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eDiscovery Trends: Brian Schrader of Business Intelligence Associates (BIA)
 

This is the fifth of the 2012 LegalTech New York (LTNY) Thought Leader Interview series.  eDiscoveryDaily interviewed several thought leaders at LTNY this year and generally asked each of them the following questions:

  1. What do you consider to be the emerging trends in eDiscovery that will have the greatest impact in 2012?
  2. Which trend(s), if any, haven’t emerged to this point like you thought they would?
  3. What are your general observations about LTNY this year and how it fits into emerging trends?
  4. What are you working on that you’d like our readers to know about?

Today’s thought leader is Brian Schrader. Brian is Co-Founder and President of Business Intelligence Associates, Inc. (BIA).  Brian is an expert and frequent writer and speaker on eDiscovery and computer forensics topics, particularly those addressing the collection, preservation and processing functions of the eDiscovery process.

What do you consider to be the emerging trends in eDiscovery that will have the greatest impact in 2012?

Well, I think you don't have to walk around the floor very much to see that this year everybody is talking about predictive coding.  I think you're going to see that shake out a lot over the next year.  We've been doing predictive coding for about a year and a half now, and we have our own algorithms for that.  We have our review teams, and they've been using our algorithms to do predictive coding.  We like to call it “suggestive coding”.

What I expect you’ll find this year is a standard shakeout among providers because everybody talks about predictive coding.  The question is how does everybody approach it?  It's very much a black-box solution.  Most people don't know what goes on inside that process and how the process works.  So, I think that's going to be a hot topic for a while.  We're doing a lot of predictive coding and BIA is going to be announcing some cool things later this year on our predictive coding offerings.

Every provider that you talk to seems to have a predictive coding solution.  I'm really looking forward to seeing how things develop, because we have a lot of input on it and a lot of experience.  We have our review team that is reviewing millions and millions of documents per year, so we can compare various predictive coding engines to real results.  It gives us the ability to review the technology.  We look forward to being part of that conversation and I hope to see a little bit more clarity from the players and some real standards set around that process.

The courts have now also started to look at these algorithmic methods, Judge Peck in particular.  Everybody agrees that key word searching is inadequate.  But, people are still tentative about it – they say “it sounds good, but how does it work?  How are we going to approach it?”

Which trend(s), if any, haven’t emerged to this point like you thought they would?

Frankly, I thought we'd see a lot more competition for us in data collection.  A huge pain point for companies is how to gather all their data from all over the world.  It's something we've always focused on.  I started to see some providers focus on that, but now it looks like everybody, even some of the classic data collection providers, are focusing more on review tools.  That surprises me a bit, though I'm happy to be left with a wide-open field to have more exposure there.

When we first came out with TotalDiscovery.com last year, we thought we'd see all sorts of similar solutions pop up out there, but we just haven't.  Even the traditional collection companies haven't really offered a similar solution.  Perhaps it’s because everybody has a “laser focus” on predictive coding, since document review is so much more expensive.  I think that has really overpowered the focus of a lot of providers as they've focused only on that.  We have tried to focus on both collection and review.

I think data processing has become a commodity.  In talking to customers, they don't really ask about it anymore.  They all expect that everybody has the same base level capabilities.  Everybody knows that McDonald's secret sauce is basically Thousand Island dressing, so it’s no longer unique, the “jig is up”.  So, it's all about the ends, the collection, and the review.

What are your general observations about LTNY this year and how it fits into emerging trends?

Well, predictive coding again.  I think there's an awful lot of talk but not enough detail.  What you're seeing is a lot of providers who are saying “we’ll have predictive coding in six months”.  You're going to see a huge number of players in that field this year.  Everybody's going to throw a hat in the ring, and it's going to be interesting to see how that all works out.  Because how do you set the standards?  Who gets up there and really cooperates? 

I think it's really up to the individual companies to get together and cooperate on this. This particular field is so critical to the legal process that I don't think you can have everybody having individual standards and processes.  The most successful companies are going to be the ones that step up and work together to set those standards.  And, I don't know for sure, but I wouldn't be surprised if The Sedona Conference already has a subcommittee on this topic.

