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Analysis

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.

DESI Got Your Input, and Here It Is: eDiscovery Trends

Back in January, we discussed the Discovery of Electronically Stored Information (DESI, not to be confused with Desi Arnaz, pictured above) workshop and its call for papers describing research or practice for the DESI VI workshop that was held last week at the University of San Diego as part of the 15th International Conference on Artificial Intelligence & Law (ICAIL 2015). Now, links to those papers are available on their web site.

The DESI VI workshop aims to bring together researchers and practitioners to explore innovation and the development of best practices for application of search, classification, language processing, data management, visualization, and related techniques to institutional and organizational records in eDiscovery, information governance, public records access, and other legal settings. Ideally, the aim of the DESI workshop series has been to foster a continuing dialogue leading to the adoption of further best practice guidelines or standards in using machine learning, most notably in the eDiscovery space. Organizing committee members include Jason R. Baron of Drinker Biddle & Reath LLP and Douglas W. Oard of the University of Maryland.

The workshop included keynote addresses by Bennett Borden and Jeremy Pickens, a session regarding Topics in Information Governance moderated by Jason R. Baron, presentations of some of the “refereed” papers and other moderated discussions. Sounds like a very informative day!

As for the papers themselves, here is a list from the site with links to each paper:

Refereed Papers

Position Papers

If you’re interested in discovery of ESI, Information Governance and artificial intelligence, these papers are for you! Kudos to all of the authors who submitted them. Over the next few weeks, we plan to dive deeper into at least a few of them.

So, what do you think? Did you attend DESI VI? 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.

Court Orders Deposition of Expert to Evaluate Issues Resulting from Plaintiff’s Deletion of ESI: eDiscovery Case Law

In Procaps S.A. v. Patheon Inc., 12-24356-CIV-GOODMAN, 2014 U.S. Dist. (S.D. Fla. Apr. 24, 2015), Florida District Judge Jonathan Goodman ordered the deposition of a third-party computer forensic expert, who had previously examined the plaintiff’s computers, to be conducted in part by a Special Master that had been appointed to examine the eDiscovery and forensic issues in the case. The purpose of the ordered deposition was to help the Court decide the issues related to files deleted by the plaintiff and assist the defendant to decide whether or not to file a sanctions motion.

Case Background

Although the plaintiff filed suit in this antitrust case in December 2012, it did not implement a formal litigation hold until after February 27, 2014, when this Court ordered one to be implemented in response to the defendant’s motion. Beyond not implementing a formal hold, the plaintiff’s counsel acknowledged that its document and electronically stored information (“ESI”) search efforts were inadequate. Its US lawyers never traveled to Colombia (where the plaintiff is based) to meet with its information technology team (or other executives) to discuss how relevant or responsive ESI would be located, and it did not retain an ESI retrieval consultant to help implement a litigation hold or to search for relevant ESI and documents. In addition, some critical executives and employees conducted their own searches for ESI and documents without ever seeing the defendant’s document request or without receiving a list of search terms from its counsel.

The plaintiff ultimately agreed to a forensic analysis by an outside vendor specializing in ESI retrieval and the Court appointed a neutral computer forensic expert to analyze the plaintiff’s ESI and later appointed a Special Master to assist the Court with ESI issues. Completed in May 2014,the report, which was “thousands of pages long” from the forensic expert, showed that “nearly 200,000 emails, PDFs, and Microsoft Word, Excel, and PowerPoint files were apparently deleted” and “[i]t appears that approximately 5,700 of these files contain an ESI search term in their title, which indicates that they could have been subject to production in the forensic analysis if they had not been deleted.”

The defendant filed a motion to conduct the deposition of the neutral third-party expert to explain the report and the plaintiff filed an opposing response.

