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Doug Austin

eDiscovery Case Law: Judge Scheindlin Says “No” to Self-Collection, “Yes” to Predictive Coding
 

When most people think of the horrors of Friday the 13th, they think of Jason Voorhees.  When US Immigration and Customs thinks of Friday the 13th horrors, do they think of Judge Shira Scheindlin?

As noted in Law Technology News (Judge Scheindlin Issues Strong Opinion on Custodian Self-Collection, written by Ralph Losey, a previous thought leader interviewee on this blog), New York District Judge Scheindlin issued a decision last Friday (July 13) addressing the adequacy of searching and self-collection by government entity custodians in response to Freedom of Information Act (FOIA) requests.  As Losey notes, this is her fifth decision in National Day Laborer Organizing Network et al. v. United States Immigration and Customs Enforcement Agency, et al., including one that was later withdrawn.

Regarding the defendant’s question as to “why custodians could not be trusted to run effective searches of their own files, a skill that most office workers employ on a daily basis” (i.e., self-collect), Judge Scheindlin responded as follows:

“There are two answers to defendants' question. First, custodians cannot 'be trusted to run effective searches,' without providing a detailed description of those searches, because FOIA places a burden on defendants to establish that they have conducted adequate searches; FOIA permits agencies to do so by submitting affidavits that 'contain reasonable specificity of detail rather than merely conclusory statements.' Defendants' counsel recognize that, for over twenty years, courts have required that these affidavits 'set [ ] forth the search terms and the type of search performed.' But, somehow, DHS, ICE, and the FBI have not gotten the message. So it bears repetition: the government will not be able to establish the adequacy of its FOIA searches if it does not record and report the search terms that it used, how it combined them, and whether it searched the full text of documents.”

“The second answer to defendants' question has emerged from scholarship and caselaw only in recent years: most custodians cannot be 'trusted' to run effective searches because designing legally sufficient electronic searches in the discovery or FOIA contexts is not part of their daily responsibilities. Searching for an answer on Google (or Westlaw or Lexis) is very different from searching for all responsive documents in the FOIA or e-discovery context.”

“Simple keyword searching is often not enough: 'Even in the simplest case requiring a search of on-line e-mail, there is no guarantee that using keywords will always prove sufficient.' There is increasingly strong evidence that '[k]eyword search[ing] is not nearly as effective at identifying relevant information as many lawyers would like to believe.' As Judge Andrew Peck — one of this Court's experts in e-discovery — recently put it: 'In too many cases, however, the way lawyers choose keywords is the equivalent of the child's game of 'Go Fish' … keyword searches usually are not very effective.'”

Regarding search best practices and predictive coding, Judge Scheindlin noted:

“There are emerging best practices for dealing with these shortcomings and they are explained in detail elsewhere. There is a 'need for careful thought, quality control, testing, and cooperation with opposing counsel in designing search terms or keywords to be used to produce emails or other electronically stored information.' And beyond the use of keyword search, parties can (and frequently should) rely on latent semantic indexing, statistical probability models, and machine learning tools to find responsive documents.”

“Through iterative learning, these methods (known as 'computer-assisted' or 'predictive' coding) allow humans to teach computers what documents are and are not responsive to a particular FOIA or discovery request and they can significantly increase the effectiveness and efficiency of searches. In short, a review of the literature makes it abundantly clear that a court cannot simply trust the defendant agencies' unsupported assertions that their lay custodians have designed and conducted a reasonable search.”

Losey notes that “A classic analogy is that self-collection is equivalent to the fox guarding the hen house. With her latest opinion, Schiendlin [sic] includes the FBI and other agencies as foxes not to be trusted when it comes to searching their own email.”

So, what do you think?  Will this become another landmark decision by Judge Scheindlin?  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: How Many Requests for User Information is Twitter Receiving? It’s Transparent.
 

As illustrated in the example we posted Tuesday, Twitter continues to receive requests from government agencies for user information (often related to litigation).  How many are they receiving?  Now, you can find out, simply by clicking on their new Transparency Report page to see the number of requests they have received.