What are you working on that you’d like our readers to know about?

Our biggest announcement is around data collection – we've vastly expanded it.  Our motto is to collect “any data, anytime, anywhere”.  We've been providing data collection services for over a decade, and our collection guys like to say they've never met a piece of data they didn't like.

Now, we've brought that data collection capability direction to TotalDiscovery.com.  The latest upgrade, which we’re previewing at the show to be released in March, will offer the ability to collect data from social media sites like Facebook, Twitter, as well as collections from Webmail and Apple systems.  So, you can collect pretty much anything through TotalDiscovery.com that we have historically offered in our services division. It gives you a single place to manage data collection and bring it all together in one place, and then deliver it out to the review platform you want.

We’re on a three-week development cycle, which doesn’t always mean new features every three weeks, but it does mean we’re regularly adding new features.  Mid-year in 2011, we added legal hold capabilities and we’ve also recently added other components to simplify search and data delivery.  Now, we’ve added expanded collection for social media sites, Webmail and Apple.  Later this year, we expect to release our predictive coding capabilities to enable clients to perform predictive coding right after collection instead of waiting until the data is in the review tool.

Thanks, Brian, for participating in the interview!

And to the readers, as always, please share any comments you might have or if you’d like to know more about a particular topic!

eDiscovery Trends: Tom Gelbmann of Gelbmann & Associates, LLC
 

This is the fourth of the 2012 LegalTech New York (LTNY) Thought Leader Interview series.  eDiscoveryDaily interviewed several thought leaders at LTNY this year and generally asked each of them the following questions:

  1. What do you consider to be the emerging trends in eDiscovery that will have the greatest impact in 2012?
  2. Which trend(s), if any, haven’t emerged to this point like you thought they would?
  3. What are your general observations about LTNY this year and how it fits into emerging trends?
  4. What are you working on that you’d like our readers to know about?

Today’s thought leader is Tom Gelbmann. Tom is Principal of Gelbmann & Associates, LLC.  Since 1993, Gelbmann & Associates, LLC has advised law firms and Corporate Law Departments to realize the full benefit of their investments in Information Technology.  Tom has also been co-author of the leading survey on the electronic discovery market, The Socha-Gelbmann Electronic Discovery Survey; last year he and George Socha converted the Survey into Apersee, an online system for selecting eDiscovery providers and their offerings.  In 2005, he and George Socha launched the Electronic Discovery Reference Model project to establish standards within the eDiscovery industry – today, the EDRM model has become a standard in the industry for the eDiscovery life cycle and there are nine active projects with over 300 members from 81 participating organizations.

What do you consider to be the emerging trends in eDiscovery that will have the greatest impact in 2012?  And which trend(s), if any, haven’t emerged to this point like you thought they would?

I’m seeing an interesting trend regarding offerings from traditional top tier eDiscovery providers. Organizations who have invested in eDiscovery related technologies are beginning to realize these same technologies can be applied to information governance and compliance and enable an organization to get a much greater grasp on its total content.  Greater understanding of location and profile of content not only helps with eDiscovery and compliance, but also business intelligence and finally – destruction – something few organizations are willing to address.

We have often heard – Storage is cheap. The full sentence should be: Storage is cheap, but management is expensive.  I think that a lot of the tools that have been applied for collection, culling, search and analysis enable organizations to look at large quantities of information that is needlessly retained. It also allows them to take a look at information and get some insights on their processes and how that information is either helping their processes or, more importantly, hindering those processes and I think it's something you're going to see will help sell these tools upstream rather than downstream.

As far as items that haven't quite taken off, I think that technology assisted coding – I prefer that term over “predictive coding” – is coming, but it's not there yet.  It’s going to take a little bit more, not necessarily waiting for the judiciary to help, but just for organizations to have good experiences that they could talk about that demonstrate the value.  You're not going to remove the human from the process.  But, it's giving the human a better tool.  It’s like John Henry, with the ax versus the steam engine.  You can cut a lot more wood with the steam engine, but you still need the human.

What are your general observations about LTNY this year and how it fits into emerging trends?