Judge’s Ruling

You’ve got to love an opinion that begins by quoting both eighteenth century English writer Samuel Johnson and the recently departed B.B. King. Judge Goodman began his analysis by referencing Federal Rule of Evidence 706, noting that it “governs court-appointed expert witnesses” and that “Subsection 706(b)(2) provides that such witnesses ‘may be deposed by any party.’” With regard to the plaintiff’s objection that such depositions are not very common, he stated that “regardless of whether depositions of court-appointed neutral experts on computer forensic issues are very common, used occasionally or are actually rare and atypical, they are certainly permissible. As noted, Federal Rule Evidence 706(b)(2) expressly provides for them. Moreover, there are published opinions discussing these types of depositions without critical comment. Perhaps more importantly, district courts have ‘broad discretion over the management of pre-trial activities, including discovery and scheduling.’”

Judge Goodman also rejected the plaintiff’s objection about the purported tardiness of the motion, noting that the forensic analysis took more than a year and was not completed until the first week of April 2015. He stated that “the deposition would undoubtedly be of great help to the Court. If I were to deny the motion, as Procaps urges, then I would be undermining my own ability to grapple with the myriad, thorny issues which will surely arise in the next several weeks or months.

Therefore, the Undersigned hopes to be able to ‘get by with a little help from my [ESI neutral expert] friends’ and is ‘gonna try [to comprehensively and correctly assess the to-be-submitted ESI issues] with a little help from my friends.’ Granting Patheon’s motion will enable the Undersigned to accomplish that goal; denying it would render that specific goal unattainable (and make the ESI spoliation/sanctions/trial evidence/bad faith/significance of missing evidence/prejudice evaluation more difficult).”

As a result, Judge Goodman ordered the deposition of the third-party computer forensic expert to be conducted in part by the Special Master and laid out the procedures for the deposition in his order.

So, what do you think? Was the judge right in ordering the deposition? Please share any comments you might have or if you’d like to know more about a particular topic.

This isn’t the first time we’ve covered this case, click here for a previous ruling we covered back in May 2014.

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.

Here’s a New Job Title that May Catch On – Chief Data Scientist: eDiscovery Trends

With big data becoming bigger than ever, the ability for organizations to apply effective data analytics within information governance and electronic discovery disciplines has become more important than ever. With that in mind, one law firm has created a new role that might catch on with other firms and corporations – the role of Chief Data Scientist.

The article from Legaltech News (Drinker Biddle Names Borden Chief Data Scientist, by Chris DiMarco) notes that Drinker Biddle & Reath has named Bennett Borden the firm’s first chief data scientist (CDS). As the author notes, in this role, Borden will oversee the implementation of technologies and services that apply use of data analytics and other cutting edge tools to the practice of law and will be tasked with developing the firm’s data analytics strategy. The move positions Drinker Biddle as one of the first firms – possibly in the world – to carve out a leadership position overseeing data analytics, with the impetus for the new role coming from the firm’s longstanding views on the importance of governing information.

Borden, who is also co-founder of the Information Governance Initiative (IGI), was quoted in the article, stating, “Our perspective is that information governance is a coordinating discipline around all the different facets of the creation use and disposition of information. And so data analytics is one more part of a large IG framework.”

Borden’s selection as the firm’s chief data scientist comes on the heels of him receiving a Master of Science degree in business analytics from New York University.

“Because of where analytics is going, especially in the business arena, I was interested in getting additional training,” Borden said. “My entire career has focused on using advanced analytics on large volumes of information to find something of value. Much of my work has focused on using advanced data analytics across many of our practices, not only for discovery, but also for compliance and investigations.”

According to Borden, he is among the first to hold the title of CDS at a major firm. Will this start a trend? Maybe so. Congrats, Bennett!

So, what do you think? Do you think other firms and organizations will create a Chief Data Scientist position? Please share any comments you might have or if you’d like to know more about a particular topic.

Image © exploringdatascience.com

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.

For a Successful Outcome to Your Discovery Project, Work Backwards: eDiscovery Best Practices

Based on a recent experience with a client, it seemed appropriate to revisit this topic. Plus, it’s always fun to play with the EDRM model. Notice anything different? 🙂

While the Electronic Discovery Reference Model from EDRM has become the standard model for the workflow of the process for handling electronically stored information (ESI) in discovery, it might be helpful to think about the EDRM model and work backwards, whether you’re the producing party or the receiving party.

