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Battle Continues between Attorneys and Client over Attorneys’ Failure to Review Documents – eDiscovery Case Law

In Price Waicukauski & Riley v. Murray, 1:10-cv-1065-WTL-TAB (S.D. Ind. Sept. 18, 2014), Indiana District Judge William T. Lawrence granted the plaintiff’s request for summary judgment for failure to pay attorney’s fees of over $125,000, and refused to issue summary judgment for either party related to a legal malpractice claim for the plaintiff’s admitted failure to review documents produced in the defendants’ case against another party because of a factual dispute regarding the plaintiff’s knowledge of the documents produced.

Case Background

This case was filed in August 2010 by the Plaintiff, Price Waicukauski & Riley, LLC, (“PWR”) against the Defendants, Dennis and Margaret Murray and DPM, Ltd. (“Murrays”), to recover $127,592.91 in attorneys’ fees owed to the plaintiff. The attorneys’ fees stem from the plaintiff’s representation of the defendants in a rather contentious lawsuit against Conseco that spanned more than six years, ultimately settling.  In November 2010, unhappy with the plaintiff’s representation, the defendants filed a counterclaim against the plaintiff alleging legal malpractice.

Legal Malpractice Claim of Breach of Duty of Loyalty

The defendants alleged several allegations of legal malpractice against the plaintiff, including conflict of interest, failure to properly plead federal subject matter jurisdiction and failure to take depositions and conduct discovery as they requested, among other allegations.  One allegation related to the defendants’ claim that the plaintiff breached the duty of loyalty to the defendants by failing (despite the defendant’s request to do so) to review documents before production in the case that revealed a Trust set up on behalf of the plaintiffs that wasn’t disclosed in interrogatory responses.  The plaintiff informed Mr. Murray that it reviewed the documents; however, it ultimately admitted that it did not.  As a result of the misleading interrogatory responses, Conseco filed a motion for sanctions which was granted, resulting in the defendants being ordered to pay over $85,000 in attorneys’ fees to their opponent’s lawyers.

The defendants claimed that the plaintiff knew about the Trust from the outset of its representation; however, the plaintiff (“falsely and underhandedly”, according to the defendants) represented to the magistrate judge assigned to the Underlying Litigation that it had no knowledge of the Trust until the defendants’ accountant produced the Murrays’ tax returns.

Judge’s Analysis and Ruling

The plaintiffs referenced Niswander v. Price Waicukauski & Riley, LLC, where the court held that “[w]hether . . . the Plaintiffs’ attorneys had a duty to review the documents personally before producing them in discovery . . . is simply not something within the knowledge of a layperson.”  However, Judge Lawrence noted, “[t]he Murrays have no expert testimony on either of these two related claims; however, they claim they fall into the above-mentioned exception for when no expert testimony is needed: ‘when the question is within the common knowledge of the community as a whole or when an attorney’s negligence is so grossly apparent that a layperson would have no difficulty in appraising it.’”  Judge Lawrence also agreed with the defendants differentiation of Niswander to this case in that they specifically directed the plaintiff to review the documents while the plaintiffs in Niswander did not.

Judge Lawrence also stated that “[t]he same rings true with the Murrays’ allegation that PWR falsely denied knowledge of the Trust… Again, the Court believes that it is well within the knowledge of a layperson that attorneys should not lie and falsely implicate their own clients in order to shield themselves from liability. Thus, the Court agrees that no expert testimony is needed on this claim regarding the standard of care.”

However, Judge Lawrence decided that “neither party is entitled to summary judgment on this issue” because “there is a factual dispute that precludes granting summary judgment on this claim. PWR maintains that it did not lie; it steadfastly maintains that it had no knowledge of the Trust at the outset of the litigation. Thus, when asked by the magistrate judge when it found out about the Trust, it informed her truthfully. Therefore, whether or not PWR breached a duty that caused injury to the Murrays depends on whom the jury believes: Mr. Murray or PWR.”