Based on the sessions that I've attended, I think there's much more education.  There's just really more practical information for people to take away on how to manage eDiscovery and deal with eDiscovery related products or problems, whether it's cross-border issues, how to deal with the volumes, how to bring processes in house or work effectively with vendors.  There's a lot more practical “how-tos” than I've seen in the past.

What are you working on that you’d like our readers to know about?

Well, I think one of the things I'm very proud of with EDRM is that just before LegalTech, we put out a press release of what's happening with the projects, and I'm very pleased that five of the nine EDRM projects had significant announcements.  You can go to EDRM.net for that press release that details those accomplishments, but it shows that EDRM is very vibrant, and the teams are actually making good progress. 

Secondly, George Socha and I are very proud about the progress of Apersee, which was announced last year at LegalTech.  We've learned a lot, and we've listened to our clientele in the market – consumers and providers.  We listened, and then our customers changed their mind.  But, as a result, it's on a stronger track and we're very proud to announce that we have two gold sponsors, AccessData and Nuix.  We’re also talking to additional potential sponsors, and I think we'll have those announcements very shortly.

Thanks, Tom, for participating in the interview!

And to the readers, as always, please share any comments you might have or if you’d like to know more about a particular topic!

eDiscovery Best Practices: Google’s Blunder Keeps Them Under the (Smoking) Gun

As we noted back in November, a mistake made by Google during discovery in its lawsuit with Oracle could cost the company dearly, perhaps billions.  Here’s a brief recap of the case:

Google is currently involved in a lawsuit with Oracle over license fees associated with Java, which forms a critical part of Google’s Android operating system.  Google has leveraged free Android to drive mobile phone users to their ecosystem and extremely profitable searches and advertising.

Despite the use of search technology to cull down a typically large ESI population, a key email, written by Google engineer Tim Lindholm a few weeks before Oracle filed suit against Google, was produced that could prove damaging to their case.  With the threat of litigation from Oracle looming, Lindholm was instructed by Google executives to identify alternatives to Java for use in Android, presumably to strengthen their negotiating position.

“What we’ve actually been asked to do (by Larry and Sergey) is to investigate what technical alternatives exist to Java for Android and Chrome,” the email reads in part, referring to Google co-founders Larry Page and Sergey Brin. “We’ve been over a bunch of these, and think they all suck. We conclude that we need to negotiate a license for Java under the terms we need.”

Lindholm added the words “Attorney Work Product” and sent the email to Andy Rubin (Google’s top Android executive) and Google in-house attorney Ben Lee; however, Lindholm’s computer saved nine drafts of the email while he was writing it – before he added the words and addressed the email to Lee.  Because Lee’s name and the words “attorney work product” weren’t on the earlier drafts, they weren’t picked up by the eDiscovery software as privileged documents, and they were produced to Oracle.

Judge William Alsup of the U.S. District Court in Oakland, California, indicated to Google’s lawyers that it might suggest willful infringement of Oracle’s patents and despite Google’s motion to “clawback” the email on the grounds it was “unintentionally produced privileged material”, Alsup refused to exclude the document at trial.  Google next filed a petition for a writ of mandamus with the U.S. Court of Appeals for the Federal Circuit in Washington, D.C., seeking to have the appeals court overrule Alsup’s decision permitting Oracle to use the email as evidence in the trial.

On February 6, the Federal Circuit upheld Alsup’s ruling that the email is not privileged, denying Google’s mandamus petition. Observing that the email was written at the request of Google’s co-founders, Larry Page and Sergey Brin (who are not lawyers) and did not refer specifically to legal advice or the senior counsel’s investigation, the appeals court rejected Google’s petition.

As we noted before, organizing the documents into clusters based on similar content, might have grouped the unsent drafts with the identified “attorney work product” final version and helped to ensure that the drafts were classified as intended and not produced.

So, what do you think?  Could this mistake cost Google billions?  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 Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

eDiscovery Case Law: Predictive Coding Considered by Judge in New York Case

In Da Silva Moore v. Publicis Groupe, No. 11 Civ. 1279 (ALC) (S.D.N.Y. Feb. 8, 2012), Magistrate Judge Andrew J. Peck of the U.S. District Court for the Southern District of New York instructed the parties to submit proposals to adopt a protocol for e-discovery that includes the use of predictive coding, perhaps the first known case where a technology assisted review approach was considered by the court.

