e-discovery 2.0

I spend a lot of time researching and developing new search functionality, and working with enterprises and law firms to use this functionality to improve their e-discovery outcomes. To this end, I have followed the excellent research performed as part of the TREC legal track. I also recently attended an informative Sedona Conference webinar on “Search and Information Retrieval”, which contained a section on Information Retrieval (IR) Lessons for E-Discovery presented by Ellen Voorhees of NIST.

As I described some of this research to a colleague of mine, he asked me “So, what’s the so what? What’s the most important step our customers can make to improve the way they search in e-discovery matters based on your work with customers and this research?” My answer was a little surprising even to me. While good cases can be made for looking at concept search and newer, more automated ways of performing content analysis, I believe the most important step that customers can take is simply for them to get their “experts” to start iteratively searching the data in a matter as early as possible in a matter. Let me explain.

When I look at Ellen’s presentation and the findings from the TREC legal track 2006 research overview three findings stand out to me:

1. If you want to get more effective results as measured by “recall” (i.e., how many of the relevant documents did you find?) and “precision” (i.e., how many of the documents you found were relevant versus false positives), then the best way to achieve this is to write a better search query.
2. One of the best ways to get better search queries is to commit human resources to improving them, by putting a “human-in-the-loop” while performing searches.
3. The more expert the human, the better results you are going to get.¹

In other words, what Ellen and the other researches have found that is that you get better results if the same person is running searches, evaluating the results, refining those queries, and trying again. The more expert the person, the better results you are going to get.

Now, you may be thinking that this sounds like common sense and I would completely agree with you. However, while this advice is clearly common sense to you and me, in my experience, it is not always followed in our industry. Instead, it’s all too common that at the beginning of a matter someone comes up with set of keyword queries, someone else runs these queries, some other people perform a detailed review of the results and then finally the “expert” or attorney at the end of this process reviews the most important documents and/or a summary of the documents written by someone else. At this point, some new queries may be developed based on the results of the review and the process starts over again.

What’s the problem with this approach? While in the end this approach can be effective, it can be exceedingly costly and time consuming. Instead, getting your “expert”, whether this is inside counsel, outside counsel, a subject matter expert, a litigation support professional, or a hired investigator, to interact with the data will allow you to find the most important information faster enabling you to make critical legal decisions faster and to dramatically reduce the cost and risk associated with e-discovery.

So why don’t more people follow the common sense advice of getting an expert in front of the data experimenting with queries, interacting with the data and developing better queries? In my view, the single biggest reason is that the technology used to perform searches for e-discovery has simply not been easy enough for legal experts to use. As a result, these experts have got used to developing queries without using technology, and not iteratively interacting with the data over a short period of time.

But that’s changing. In the past few years, several intuitive e-discovery solutions have come to market that enable non-technical lawyers to run their own queries. More and more law firms and enterprises are leveraging these solutions to move to “human-in-the-loop” searching. The results are striking: better early case assessment, much shorter turnaround times, lower costs, and more accurate results.

¹ This is my simplified interpretation of the findings of the TREC legal track. What was found was that an expert manual searcher performed well relative to other non-expert manual run results. Baron, J., Lewis, D., and Oard, D. ”TREC-2006 Legal Track Overview.” The TREC research also contained other findings not covered in this post and I recommend reading the full document so that readers can draw their own conclusions.