Ultimately, Judge Lawrence granted the summary judgment on behalf of the plaintiffs for the attorney’s fees of $127,592.91 (which the defendant did not dispute, but argued that “[t]he successful pursuit of [their] claims would effectively eliminate PWR’s claim”) and denied the defendant’s summary judgment request, but refused a final judgment as outstanding claims remained against the plaintiff.  Judge Lawrence concluded his ruling by noting that “The only claims that remain to be tried are the proximate cause issue with regard to the federal subject matter jurisdiction claim and the allegation of malpractice committed by PWR as a result of its alleged failure to review certain documents that led to sanctions being imposed on Mr. Murray.”

So, what do you think?  Does the failure by the plaintiff to review the defendant’s production constitute legal malpractice?  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.

How Mature is Your Organization in Handling eDiscovery? – eDiscovery Best Practices

A new self-assessment resource from EDRM helps you answer that question.

A few days ago, EDRM announced the release of the EDRM eDiscovery Maturity Self-Assessment Test (eMSAT-1), the “first self-assessment resource to help organizations measure their eDiscovery maturity” (according to their press release linked here).

As stated in the press release, eMSAT-1 is a downloadable Excel workbook containing 25 worksheets (actually 27 worksheets when you count the Summary sheet and the List sheet of valid choices at the end) organized into seven sections covering various aspects of the e-discovery process. Complete the worksheets and the assessment results are displayed in summary form at the beginning of the spreadsheet.  eMSAT-1 is the first of several resources and tools being developed by the EDRM Metrics group, led by Clark and Dera Nevin, with assistance from a diverse collection of industry professionals, as part of an ambitious Maturity Model project.

The seven sections covered by the workbook are:

  1. General Information Governance: Contains ten questions to answer regarding your organization’s handling of information governance.
  2. Data Identification, Preservation & Collection: Contains five questions to answer regarding your organization’s handling of these “left side” phases.
  3. Data Processing & Hosting: Contains three questions to answer regarding your organization’s handling of processing, early data assessment and hosting.
  4. Data Review & Analysis: Contains two questions to answer regarding your organization’s handling of search and review.
  5. Data Production: Contains two questions to answer regarding your organization’s handling of production and protecting privileged information.
  6. Personnel & Support: Contains two questions to answer regarding your organization’s hiring, training and procurement processes.
  7. Project Conclusion: Contains one question to answer regarding your organization’s processes for managing data once a matter has concluded.

Each question is a separate sheet, with five answers ranked from 1 to 5 to reflect your organization’s maturity in that area (with descriptions to associate with each level of maturity).  Default value of 1 for each question.  The five answers are:

  • 1: No Process, Reactive
  • 2: Fragmented Process
  • 3: Standardized Process, Not Enforced
  • 4: Standardized Process, Enforced
  • 5: Actively Managed Process, Proactive

Once you answer all the questions, the Summary sheet shows your overall average, as well as your average for each section.  It’s an easy workbook to use with input areas defined by cells in yellow.  The whole workbook is editable, so perhaps the next edition could lock down the calculated only cells.  Nonetheless, the workbook is intuitive and provides a nice exercise for an organization to grade their level of eDiscovery maturity.

You can download a copy of the eMSAT-1 Excel workbook from here, as well as get more information on how to use it (the page also describes how to provide feedback to make the next iterations even better).

The EDRM Maturity Model Self-Assessment Test is the fourth release in recent months by the EDRM Metrics team. In June 2013, the new Metrics Model was released, in November 2013 a supporting glossary of terms for the Metrics Model was published and in November 2013 the EDRM Budget Calculators project kicked off (with four calculators covered by us here, here, here and here).  They’ve been busy.

So, what do you think?  How mature is your organization in handling eDiscovery?  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.

