easier to understand technology-assisted review by reference to parallels like Pandora. In Pandora, the user selects something – a movie or a song – and the computer finds others like it. As the user gives more feedback, and the computer gets better at choosing things for them. It is the same with document review.

Modern iterations of technology-assisted review are not primarily for culling but for prioritising. It might be used, for example, to show the clients which documents have been left unreviewed when they have used some other means of review.

One important aspect is to show the clients what the system has done. Consilio produces a series of metrics which illustrate progress. They might, for example, show the rate at which reviewers are finding responsive documents. As the review continues, fewer responsive documents are found and it becomes possible to show that the costs of an exercise have become disproportionate to the value.

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