Why work backwards?

You can’t have a successful outcome without envisioning the successful outcome that you want to achieve. The end of the discovery process includes the production and presentation stages, so it’s important to determine what you want to get out of those stages. Let’s look at them.

Presentation

Whether you’re a receiving party or a producing party, it’s important to think about what types of evidence you need to support your case when presenting at depositions and at trial – this is the type of information that needs to be included in your production requests at the beginning of the case as well as the type of information that you’ll need to preserve as a producing party.

Production

The format of the ESI produced is important to both sides in the case. For the receiving party, it’s important to get as much useful information included in the production as possible. This includes metadata and searchable text for the produced documents, typically with an index or load file to facilitate loading into a review application. The most useful form of production is native format files with all metadata preserved as used in the normal course of business.

For the producing party, it’s important to be efficient and minimize costs, so it’s important to agree to a production format that minimizes production costs. Converting files to an image based format (such as TIFF) adds costs, so producing in native format can be cost effective for the producing party as well. It’s also important to determine how to handle issues such as privilege logs and redaction of privileged or confidential information.

Addressing production format issues up front will maximize cost savings and enable each party to get what they want out of the production of ESI. If you don’t, you could be arguing in court like our case participants from yesterday’s post.

Processing-Review-Analysis

It also pays to make decisions early in the process that affect processing, review and analysis. How should exception files be handled? What do you do about files that are infected with malware? These are examples of issues that need to be decided up front to determine how processing will be handled.

As for review, the review tool being used may impact how quick and easy it is to get started, to load data and to use the tool, among other considerations. If it’s Friday at 5 and you have to review data over the weekend, is it easy to get started? As for analysis, surely you test search terms to determine their effectiveness before you agree on those terms with opposing counsel, right?

Preservation-Collection-Identification

Long before you have to conduct preservation and collection for a case, you need to establish procedures for implementing and monitoring litigation holds, as well as prepare a data map to identify where corporate information is stored for identification, preservation and collection purposes.

And, before a case even begins, you need an effective Information Governance program to minimize the amount of data that you might have to consider for responsiveness in the first place.

As you can see, at the beginning of a case (and even before), it’s important to think backwards within the EDRM model to ensure a successful discovery process. Decisions made at the beginning of the case affect the success of those latter stages, so working backwards can help ensure a successful outcome!

So, what do you think? What do you do at the beginning of a case to ensure success at the end?   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.

For Better Document Review, You Need to Approach a ZEN State: eDiscovery Best Practices

Among the many definitions of the word “zen”, the Urban Dictionary provides perhaps the most appropriate (non-religious) definition of the word, as follows: a total state of focus that incorporates a total togetherness of body and mind. However, when it comes to document review, a new web site by eDiscovery thought leader Ralph Losey may change your way of thinking about the word “ZEN”.

Ralph’s new site, ZEN Document Review, introduces ‘ZEN’ as an acronym: Zero Error Numerics. As stated on the site, “ZEN document review is designed to attain the highest possible level of efficiency and quality in computer assisted review. The goal is zero error. The methods to attain that goal include active machine learning, random sampling, objective measurements, and comparative analysis using simple, repeatable systems.”

The ZEN methods were developed by Ralph Losey’s e-Discovery Team (many of which are documented on his excellent e-Discovery Team® blog). They rely on focused attention and full clear communication between review team members.

In the intro video on his site, Ralph acknowledges that it’s impossible to have zero error in any large, complex project, but “with the help of the latest tools and using the right mindset, we can come pretty damn close”. One of the graphics on the site represents an “upside down champagne glass” that illustrates 99.9% probable relevant identified correctly during the review process at the top of the graph and 00.1% probable relevant identified incorrectly at the bottom of the graph.

