eDiscovery Daily Blog

Here’s One Study That Shows Potential Savings from Technology Assisted Review: eDiscovery Trends

A couple of weeks ago, we discussed the Discovery of Electronically Stored Information (DESI) workshop and the papers describing research or practice presented at the workshop that was held earlier this month.  Today, let’s cover one of those papers.

The Case for Technology Assisted Review and Statistical Sampling in Discovery (by Christopher H Paskach, F. Eli Nelson and Matthew Schwab) aims to show how Technology Assisted Review (TAR) and Statistical Sampling can significantly reduce risk and improve productivity in eDiscovery processes.  The easy to read 6 page report concludes with the observation that, with measures like statistical sampling, “attorney stakeholders can make informed decisions about  the reliability and accuracy of the review process, thus quantifying actual risk of error and using that measurement to maximize the value of expensive manual review. Law firms that adopt these techniques are demonstrably faster, more informed and productive than firms who rely solely on attorney reviewers who eschew TAR or statistical sampling.”

The report begins by giving an introduction which includes a history of eDiscovery, starting with printing documents, “Bates” stamping them, scanning and using Optical Character Recognition (OCR) programs to capture text for searching.  As the report notes, “Today we would laugh at such processes, but in a profession based on ‘stare decisis,’ changing processes takes time.”  Of course, as we know now, “studies have concluded that machine learning techniques can outperform manual document review by lawyers”.  The report also references key cases such as DaSilva Moore, Kleen Products and Global Aerospace, demonstrating with the first few of many cases to approve the use of technology assisted review for eDiscovery.

Probably the most interesting portion of the report is the section titled Cost Impact of TAR, which illustrates a case scenario that compares the cost of TAR to the cost of manual review.  On a strictly relevance based review of 90,000 documents (after keyword filtering, which implies a multimodal approach to TAR), the TAR approach was over $57,000 less expensive ($136,225 vs. $193,500 for manual review).  The report illustrates the comparison with both a numbers spreadsheet and a pie chart comparison of costs, based on the assumptions provided.  Sounds like the basis for a budgeting tool!

Anyway, the report goes on to discuss the benefits of statistical sampling to validate the results, demonstrating that the only way to attempt to do so in a manual review scenario is to review the documents multiple times, which is prone to human error and inconsistent assessments of responsiveness.  The report then covers necessary process changes to realize the benefits of TAR and statistical sampling and concludes with the declaration that:

“Companies and law firms that take advantage of the rapid advances in TAR will be able to keep eDiscovery review costs down and reduce the investment in discovery by getting to the relevant facts faster. Those firms who stick with unassisted manual review processes will likely be left behind.”

The report is a quick, easy read and can be viewed here.

So, what do you think?  Do you agree with the report’s findings?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine. eDiscovery Daily is made available by CloudNine solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscovery Daily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.