In this case, the plaintiff, Monique Da Silva Moore, filed a Title VII gender discrimination action against advertising conglomerate Publicis Groupe, on her behalf and the behalf of other women alleged to have suffered discriminatory job reassignments, demotions and terminations.  Discovery proceeded to address whether Publicis Groupe:

  • Compensated female employees less than comparably situated males through salary, bonuses, or perks;
  • Precluded or delayed selection and promotion of females into higher level jobs held by male employees; and
  • Disproportionately terminated or reassigned female employees when the company was reorganized in 2008.

Consultants provided guidance to the plaintiffs and the court to develop a protocol to use iterative sample sets of 2,399 documents from a collection of 3 million documents to yield a 95 percent confidence level and a 2 percent margin of error (see our previous posts here, here and here on how to determine an appropriate sample size, randomly select files and conduct an iterative approach). In all, the parties expect to review between 15,000 to 20,000 files to create the “seed set” to be used to predictively code the remainder of the collection.

The parties were instructed to submit their draft protocols by February 16th, which is today(!).  The February 8th hearing was attended by counsel and their respective ESI experts.  It will be interesting to see what results from the draft protocols submitted and the opinion from Judge Peck that results.

So, what do you think?  Should courts order the use of technology such as predictive coding in litigation?  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 Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

eDiscovery Trends: George Socha of Socha Consulting
 

This is the first of the 2012 LegalTech New York (LTNY) Thought Leader Interview series.  eDiscoveryDaily interviewed several thought leaders at LTNY this year and generally asked each of them the following questions:

  1. What do you consider to be the emerging trends in eDiscovery that will have the greatest impact in 2012?
  2. Which trend(s), if any, haven’t emerged to this point like you thought they would?
  3. What are your general observations about LTNY this year and how it fits into emerging trends?
  4. What are you working on that you’d like our readers to know about?

Today’s thought leader is George Socha.  A litigator for 16 years, George is President of Socha Consulting LLC, offering services as an electronic discovery expert witness, special master and advisor to corporations, law firms and their clients, and legal vertical market software and service providers in the areas of electronic discovery and automated litigation support. George has also been co-author of the leading survey on the electronic discovery market, The Socha-Gelbmann Electronic Discovery Survey; last year he and Tom Gelbmann converted the Survey into Apersee, an online system for selecting eDiscovery providers and their offerings.  In 2005, he and Tom Gelbmann launched the Electronic Discovery Reference Model project to establish standards within the eDiscovery industry – today, the EDRM model has become a standard in the industry for the eDiscovery life cycle and there are nine active projects with over 300 members from 81 participating organizations.  George has a J.D. for Cornell Law School and a B.A. from the University of Wisconsin – Madison.

What do you consider to be the emerging trends in eDiscovery that will have the greatest impact in 2012?

I may have said this last year too, but it holds true even more this year – if there's an emerging trend, it's the trend of people talking about the emerging trend.  It started last year and this year every person in the industry seems to be delivering the emerging trend.  Not to be too crass about it, but often the message is, "Buy our stuff", a message that is not especially helpful.

Regarding actual emerging trends, each year we all try to sum up legal tech in two or three words.  The two words for this year can be “predictive coding.”  Use whatever name you want, but that's what everyone seems to be hawking and talking about at LegalTech this year.  This does not necessarily mean they really can deliver.  It doesn't mean they know what “predictive coding” is.  And it doesn't mean they've figured out what to do with “predictive coding.”  Having said that, expanding the use of machine assisted review capabilities as part of the e-discovery process is a important step forward.  It also has been a while coming.  The earliest I can remember working with a client, doing what's now being called predictive coding, was in 2003.  A key difference is that at that time they had to create their own tools.  There wasn't really anything they could buy to help them with the process.

Which trend(s), if any, haven’t emerged to this point like you thought they would?

