eDiscovery Daily Blog

eDiscovery Best Practices: Judges’ Guide to Cost-Effective eDiscovery


Last week at LegalTech, I met Joe Howie at the blogger’s breakfast on Tuesday morning.  Joe is the founder of Howie Consulting and is the Director of Metrics Development and Communications for the eDiscovery Institute, which is a 501(c)(3) nonprofit research organization for eDiscovery.

eDiscovery Institute has just released a new publication that is a vendor-neutral guide for approaches to considerably reduce discovery costs for ESI.  The Judges’ Guide to Cost-Effective E-Discovery, co-written by Anne Kershaw (co-Founder and President of the eDiscovery Institute) and Joe Howie, also contains a foreword by the Hon. James C. Francis IV, Magistrate Judge for the Southern District of New York.  Joe gave me a copy of the guide, which I read during my flight back to Houston and found to be a terrific publication that details various mechanisms that can reduce the volume of ESI to review by up to 90 percent or more.  You can download the publication here (for personal review, not re-publication), and also read a summary article about it from Joe in InsideCounsel here.

Mechanisms for reducing costs covered in the Guide include:

  • DeNISTing: Excluding files known to be associated with commercial software, such as help files, templates, etc., as compiled by the National Institute of Standards and Technology, can eliminate a high number of files that will clearly not be responsive;
  • Duplicate Consolidation (aka “deduping”): Deduping across custodians as opposed to just within custodians reduces costs 38% for across-custodian as opposed to 21% for within custodian;
  • Email Threading: The ability to review the entire email thread at once reduces costs 36% over having to review each email in the thread;
  • Domain Name Analysis (aka Domain Categorization): As noted previously in eDiscoveryDaily, the ability to classify items based on the domain of the sender of the email can significantly reduce the collection to be reviewed by identifying emails from parties that are clearly not responsive to the case.  It can also be a great way to quickly identify some of the privileged emails;
  • Predictive Coding: As noted previously in eDiscoveryDaily, predictive coding is the use of machine learning technologies to categorize an entire collection of documents as responsive or non-responsive, based on human review of only a subset of the document collection. According to this report, “A recent survey showed that, on average, predictive coding reduced review costs by 45 percent, with several respondents reporting much higher savings in individual cases”.

The publication also addresses concepts such as focused sampling, foreign language translation costs and searching audio records and tape backups.  It even addresses some of the most inefficient (and therefore, costly) practices of ESI processing and review, such as wholesale printing of ESI to paper for review (either in paper form or ultimately converted to TIFF or PDF), which is still more common than you might think.  Finally, it references some key rules of the ABA Model Rules of Professional Conduct to address the ethical duty of attorneys in effective management of ESI.  It’s a comprehensive publication that does a terrific job of explaining best practices for efficient discovery of ESI.

So, what do you think?  How many of these practices have been implemented by your organization?  Please share any comments you might have or if you’d like to know more about a particular topic.