Court Approves Use of Predictive Coding, Disagrees that it is an “Unproven Technology” – eDiscovery Case Law
In Dynamo Holdings v. Commissioner of Internal Revenue, Docket Nos. 2685-11, 8393-12 (U.S. Tax Ct. Sept 17, 2014), Texas Tax Court Judge Ronald Buch ruled that the petitioners “may use predictive coding in responding to respondent’s discovery request” and if “after reviewing the results, respondent believes that the response to the discovery request is incomplete, he may file a motion to compel at that time”.

The cases involved various transfers from one entity to a related entity where the respondent determined that the transfers were disguised gifts to the petitioner’s owners and the petitioners asserted that the transfers were loans.

The respondent requested for the petitioners to produce the electronically stored information (ESI) contained on two specified backup storage tapes or simply produce the tapes themselves. The petitioners asserted that it would “take many months and cost at least $450,000 to do so”, requesting that the Court deny the respondent’s motion as a “fishing expedition” in search of new issues that could be raised in these or other cases. Alternatively, the petitioners requested that the Court let them use predictive coding to efficiently and economically identify the non-privileged information responsive to respondent’s discovery request.  The respondent opposed the petitioners’ request to use predictive coding, calling it “unproven technology” and added that petitioners could simply give him access to all data on the two tapes and preserve the right (through a “clawback agreement”) to later claim that some or all of the data is privileged.

Judge Buch called the request to use predictive coding “somewhat unusual” and stated that “although it is a proper role of the Court to supervise the discovery process and intervene when it is abused by the parties, the Court is not normally in the business of dictating to parties the process that they should use when responding to discovery… Yet that is, in essence, what the parties are asking the Court to consider – whether document review should be done by humans or with the assistance of computers. Respondent fears an incomplete response to his discovery. If respondent believes that the ultimate discovery response is incomplete and can support that belief, he can file another motion to compel at that time.”

With regard to the respondent’s categorization of predictive coding as “unproven technology”, Judge Buch stated “We disagree. Although predictive coding is a relatively new technique, and a technique that has yet to be sanctioned (let alone mentioned) by this Court in a published Opinion, the understanding of e-discovery and electronic media has advanced significantly in the last few years, thus making predictive coding more acceptable in the technology industry than it may have previously been. In fact, we understand that the technology industry now considers predictive coding to be widely accepted for limiting e-discovery to relevant documents and effecting discovery of ESI without an undue burden.”

As a result, Judge Buch ruled that “[p]etitioners may use predictive coding in responding to respondent’s discovery request. If, after reviewing the results, respondent believes that the response to the discovery request is incomplete, he may file a motion to compel at that time.”

So, what do you think?  Should predictive coding have been allowed in this case?  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.

Good Processing Requires a Sound Process – Best of eDiscovery Daily

Home at last!  Today, we are recovering from our trip, after arriving back home one day late and without our luggage.  Satan, thy name is Lufthansa!  Anyway, for these past two weeks except for Jane Gennarelli’s Throwback Thursday series, we have been re-publishing some of our more popular and frequently referenced posts.  Today’s post is a topic that comes up often with our clients.  Enjoy!  New posts next week!

As we discussed Wednesday, working with electronic files in a review tool is NOT just simply a matter of loading the files and getting started.  Electronic files are diverse and can represent a whole collection of issues to address in order to process them for loading.  To address those issues effectively, processing requires a sound process.

eDiscovery providers like (shameless plus warning!) CloudNine Discovery process electronic files regularly to enable their clients to work with those files during review and production.  As a result, we are aware of some of the information that must be provided by the client to ensure that the resulting processed data meets their needs and have created an EDD processing spec sheet to gather that information before processing.  Examples of information we collect from our clients:

  • Do you need de-duplication?  If so, should it performed at the case or the custodian level?
  • Should Outlook emails be extracted in MSG or HTM format?
  • What time zone should we use for email extraction?  Typically, it’s the local time zone of the client or Greenwich Mean Time (GMT).  If you don’t think that matters, consider this example.
  • Should we perform Optical Character Recognition (OCR) for image-only files that don’t have corresponding text?  If we don’t OCR those files, these could be responsive files that are missed during searching.
  • If any password-protected files are encountered, should we attempt to crack those passwords or log them as exception files?
  • Should the collection be culled based on a responsive date range?
  • Should the collection be culled based on key terms?