One thing I don't yet hear is discussion about using predictive coding capabilities as a tool to assist with determining what data to preserve in the first place.  Right now the focus is almost exclusively on what do you do once you’ve “teed up” data for review, and then how to use predictive coding to try to help with the review process.

Think about taking the predictive coding capabilities and using them early on to make defensible decisions about what to and what not to preserve and collect.  Then consider continuing to use those capabilities throughout the e-discovery process.  Finally, look into using those capabilities to more effectively analyze the data you're seeing, not just to determine relevance or privilege, but also to help you figure out how to handle the matter and what to do on a substantive level.

What are your general observations about LTNY this year and how it fits into emerging trends?

Well, Legal Tech continues to have been taken over by electronic discovery.  As a result, we tend to overlook whole worlds of technologies that can be used to support and enhance the practice of law. It is unfortunate that in our hyper-focus on e-discovery, we risk losing track of those other capabilities.

What are you working on that you’d like our readers to know about?

With regard to EDRM, we recently announced that we have hit key milestones in five projects.  Our EDRM Enron Email Data Set has now officially become an Amazon public dataset, which I think will mean wider use of the materials.

We announced the publication of our Model Code of Conduct, which was five years in the making.  We have four signatories so far, and are looking forward to seeing more organizations sign on.

We announced the publication of version 2.0 of our EDRM XML schema.  It's a tightened-up schema, reorganized so that it should be a bit easier to use and more efficient in the operation.

With the Metrics project, we are beginning to add information to a database that we've developed to gather metrics, the objective being to be able to make available metrics with an empirical basis, rather than the types of numbers bandied about today, where no one seems to know how they were arrived at. Also, last year the Uniform Task Billing Management System (UTBMS) code set for litigation was updated.  The codes to use for tracking e-discovery activities were expanded from a single code that covered not just e-discovery but other activities, to a number of codes based on the EDRM Metrics code set.

On the Information Governance Reference Model (IGRM) side, we recently published a joint white paper with ARMA.  The paper cross-maps the EDRMs Information Governance Reference Model (IGRM) with ARMA's Generally Accepted Recordkeeping Principles (GARP).  We look forward to more collaborative materials coming out of the two organizations.

As for Apersee, we continue to allow consumers search the data on the site for free, but we also are longer charging providers a fee for their information to be available.  Instead, we now have two sponsors and some advertising on the site.  This means that any provider can put information in, and everyone can search that information.  The more data that goes in, the more useful the searching process comes because.  All this fits our goal of creating a better way to match consumers with the providers who have the services, software, skills and expertise that the consumers actually need.

And on a consulting and testifying side, I continue to work a broad array of law firms; corporate and governmental consumers of e-discovery services and software; and providers offering those capabilities.

Thanks, George, for participating in the interview!

And to the readers, as always, please share any comments you might have or if you’d like to know more about a particular topic!

eDiscovery Trends: “Assisted” is the Key Word for Technology Assisted Review
 

As noted in our blog post entitled 2012 Predictions – By The Numbers, almost all of the sets of eDiscovery predictions we reviewed (9 out of 10) predicted a greater emphasis on Technology Assisted Review (TAR) in the coming year.  It was one of our predictions, as well.  And, during all three days at LegalTech New York (LTNY) a couple of weeks ago, sessions were conducted that addressed technology assisted review concepts and best practices.

While some equate technology assisted review with predictive coding, other technology approaches such as conceptual clustering are also increasing in popularity.  They qualify as TAR approaches, as well.  However, for purposes of this blog post, we will focus on predictive coding.

Over a year ago, I attended a Virtual LegalTech session entitled Frontiers of E-Discovery: What Lawyers Need to Know About “Predictive Coding” and wrote a blog post from that entitled What the Heck is “Predictive Coding”?  The speakers for the session were Jason R. Baron, Maura Grossman and Bennett Borden (Jason and Bennett are previous thought leader interviewees on this blog).  The panel gave the best descriptive definition that I’ve seen yet for predictive coding, as follows:

“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. These technologies typically rank the documents from most to least likely to be responsive to a specific information request. This ranking can then be used to “cut” or partition the documents into one or more categories, such as potentially responsive or not, in need of further review or not, etc.”