Starting for the first six months of this year, Twitter’s report will be issued every six months and provides information in three areas:

  • Government requests received for user information;
  • Government requests received to withhold content; and
  • DMCA takedown notices received from copyright holders.

Twitter provides a table for each category.  For the government requests categories (first two sections), it shows requests by country.  In the User Information Requests table, it’s notable that, out of 849 total user information requests for the first half of 2012, 679 were requested by US government entities (we’re so litigious!).  They also provide stats for percentage of the requests where some or all information was produced and a count of users/accounts specified.  Here are some observations:

  • There were 849 total user information requests for the first half of 2012, 679 coming from US government entities.  The only other countries that had more than 10 requests were: Japan (98), Canada (11) and the United Kingdom (11).
  • Information was produced in 63% of those requests, 75% of the time for US requests.  Interestingly enough, only 20% of Japan’s 98 requests resulted in information produced.
  • The 849 total user information requests for the first half of 2012 specified 1,181 user accounts in those requests, with the 679 US requests specifying 948 user accounts.

Twitter notes that their report is inspired by Google’s own Transparency Report (click here to see their Transparency Report page and here to see user data requests they receive from government agencies and courts for a selected six-month period, starting with July through December 2009).  Early versions of the report don’t show the percentages of user data requests they comply with or the number of users or accounts about which data was requested.  But, it’s interesting to note that since Google began tracking requests, they have risen from greater than 12,539 in July through December 2009 to greater than 18,257 in July through December 2011, a 46% rise in two years.  It will be interesting to see if the number of Twitter requests rises in a similar fashion.  I’m betting yes.

Of course, there’s a protocol to follow if you’re a government entity or law enforcement organization requesting private information from Twitter as we detailed back in April.

So, what do you think?  Is this useful information?  Would you have expected more or less information requests to Twitter?  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: “Tweets” Are Public and Must Be Produced, Judge Rules
 

First, Malcolm Harris tried to quash a subpoena seeking production of his Tweets and his Twitter account user information in his New York criminal case.  That request was rejected, so Twitter then sought to quash the subpoena themselves, claiming that the order to produce the information imposed an “undue burden” on Twitter and even forced it to “violate federal law”.  Now, the criminal court judge has ruled on Twitter’s motion.

On June 30, in People v. Harris, 2011NY080152, New York Criminal Court Judge Matthew Sciarrino Jr. ruled that Twitter must produce tweets and user information of, Harris, an Occupy Wall Street protester, who clashed with New York Police back in October of last year and faces disorderly conduct charges.

Noting that “The court order is not unreasonably burdensome to Twitter, as it does not take much to search and provide the data to the court.”, Judge Sciarrino provided an analogy regarding the privacy of the Twitter account information, as follows:

“Consider the following: a man walks to his window, opens the window, and screams down to a young lady, ‘I'm sorry I hit you, please come back upstairs.’ At trial, the People call a person who was walking across the street at the time this occurred. The prosecutor asks, ‘What did the defendant yell?’ Clearly the answer is relevant and the witness could be compelled to testify. Well today, the street is an online, information superhighway, and the witnesses can be the third party providers like Twitter, Facebook, Instragram, Pinterest, or the next hot social media application.”

Continuing, Judge Sciarrino stated: “If you post a tweet, just like if you scream it out the window, there is no reasonable expectation of privacy. There is no proprietary interest in your tweets, which you have now gifted to the world. This is not the same as a private email, a private direct message, a private chat, or any of the other readily available ways to have a private conversation via the internet that now exist…Those private dialogues would require a warrant based on probable cause in order to access the relevant information.”

Judge Sciarrino indicated that his decision was “partially based on Twitter's then terms of service agreement. After the April 20, 2012 decision, Twitter changed its terms and policy effective May 17, 2012. The newly added portion states that: ‘You Retain Your Right To Any Content You Submit, Post Or Display On Or Through The Service.’”  So, it would be interesting to see if the same ruling would be applied for “tweets” and other information posted after that date.