Those are some general examples for native processing.  If the client requests creation of image files (many still do, despite the well documented advantages of native files), there are a number of additional questions we ask regarding the image processing.  Some examples:

  • Generate as single-page TIFF, multi-page TIFF, text-searchable PDF or non text-searchable PDF?
  • Should color images be created when appropriate?
  • Should we generate placeholder images for unsupported or corrupt files that cannot be repaired?
  • Should we create images of Excel files?  If so, we proceed to ask a series of questions about formatting preferences, including orientation (portrait or landscape), scaling options (auto-size columns or fit to page), printing gridlines, printing hidden rows/columns/sheets, etc.
  • Should we endorse the images?  If so, how?

Those are just some examples.  Questions about print format options for Excel, Word and PowerPoint take up almost a full page by themselves – there are a lot of formatting options for those files and we identify default parameters that we typically use.  Don’t get me started.

We also ask questions about load file generation (if the data is not being loaded into our own review tool, OnDemand®), including what load file format is preferred and parameters associated with the desired load file format.

This isn’t a comprehensive list of questions we ask, just a sample to illustrate how many decisions must be made to effectively process electronic data.  Processing data is not just a matter of feeding native electronic files into the processing tool and generating results, it requires a sound process to ensure that the resulting output will meet the needs of the case.

So, what do you think?  How do you handle processing of electronic files?  Please share any comments you might have or if you’d like to know more about a particular topic.

P.S. – No hamsters were harmed in the making of this blog post.

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.

The Files are Already Electronic, How Hard Can They Be to Load? – Best of eDiscovery Daily

Come fly with me!  Today we are winding our way back home from Paris, by way of Frankfurt.  For the next two weeks except for Jane Gennarelli’s Throwback Thursday series, we will be re-publishing some of our more popular and frequently referenced posts.  Today’s post is a topic that relates to a question that I get asked often.  Enjoy!

Since hard copy discovery became electronic discovery, I’ve worked with a number of clients who expect that working with electronic files in a review tool is simply a matter of loading the files and getting started.  Unfortunately, it’s not that simple!

Back when most discovery was paper based, the usefulness of the documents was understandably limited.  Documents were paper and they all required conversion to image to be viewed electronically, optical character recognition (OCR) to capture their text (though not 100% accurately) and coding (i.e., data entry) to capture key data elements (e.g., author, recipient, subject, document date, document type, names mentioned, etc.).  It was a problem, but it was a consistent problem – all documents needed the same treatment to make them searchable and usable electronically.

Though electronic files are already electronic, that doesn’t mean that they’re ready for review as is.  They don’t just represent one problem, they can represent a whole collection of problems.  For example:

These are just a few examples of why working with electronic files for review isn’t necessarily straightforward.  Of course, when processed correctly, electronic files include considerable metadata that provides useful information about how and when the files were created and used, and by whom.  They’re way more useful than paper documents.  So, it’s still preferable to work with electronic files instead of hard copy files whenever they are available.  But, despite what you might think, that doesn’t make them ready to review as is.

So, what do you think?  Have you encountered difficulties or challenges when processing electronic files?  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.

Does Size Matter? – Best of eDiscovery Daily

Vive la France!  Today is our third full day in Paris and we’re planning to have lunch at the Eiffel Tower, which is really large.  For the next two weeks except for Jane Gennarelli’s Throwback Thursday series, we will be re-publishing some of our more popular and frequently referenced posts.  Today’s post is one that has generated a lot of discussion over the years.  Enjoy!