It’s very cool technology and capable of efficient and accurate review of the document collection, saving costs without sacrificing quality of review (in some cases, it yields even better results than traditional manual review).  However, there is one key phrase in the definition above that can make or break the success of the predictive coding process: “based on human review of only a subset of the document collection”. 

Key to the success of any review effort, whether linear or technology assisted, is knowledge of the subject matter.  For linear review, knowledge of the subject matter usually results in preparation of high quality review instructions that (assuming the reviewers competently follow those instructions) result in a high quality review.  In the case of predictive coding, use of subject matter experts (SMEs) to review a core subset of documents (typically known as a “seed set”) and make determinations regarding that subset is what enables the technology in predictive coding to “predict” the responsiveness and importance of the remaining documents in the collection.  The more knowledgeable the SMEs are in creating the “seed set”, the more accurate the “predictions” will be.

And, as is the case with other processes such as document searching, sampling the results (by determining the appropriate sample size of responsive and non-responsive items, randomly selecting those samples and reviewing both groups – responsive and non-responsive – to test the results) will enable you to determine how effective the process was in predictively coding the document set.  If sampling shows that the process yielded inadequate results, take what you’ve learned from the sample set review and apply it to create a more accurate “seed set” for re-categorizing the document collection.  Sampling will enable you to defend the accuracy of the predictive coding process, while saving considerable review costs.

So, what do you think?  Have you utilized predictive coding in any of your reviews?  How did it work for you?  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 Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

eDiscovery Best Practices: Preparing Your 30(b)(6) Witnesses
 

When it comes to questions and potential issues that the receiving party may have about the discovery process of the producing party, one of the most common and direct methods for conducting “discovery about the discovery” is a deposition under Federal Rule 30(b)(6). This rule enables a party to serve a deposition notice on the entity involved in the litigation rather than an individual. The notice identifies the topics to be covered in the deposition, and the entity being deposed must designate one or more people qualified to answer questions on the identified topics.

While those designated to testify may not necessarily have day-to-day responsibility related to the identified topics, they must be educated enough in those issues to sufficiently address them during the testimony. Serving a deposition notice on the entity under Federal Rule 30(b)(6) saves the deposing party from having to identify specific individual(s) to depose while still enabling the topics to be fully explored in a single deposition.

Topics to be covered in a 30(b)(6) deposition can vary widely, depending on the facts and circumstances of the case. However, there are some typical topics that the deponent(s) should be prepared to address.

Legal Hold Process: Perhaps the most common area of focus in a 30(b)(6) deposition is the legal hold process as spoliation of data can occur when the legal hold process is unsound and data spoliation is the most common cause of sanctions resulting from the eDiscovery process.  Issues to address include:

  • General description of the legal hold process including all details of that policy and specific steps that were taken in this case to effectuate a hold.
  • Timing of issuing the legal hold and to whom it was issued.
  • Substance of the legal hold communication (if the communication is not considered privileged).
  • Process for selecting sources for legal hold, identification of sources that were eliminated from legal hold, and a description of the rationale behind those decisions.
  • Tracking and follow-up with the legal hold sources to ensure understanding and compliance with the hold process.
  • Whether there are any processes in place in the company to automatically delete data and, if so, what steps were taken to disable them and when were those steps taken?

Collection Process: Logically, the next eDiscovery step discussed in the 30(b)(6) deposition is the process for collecting preserved data:

  • Method of collecting ESI for review, including whether the method preserved all relevant metadata intact.
  • Chain of custody tracking from origination to destination.

Searching and Culling: Once the ESI is collected, the methods for conducting searches and culling the collection down for review must be discussed:

  • Method used to cull the ESI prior to review, including the tools used, the search criteria for inclusion in review and how the search criteria was developed (including potential use of subject matter experts to flush out search terms).
  • Process for testing and refining search terms used.