Judge Sciarrino did note that the government must obtain a search warrant to compel a provider of Electronic Communication Service (“ECS”) to disclose contents of communication in its possession that are in temporary "electronic storage" for 180 days or less (18 USC §2703[a]).  So, he ordered “that Twitter disclose all non-content information and content information from September 15, 2011 to December 30, 2011” related to Harris’ account.

So, what do you think?  Did the judge make the right call or should Twitter have been able to quash the subpoena?  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: TREC Study Finds that Technology Assisted Review is More Cost Effective
 

As reported in Law Technology News (Technology-Assisted Review Boosted in TREC 2011 Results by Evan Koblentz), the Text Retrieval Conference (TREC) Legal Track, a government sponsored project designed to assess the ability of information retrieval techniques to meet the needs of the legal profession, has released its 2011 study results (after several delays).  The overview of the 2011 TREC Legal Track can be found here.

The report concludes the following: “From 2008 through 2011, the results show that the technology-assisted review efforts of several participants achieve recall scores that are about as high as might reasonably be measured using current evaluation methodologies. These efforts require human review of only a fraction of the entire collection, with the consequence that they are far more cost-effective than manual review.” 

However, the report also notes that “There is still plenty of room for improvement in the efficiency and effectiveness of technology-assisted review efforts, and, in particular, the accuracy of intra-review recall estimation tools, so as to support a reasonable decision that 'enough is enough' and to declare the review complete. Commensurate with improvements in review efficiency and effectiveness is the need for improved external evaluation methodologies that address the limitations of those used in the TREC Legal Track and similar efforts.”

Other notable tidbits from the study and article:

  • Ten organizations participated in the 2011 study, including universities from diverse locations such as Beijing and Melbourne and vendors including OpenText and Recommind;
  • Participants were required to rank the entire corpus of 685,592 documents by their estimate of the probability of responsiveness to each of three topics, and also to provide a quantitative estimate of that probability;
  • The document collection used was derived from the EDRM Enron Data Set;
  • The learning task had three distinct topics, each representing a distinct request for production.  A total of 16,999 documents was selected – about 5,600 per topic – to form the “gold standard” for comparing the document collection;
  • OpenText had the top number of documents reviewed compared to recall percentage in the first topic, the University of Waterloo led the second, and Recommind placed best in the third;
  • One of the participants has been barred from future participation in TREC – “It is inappropriate –- and forbidden by the TREC participation agreement –- to claim that the results presented here show that one participant’s system or approach is generally better than another’s. It is also inappropriate to compare the results of TREC 2011 with the results of past TREC Legal Track exercises, as the test conditions as well as the particular techniques and tools employed by the participating teams are not directly comparable. One TREC 2011 Legal Track participant was barred from future participation in TREC for advertising such invalid comparisons”.  According to the LTN article, the barred participant was Recommind.

For more information, check out the links to the article and the study above.  TREC previously announced that there would be no 2012 study and is targeting obtaining a new data set for 2013.

So, what do you think?  Are you surprised by the results or are they expected?  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: Quality Assurance vs. Quality Control and Why Both Are Important in eDiscovery
 

People tend to use the terms Quality Assurance (QA) and Quality Control (QC) interchangeably and it’s a pet peeve of mine.  It’s like using the word “irregardless” – which isn’t really a word.  The fact is that QA and QC are different mechanisms for ensuring quality in…anything.  Products, processes and projects (as well as things that don’t begin with “pro”) are all examples of items that can benefit from quality ensuring mechanisms and those that are related to electronic discovery can particularly benefit.

First, let’s define terms

Quality Assurance (QA) can be defined as planned and systematic activities and mechanisms implemented so that quality requirements for a product or service will be fulfilled.

Quality Control, (QC) can be defined as one or more processes to review the quality of all factors involved in that product or service.

Now, let’s apply the terms to an example in eDiscovery

CloudNine Discovery’s flagship product is OnDemand®, which is an online eDiscovery review application.  It’s easy to use and the leader in self-service, online eDiscovery review (sorry, I’m the marketing director, I can’t help myself).