I admit it, with a title like “Does Size Matter?”, I’m looking for a few extra page views.  😉

I frequently get asked how big does an ESI collection need to be to benefit from eDiscovery technology.  In a recent case with one of my clients, the client had a fairly small collection – only about 4 GB.  But, when a judge ruled that they had to start conducting depositions in a week, they needed to review that data in a weekend.  Without culling the data and using OnDemand® to manage the linear review, they would not have been able to make that deadline.  So, they clearly benefited from the use of eDiscovery technology in that case.

But, if you’re not facing a tight deadline, how large does your collection need to be for the use of eDiscovery technology to provide benefits?

I recently conducted a webinar regarding the benefits of First Pass Review – aka Early Case Assessment (ECA), or a more accurate term (as George Socha points out regularly), Early Data Assessment.  One of the topics discussed in that webinar was the cost of review for each gigabyte (GB).  Extrapolated from an analysis conducted by Anne Kershaw a few years ago (and published in the Gartner report E-Discovery: Project Planning and Budgeting 2008-2011), here is a breakdown:

Estimated Cost to Review All Documents in a GB:

  • Pages per GB:                   75,000
  • Pages per Document:        4
  • Documents Per GB:           18,750
  • Review Rate:                    50 documents per hour
  • Total Review Hours:          375
  • Reviewer Billing Rate:       $50 per hour

Total Cost to Review Each GB:      $18,750

Notes: The number of pages per GB can vary widely.  Page per GB estimates tend to range from 50,000 to 100,000 pages per GB, so 75,000 pages (18,750 documents) seems an appropriate average.  50 documents reviewed per hour is considered to be a fast review rate and $50 per hour is considered to be a bargain price.  eDiscovery Daily provided an earlier estimate of $16,650 per GB based on assumptions of 20,000 documents per GB and 60 documents reviewed per hour – the assumptions may change somewhat, but, either way, the cost for attorney review of each GB could be expected to range from at least $16,000 to $18,000, possibly more.

Advanced culling and searching capabilities of tools like OnDemand can enable you to cull out 70-80% of most collections as clearly non-responsive without having to conduct attorney review on those files.  If you have merely a 2 GB collection and assume the lowest review cost above of $16,000 per GB, the use of an ECA tool to cull out 70% of the collection can save $22,400 in attorney review costs.  Is that worth it?

So, what do you think?  Do you use eDiscovery technology for only the really large cases or ALL cases?   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.

Is Technology Assisted Review Older than the US Government? – eDiscovery Trends

A lot of people consider Technology Assisted Review (TAR) and Predictive Coding (PC) to be new technology.  We attempted to debunk that as myth last year after our third annual thought leader interview series by summarizing comments from some of the thought leaders that noted that TAR and PC really just apply artificial intelligence to the review process.  But, the foundation for TAR may go way farther back than you might think.

In the BIA blog, Technology Assisted Review: It’s not as new as you think it is, Robin Athlyn Thompson and Brian Schrader take a look at the origins of at least one theory behind TAR.  Called the “Naive Bayes classifier”, it’s based on theorems that were essentially introduced to the public in 1812.  But, the theorems existed quite a bit earlier than that.

Bayes’s theorem is named after Rev. Thomas Bayes (who died in 1761), who first showed how to use new evidence to update beliefs. He lived so long ago, that there is no known widely accepted portrait of him.  His friend Richard Price edited and presented this work in 1763, after Bayes’s death, as An Essay towards solving a Problem in the Doctrine of Chances.  Bayes’ algorithm remained unknown until it was independently rediscovered and further developed by Pierre-Simon Laplace, who first published the modern formulation in his 1812 Théorie analytique des probabilities (Analytic theory of probabilities).

Thompson and Schrader go on to discuss more recent uses of artificial intelligence algorithms to map trends, including Amazon’s More Like This functionality that Amazon uses to recommend other items that you may like, based on previous purchases.  That technology has been around for nearly two decades – can you believe it’s been that long? – and is one of the key factors for Amazon’s success over that time.