The ZEN approach includes everything from “predictive coding analytics, a type of artificial intelligence, actively managed by skilled human analysts in a hybrid approach” to “quiet, uninterrupted, single-minded focus” where “dual tasking during review is prohibited” to “judgmental and random sampling and analysis such as i-Recall” and even high ethics, with the goal being to “find and disclose the truth in compliance with local laws, not win a particular case”. And thirteen other factors, as well. Hey, nobody said that attaining ZEN is easy!

Attaining zero error in document review is a lofty goal – I admire Ralph for setting the bar high. Using the right tools, methods and attitude, can we come “pretty damn close”?  What do you think? 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.

This Guy Says that Computers Could Eventually Replace Lawyers – In the Courtroom: eDiscovery Trends

Over four years ago, we covered an article in The New York Times that discussed how the use of artificial intelligence could lead to replacing “armies of expensive lawyers” during the eDiscovery process. Now, a new article in The Wall Street Journal online goes a step further, speculating that “computers will eventually pass the legal bar exam and defendants will be given the right to be represented by a computational attorney if they so wish”.

What Big Data Means for the Legal System, written by Robert Plant (not the Led Zeppelin singer, but a professor at the University of Miami, as well as an author and blogger for Harvard Business Review & WSJ Leadership Expert) discusses how artificial intelligence researchers have used the legal domain as an exploratory space to test theories for decades, but with limited success. The advent of big data has changed that, enabling us to analyze not only text but many other data types such as pictures, email, video and voice. As Plant notes, this capability “allows lawyers to look for patterns and correlations across vast data sets previously inaccessible.”

Plant uses analysis of judges’ behavior in cases as an example, suggesting the ability to obtain answers to questions like: “How does the Judge rule on certain types of cases can be studied by date and time? Does the judge dismiss cases for a consistent pattern of reasoning? How do holidays affect decisions? Do they sentence harder at different times of the day?”

Because of big data analytics, Plant predicts that “[m]any of the routine tasks now performed by entry-level lawyers or paralegals will increasingly be undertaken by analytics; case and trial strategies will be developed by legal informatics as will increasingly jury-selection strategies.” As a result, Plant takes the concept to a somewhat controversial conclusion, as follows:

“It is clear that with advances in machine learning, computers will eventually pass the legal bar exam and defendants will be given the right to be represented by a computational attorney if they so wish and thus court rooms could see a truly new form of human computer interaction in which the computer answers the question ‘does the client have a case?’”

Must he “ramble on”? Computers replace lawyers?!? In the courtroom?!? He sure isn’t showing the legal profession a “whole lotta love”, is he? (sorry, I couldn’t resist)

Clearly, we’ve seen the application of artificial intelligence result in significant benefits during the eDiscovery process, with several cases over the past few years endorsing technology assisted review (including this latest case just last month) as well as initiatives to apply technology to information governance (such as the Information Governance Initiative launched last year). Is it that far of a stretch to apply technology to decision making in the courtroom too? Or is the author simply “dazed and confused”? (ok, I really will stop now)

So, what do you think? Will clients someday be represented by computers in the courtroom? Please share any comments you might have or if you’d like to know more about a particular topic.

Clipart from Clipartheaven.com

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.

Court Agrees with Plaintiffs, Orders Provision for Qualitative Sampling of Disputed Search Terms: eDiscovery Case Law

In the case In Re: Lithium Ion Batteries Antitrust Litigation, No. 13-MD-02420 YGR (DMR) (N.D. Cal., Feb. 24, 2015), California Magistrate Judge Donna M. Ryu ordered the defendants to comply with the plaintiffs’ proposed qualitative sampling process for keyword search terms, citing DaSilva Moore that keywords “often are overinclusive”.