Review Process: The 30(b)(6) witness(es) should be prepared to fully describe the review process, including:

  • Methods to conduct review of the ESI including review application(s) used and workflow associated with the review process.
  • Use of technology to assist with the review, such as clustering, predictive coding, duplicate and near-duplicate identification.
  • To the extent the process can be described, methodology for identifying and documenting privileged ESI on the privilege log (this methodology may be important if the producing party may request to “claw back” any inadvertently produced privileged ESI).
  • Personnel employed to conduct ESI review, including their qualifications, experience, and training.

Production Process: Information regarding the production process, including:

  • Methodology for organizing and verifying the production, including confirmation of file counts and spot QC checks of produced files for content.
  • The total volume of ESI collected, reviewed, and produced.

Depending on the specifics of the case and discovery efforts, there may be further topics to be addressed to ensure that the producing party has met its preservation and discovery obligations.

So, what do you think?  Have you had to prepare 30(b)(6) witnesses for deposition?  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 Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

eDiscovery Trends: Deadly Sins of Document Review

With all of the attention on Technology Assisted Review (TAR) during the LegalTech New York (LTNY) show, you would think that no one is conducting manual review anymore.  However, even the staunchest advocates of TAR that I spoke to last week indicated that manual review is still a key part of an effective review process where technology is used to identify potentially responsive and privileged ESI before the manual review process enables the final determinations to be made.

There are “dos” and “don’ts” for conducting an effective manual review.  There was an interesting article in Texas Lawyer (via Law Technology News) entitled The 7 Deadly Sins of Document Review by Dalton Young that focuses on the “don’ts”.  As review is the most expensive phase of the eDiscovery process and legal budgets are stretched to the limit, it’s important to get the most out of your spend on manual review.  With that in mind, here are the seven deadly sins of document review (along with a few of my observations):

  1. Hiring overqualified reviewers: Although there are many qualified lawyers available due to the recent recession, those lawyers often don’t have as much experience as seasoned review paralegals, who are also less expensive and less likely to leave for another offer.
  2. Failing to establish a firm time commitment: If lead counsel doesn’t clearly establish the expected review timeline up front and expect reviewers to commit to that time frame, turnover of reviewers can drive up costs and delay project completion.
  3. Failing to provide reviewers with thorough training on the review tools: Train beyond just the basics so that reviewers can take advantage of advanced software features and training starts with lead counsel.  I would adjust this point a bit: Lead counsel needs to become fully proficient on the review tools, then develop a workflow that manages the efficiency of the reviewers and train the reviewers according to that workflow.  While it may be nice for reviewers to know all of the advanced search features, full understanding of searching best practices isn’t something that can be accomplished in a single training session and should be managed by someone with considerable experience using advanced searching capabilities in an efficient and defensible manner.
  4. Failing to empower reviewers with sufficient background on the case: Providing reviewers with not just a list of expected key words, but also an understanding of the issues of the case enables them to recognize important documents that might not fit within the key words identified.  I would also add that it’s important to have regular “huddles” so that learned knowledge by selected reviewers can be shared with the entire team to maximize review effectiveness.
  5. Failing to foster bonds within the review team: Just like any other team member, reviewers like to know that they’re an important part of the cause and that their work is appreciated, so treating them to lunch or an occasional happy hour can foster a more enjoyable work environment and increase reviewer retention.
  6. Failing to predetermine tags and codes before the project begins: A lead member of the law firm should complete an overview of the discovery to identify the process and establish tags up front instead of “on the fly” as review progresses (even though that tag list will often need to be supplemented regardless how well the upfront overview is conducted).  I would add inclusion of one or more subject matter experts in that upfront process to help identify those tags.
  7. Providing reviewers with a too-structured work environment: The author indicates that counsel should “consider providing a relaxed, somewhat self-directed work environment”.  The key here is “somewhat”, but flexibility in start and stop work times and break/lunch times can enable you to keep good reviewers who may need some flexibility.  Regular monitoring of reviewer metrics will enable the review manager to confirm that reviewer performance is not adversely affected by increased flexibility, or adjust accordingly if the review environment becomes too lax.

So, what do you think?  Are there other “deadly sins” that the author doesn’t mention?  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 Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

eDiscovery Trends: Needing “Technology Assisted Review” to Write a Blog Post
 

Late on a Thursday night, with a variety of tasks and projects on my plate at the moment, it seems more difficult this night to find a unique and suitable topic for today’s blog post.