So, don’t scoff at the use of TAR because it’s “new technology”, that thinking is “naïve”.  Some of the foundation statistical theories for TAR go further back than the birth of our country.

So, what do you think?  Has your organization used technology assisted review on a case yet?  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.

Though it was “Switching Horses in Midstream”, Court Approves Plaintiff’s Predictive Coding Plan – eDiscovery Case Law

In Bridgestone Americas Inc. v. Int’l Bus. Mach. Corp., No. 3:13-1196 (M.D. Tenn. July 22, 2014), Tennessee Magistrate Judge Joe B. Brown, acknowledging that he was “allowing Plaintiff to switch horses in midstream”, nonetheless ruled that that the plaintiff could use predictive coding to search documents for discovery, even though keyword search had already been performed.

In this case where the plaintiff sued the defendant for a $75 million computer system that it claimed threw its “entire business operation into chaos”, the plaintiff requested that the court allow the use of predictive coding in reviewing over two million documents.  The defendant objected, noting that the request was an unwarranted change to the original case management order that did not include predictive coding, and that it would be unfair to use predictive coding after an initial screening had been done with keyword search terms.

Judge Brown conducted a lengthy telephone conference with the parties on June 25 and, began the analysis in his order by observing that “[p]redictive coding is a rapidly developing field in which the Sedona Conference has devoted a good deal of time and effort to, and has provided various best practices suggestions”, also noting that “Magistrate Judge Peck has written an excellent article on the subject and has issued opinions concerning predictive coding.”  “In the final analysis”, Judge Brown continued, “the uses of predictive coding is a judgment call, hopefully keeping in mind the exhortation of Rule 26 that discovery be tailored by the court to be as efficient and cost-effective as possible.”

As a result, noting that “we are talking about millions of documents to be reviewed with costs likewise in the millions”, Judge Brown permitted the plaintiff “to use predictive coding on the documents that they have presently identified, based on the search terms Defendant provided.”  Judge Brown acknowledged that he was “allowing Plaintiff to switch horses in midstream”, so “openness and transparency in what Plaintiff is doing will be of critical importance.”

This case has similar circumstances to Progressive Cas. Ins. Co. v. Delaney, where that plaintiff also desired to shift from the agreed upon discovery methodology for privilege review to a predictive coding methodology.  However, in that case, the plaintiff did not consult with either the court or the requesting party regarding their intentions to change review methodology and the plaintiff’s lack of transparency and lack of cooperation resulted in the plaintiff being ordered to produce documents according to the agreed upon methodology.  It pays to cooperate!

So, what do you think?  Should the plaintiff have been allowed to shift from the agreed upon methodology or did the volume of the collection warrant the switch?  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.

Our 1,000th Post! – eDiscovery Milestones

When we launched nearly four years ago on September 20, 2010, our goal was to be a daily resource for eDiscovery news and analysis.  Now, after doing so each business day (except for one), I’m happy to announce that today is our 1,000th post on eDiscovery Daily!

We’ve covered the gamut in eDiscovery, from case law to industry trends to best practices.  Here are some of the categories that we’ve covered and the number of posts (to date) for each:

We’ve also covered every phase of the EDRM (177) life cycle, including:

Every post we have published is still available on the site for your reference, which has made eDiscovery Daily into quite a knowledgebase!  We’re quite proud of that.

Comparing our first three months of existence to now, we have seen traffic on our site grow an amazing 474%!  Our subscriber base has more than tripled in the last three years!  We want to take this time to thank you, our readers and subcribers, for making that happen.  Thanks for making the eDiscoveryDaily blog a regular resource for your eDiscovery news and analysis!  We really appreciate the support!