Case Background

In this multi-district litigation (MDL), the court ordered the parties to meet and confer to negotiate a protocol for the use of search terms in December 2014. The parties agreed upon an iterative process for the development and testing of search terms, summarized as follows:

  1. The producing/responding party will develop an initial list of proposed search terms and provide those terms to the requesting party;
  2. Within 30 days, the requesting party may propose modifications to the list of terms or provide additional terms (up to 125 additional terms or modifications); and
  3. Upon receipt of any additional terms or modifications, the producing/responding party will evaluate the terms, and
  4. Run all additional/modified terms upon which the parties can agree and review the results of those searches for responsiveness, privilege, and necessary redactions, or
  5. For those additional/modified terms to which the producing/responding party objects on the basis of overbreadth or identification of a disproportionate number of irrelevant documents, that party will provide the requesting party with certain quantitative metrics and meet and confer to determine whether the parties can agree on modifications to such terms. Among other things, the quantitative metrics include the number of documents returned by a search term and the nature and type of irrelevant documents that the search term returns. In the event the parties are unable to reach agreement regarding additional/modified search terms, the parties may file a joint letter regarding the dispute.

The parties requested the court’s guidance on a single remaining issue regarding their search term protocol: the steps the parties needed to take if they could not resolve a disagreement over a particular term. The plaintiff wanted the defendant to conduct a randomized qualitative sampling of documents retrieved by searching for any disputed terms, and to then allow the plaintiff to review the resulting documents following a privilege review.

The defendants objected to the proposed sampling provision “solely on the grounds that it will provide Plaintiffs with access to non-responsive, irrelevant documents that will be generated through the procedure.” They argued that the provision was unnecessary due to the detailed quantitative information that they agreed to produce regarding disputed search terms and because “there has been no showing that any Defendant’s production is incomplete.” The plaintiffs countered “that the proposed provision incorporates ESI best practices, including those embodied in materials developed by this Court” and contended that “the best way to refine searches and eliminate unhelpful search terms is to analyze a random sample of documents, including irrelevant ones, to modify the search in an effort to improve precision.”

Judge’s Opinion

With regard to the plaintiffs’ argument, Judge Ryu stated simply, “The court agrees. The point of random sampling is to eliminate irrelevant documents from the group identified by a computerized search and focus the parties’ search on relevant documents only. As the court noted in Moore v. Publicis Groupe, 287 F.R.D. 182 (S.D.N.Y. 2012), a problem with keywords ‘is that they often are overinclusive, that is, they find responsive documents but also large numbers of irrelevant documents.’”

Noting, however, that the defendants “raise a valid concern that the sampling protocol will result in the production of irrelevant information”, Judge Ryu ordered the following parameters to alleviate that concern:

  • At the hearing, the plaintiffs agreed that the defendants “may review the random qualitative sample and remove any irrelevant document(s) from the sample for any reason, provided that they replace the document(s) with an equal number of randomly generated document(s)”;
  • The parties also agreed that the defendants would conduct the qualitative sampling only after they had exhausted an agreed-upon quantitative evaluation process;
  • Judge Ryu ordered that irrelevant documents in the sample “shall be used only for the purpose of resolving disputes regarding search terms in this action, and for no other purpose in this litigation or in any other litigation” and that those irrelevant documents, as well as any attorney notes regarding the sample, “shall be destroyed within fourteen days of resolution of the search term dispute”;
  • Only one attorney from each law firm designated co-lead class counsel for Direct Purchaser Plaintiffs and Indirect Purchaser Plaintiffs (total of six attorneys) would be allowed to review the random sample;
  • The plaintiffs could invoke the random sampling process with respect to no more than five search terms per defendant group.

So, what do you think? Was the court right to order random sampling? 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.

Organizations are Increasing Their Investment in Legal Data Analytics, According to New Survey: eDiscovery Trends

According to a new survey of more than 125 legal technology professionals released by Huron Legal earlier this week, 68% of respondents expect their organizations’ investment in legal data analytics to increase in the next two years.

As noted in their announcement, there are, however, several challenges to effectively implement legal data analytics identified by the respondents, including:

  • Securing buy-in from senior leadership on the value of analytics (37% of respondents identified as the biggest challenge);
  • Quality of data (22%);
  • Cost of implementing data analytics effectively (23%),
  • Lack of accessible data (9%);
  • Threat to the practice of law (9%).