One thing I often do when looking for ideas is to hit the web and turn to the many resources that I read regularly to stay abreast of developments in the industry.  Usually when I do that, I find one article or blog post that “speaks to me” as a topic to talk about on this blog.  However, when doing so last night, I found several topics worth discussing and had difficulty selecting just one.  So, here are some of the notable articles and posts that I’ve been reviewing:

There’s plenty more articles out there.  I’ve barely scratched the surface.  When we launched eDiscovery Daily about 16 months ago, some wondered whether there would be enough eDiscovery news and information to talk about on a daily basis.  The problem we have found instead is that there is SO much to talk about, it’s difficult to choose.  Today, I was unable to choose just one topic, so, as the picture notes, “I have nothing to say”.  Therefore, I’ve had to use “technology assisted review” to provide a post to you, thanks to the many excellent articles and blogs out there.  Enjoy!

So, what do you think?  Are there any specific topics that you find are being discussed a lot on the web?  Are there any topics that you’d like to see discussed more?  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 Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

eDiscovery Case Law: Court Denies Plaintiff Request For Additional Searches for Acronyms
 

In the case In Re: National Association of Music Merchants, Musical Instruments and Equipment Antitrust Litigation, MDL No. 2121 (Dec. 19, 2011), U.S. Magistrate Judge Louisa S. Porter considered a motion by the plaintiffs seeking to compel the defendants to run document searches containing abbreviations and acronyms identified during discovery.  Ruling that the plaintiffs had “ample opportunity” to obtain this discovery earlier in the case, the court denied the motion.

The defendants notified the plaintiffs that they intended to use keyword searches to find relevant documents to plaintiffs’ discovery requests and asked the plaintiffs to provide search terms.  However, the plaintiffs indicated that they could not provide the terms, lacking sufficient information at that point to construct meaningful searches. So, the defendants created their own list of search terms, which they then reviewed with the plaintiffs, who protested that the terms were too restrictive and were unlikely to capture some highly relevant documents. As a result, both sides sat down and negotiated a list of agreed-upon search terms, including several terms specifically targeted to capturing defendant-to-defendant communications.

The defendants began to produce documents based on the agreed-upon terms. Through review of those produced documents, the plaintiffs discovered the frequent use of abbreviations and acronyms and filed a motion seeking to compel the defendants to run document searches containing these abbreviations and acronyms.

While the court noted that keyword searching should be “a cooperative and informed process” and emphasized the importance of “a full and transparent discussion among counsel of the search terminology”, the court chastised the plaintiffs, noting:

“Here, the Court finds Plaintiffs had ample opportunity to obtain discovery regarding abbreviations and acronyms of Defendant companies, and the burden or expense to Defendants in having to comply with Plaintiffs’ request regarding abbreviations and acronyms outweighs its likely benefit. … First, Plaintiffs had two separate opportunities to suggest that Defendants search for abbreviations and acronyms of the Defendant companies; initially, before Defendant’s produced documents; and second, during negotiations between the parties on agreed-upon expanded search terms. In the spirit of the conclusions made at the Sedona Conference, and in light of the transparent discussion among counsel of the search terminology and subsequent agreement on the search method, the Court finds it unreasonable for Defendant to re-search documents they have already searched and produced.

Second, after meeting and conferring with Plaintiffs, and relying on their agreement with Plaintiffs regarding search terms, Defendants have already searched and produced a significant number of documents, thereby incurring significant expenses during this limited discovery period. Further, as articulated by Defendants, the new search terms Plaintiffs have proposed would require some Defendants to review tens of thousands of additional documents that would likely yield only a very small number of additional responsive documents. Therefore, the Court finds a re-search of documents Defendants have already searched and produced is overly burdensome.”

As a result, the court denied the plaintiffs’ request to “run document searches containing abbreviations and acronyms for agreed-upon search terms concepts”.

So, what do you think?  Should the plaintiffs’ have been able to anticipate the abbreviations and acronyms during negotiations or should their motion have been granted to add them later?  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 Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.