We also want to thank the blogs and publications that have linked to our posts and raised our public awareness, including Pinhawk, Ride the Lightning, Litigation Support Guru, Complex Discovery, Bryan University, The Electronic Discovery Reading Room, Litigation Support Today, Alltop, ABA Journal, Litigation Support Blog.com, InfoGovernance Engagement Area, EDD Blog Online, eDiscovery Journal, e-Discovery Team ® and any other publication that has picked up at least one of our posts for reference (sorry if I missed any!).  We really appreciate it!

I also want to extend a special thanks to Jane Gennarelli, who has provided some serial topics, ranging from project management to coordinating review teams to what litigation support and discovery used to be like back in the 80’s (to which some of us “old timers” can relate).  Her contributions are always well received and appreciated by the readers – and also especially by me, since I get a day off!

We always end each post with a request: “Please share any comments you might have or if you’d like to know more about a particular topic.”  And, we mean it.  We want to cover the topics you want to hear about, so please let us know.

Tomorrow, we’ll be back with a new, original post.  In the meantime, feel free to click on any of the links above and peruse some of our 999 previous posts.  Now is your chance to catch up!  😉

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.

Court Sides with Defendant in Dispute over Predictive Coding that Plaintiff Requested – eDiscovery Case Law

In the case In re Bridgepoint Educ., Inc., Securities Litigation, 12cv1737 JM (JLB) (S.D. Cal. Aug. 6, 2014), California Magistrate Judge Jill L. Burkhardt ruled that expanding the scope of discovery by nine months was unduly burdensome, despite the plaintiff’s request for the defendant to use predictive coding to fulfill its discovery obligation and also approved the defendants’ method of using search terms to identify responsive documents for the already reviewed three individual defendants, directing the parties to meet and confer regarding the additional search terms the plaintiffs requested.

In this case involving several discovery disputes, a telephonic discovery conference was held in the instant action on June 27, during which, the Court issued oral orders on three of four discovery disputes.  As to the remaining dispute, the Court requested supplemental briefings from both parties and issued a ruling in this order, along with formalizing the remaining orders.

The unresolved discovery dispute concerned the plaintiffs’ “request for discovery extending beyond the time frame that Defendants have agreed to” for an additional nine months.  In their briefing, the defendants (based on the production efforts to date) claimed that expanding the scope of discovery by nine months would increase their review costs by 26% or $390,000.  The plaintiffs’ reply brief argued that the defendants’ estimate reflected the cost of manual review rather than the predictive coding system that the defendants would use – according to the plaintiffs, the cost of predictive coding was the only cost relevant to the defendants’ burden, estimating the additional burden to be roughly $11,279.

Per the Court’s request, the defendants submitted a reply brief addressing the arguments raised by the plaintiffs, arguing that predictive coding software “does not make manual review for relevance merely elective”.  The defendants argued that the software only assigns a percentage estimate to each document that reflects the assessment of the probability that the document is relevant, but the software is not foolproof and that attorney review is still required to ensure that the documents produced are both relevant and not privileged.

Judge Burkhardt, citing the “proportionality” rule of Federal Rule of Civil Procedure Rule 26(b)(2)(C), denied expanding the scope of discovery by nine months, finding that “Defendants have set forth sufficient evidence to conclude that the additional production would be unduly burdensome”.

The plaintiffs, claiming that the defendants “unilaterally-selected search terms” to identify the original production, also argued discovery produced from three Individual Defendants should be added to the Defendants’ predictive coding software.  But, Judge Burkhardt, formalizing the oral order, stated “[t]he Court approved Defendants’ method of using linear screening with the aid of search terms to identify responsive documents with regard to the emails already reviewed for the three Individual Defendants. The parties were directed to meet and confer regarding the additional search terms Plaintiffs would like Defendants to use.”

So, what do you think?  Was the additional discovery scope unduly burdensome or did the plaintiff have a point about reduced discovery costs?  Please share any comments you might have or if you’d like to know more about a particular topic.

eDiscovery Daily will resume posts on Tuesday.  Happy Labor Day!

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