Also, 64% of respondents said that the legal industry is behind other industries when it comes to data analytics.

When asked about the one or more areas where data analytics is currently being applied in their organization, respondents replied as follows:

  • 64% of respondents indicated that data analytics is currently being applied in eDiscovery;
  • A third (33%) noted litigation management (i.e. case strategy, staffing);
  • Nearly a quarter (24%) indicated law department management (i.e., matter budgeting, legal project management);
  • Almost a third (29%) selected information governance;
  • 17% pointed to outside counsel/law firm management (i.e., staffing, etc.);
  • 16% noted rate/fee negotiation;
  • 10% stated M&A evaluation.

Only about 10% of respondents said that data analytics is not being applied at all within their organization. Not surprisingly, 45% of respondents identified cost management and savings as the biggest benefit of data analytics in the legal industry.

“It is clear that the legal industry is starting to recognize the power of data analytics, as evidenced by the burgeoning use of emerging legal technology and the willingness to increase investment in analytics,” said Nathalie Hofman, managing director at Huron Legal. “However, in order to realize analytics’ full potential, legal professionals at all levels must be educated about how to best to use them. Analytics can inform decisions in a number of areas, leading to greater efficiency and cost effectiveness.”

No survey would be complete without a handy-dandy infographic to summarize the results, click here to view the infographic for this survey by Huron Legal.

So, what do you think? Do these results reflect a promising trend? Or do they reflect that we still have a long way to go? 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. 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.

Judge Peck Wades Back into the TAR Pits with ‘Da Silva Moore Revisited’: eDiscovery Case Law

In Rio Tinto Plc v. Vale S.A., 14 Civ. 3042 (RMB)(AJP) (S.D.N.Y. Mar. 2, 2015), New York Magistrate Judge Andrew J. Peck approved the proposed protocol for technology assisted review (TAR) presented by the parties, but made it clear to note that “the Court’s approval ‘does not mean. . . that the exact ESI protocol approved here will be appropriate in all [or any] future cases that utilize [TAR].’”

Judge’s Opinion

Judge Peck began by stating that it had been “three years since my February 24, 2012 decision in Da Silva Moore v. Publicis Groupe & MSL Grp., 287 F.R.D. 182 (S.D.N.Y. 2012)” (see our original post about that case here), where he stated:

“This judicial opinion now recognizes that computer-assisted review [i.e., TAR] is an acceptable way to search for relevant ESI in appropriate cases.”

Judge Peck then went on to state that “[i]n the three years since Da Silva Moore, the case law has developed to the point that it is now black letter law that where the producing party wants to utilize TAR for document review, courts will permit it.” (Here are links to cases we’ve covered related to TAR in the last three years). He also referenced the Dynamo Holdings case from last year, calling it “instructive” in its approval of TAR, noting that the tax court ruled that “courts leave it to the parties to decide how best to respond to discovery requests”.

According to Judge Peck, the TAR issue still to be addressed overall “is how transparent and cooperative the parties need to be with respect to the seed or training set(s)”, commenting that “where the parties do not agree to transparency, the decisions are split and the debate in the discovery literature is robust”. While observing that the court “need not rule on the need for seed set transparency in this case, because the parties agreed to a protocol that discloses all non-privileged documents in the control sets”, Judge Peck stated:

“One point must be stressed — it is inappropriate to hold TAR to a higher standard than keywords or manual review. Doing so discourages parties from using TAR for fear of spending more in motion practice than the savings from using TAR for review.”

While approving the parties’ TAR protocol, Judge Peck indicated that he wrote this opinion, “rather than merely signing the parties’ stipulated TAR protocol, because of the interest within the ediscovery community about TAR cases and protocols.” And, he referenced Da Silva Moore once more, stating “the Court’s approval ‘does not mean. . . that the exact ESI protocol approved here will be appropriate in all [or any] future cases that utilize [TAR]. Nor does this Opinion endorse any vendor . . ., nor any particular [TAR] tool.’”

So, what do you think? How transparent should the technology assisted review process be? 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. 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.