OnDemand has a team of developers, who use a variety of Quality Assurance mechanisms to ensure the quality of the application.  They include (but are not limited to):

  • Requirements meetings with stakeholders to ensure that all required functionality for each component is clearly defined;
  • Development team “huddles” to discuss progress and to learn from each other’s good development ideas;
  • Back end database and search engine that establish rules for data and searching that data (so, for example, the valid values for whether or not a document is responsive are “True” and “False” and not “Purple”) and;
  • Code management software to keep versions of development code to ensure the developers don’t overwrite each other’s work.

Quality Control mechanisms for OnDemand include:

  • Test plan creation to identify all functional areas of the application that need to be tested;
  • Rigorous testing of all functionality within each software release by a team of software testers;
  • Issue tracking software to track all problems found in testing that allows for assignment to responsible developers and tracking through to completion to address the issue and re-testing to confirm the issue has been adequately addressed;
  • Beta testing by selected clients interested in using the latest new features and willing to provide feedback as to how well those features work and how well they meet their needs.

These QA and QC mechanisms help ensure that OnDemand works correctly and that it provides the functionality required by our clients.  And, we continue to work to make those mechanisms even more effective.

QA & QC mechanisms aren’t just limited to eDiscovery software.  Take the process of conducting attorney review to determine responsiveness and privilege.  QA mechanisms include instructions and background information provided to reviewers up front to get them up to speed on the review process, periodic “huddles” for additional instructions and discussion amongst reviewers to share best practices, assignment of “batches” so that each document is reviewed by one, and only one, reviewer and validation rules to ensure that entries are recorded correctly.  QC mechanisms include a second review (usually by a review supervisor or senior attorney) to ensure that documents are being categorized correctly and metrics reports to ensure that the review team can meet deadlines while still conducting a thorough review.  QA & QC mechanisms can also be applied to preservation, collection, searching and production (among other eDiscovery activities) and they are critical to enabling discovery obligations to be met.

So, what do you think?  What QA & QC mechanisms do you use in your eDiscovery processes?  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: eDiscovery Work is Growing in Law Firms and Corporations
 

There was an article in Law Technology News last Friday (Survey Shows Surge in E-Discovery Work at Law Firms and Corporations, written by Monica Bay) that discussed the findings of a survey released by The Cowen Group, indicating that eDiscovery work in law firms and corporations is growing considerably.  Eighty-eight law firm and corporate law department professionals responded to the survey.

Some of the key findings:

  • 70 percent of law firm respondents reported an increase in workload for their litigation support and eDiscovery departments (compared to 42 percent in the second quarter of 2009);
  • 77 percent of corporate law department respondents reported an increase in workload for their litigation support and eDiscovery departments;
  • 60 percent of respondents anticipate increasing their internal capabilities for eDiscovery;
  • 55 percent of corporate and 62 percent of firm respondents said they "anticipate outsourcing a significant amount of eDiscovery to third-party providers” (some organizations expect to both increase internal capabilities and outsource);
  • 50 percent of the firms believe they will increase technology speeding in the next three months (compared to 31 percent of firms in 2010);
  • 43 percent of firms plan to add people to their litigation support and eDiscovery staff in the next 3 months, compared to 32 percent in 2011;
  • Noting that “corporate legal departments are under increasing pressure to ‘do more with less in-house to keep external costs down’”, only 12 percent of corporate respondents anticipate increasing headcount and 30 percent will increase their technology spend in the next six months;
  • In the past year, 49 percent of law firms and 23 percent of corporations have used Technology Assisted Review/ Predictive Coding technology through a third party service provider – an additional 38 percent have considered using it;
  • As for TAR/Predictive Coding inhouse, 30 percent of firms have an inhouse tool, and an additional 35 percent are considering making the investment.

As managing partner David Cowen notes, “Cases such as Da Silva Moore, Kleen, and Global Aerospace, which have hit our collective consciousness in the past three months, affect the investments in technology that both law firms and corporations are making.”  He concludes the Executive Summary of the report with this advice: “Educate yourself on the latest evolving industry trends, invest in relationships, and be an active participant in helping your executives, your department, and your clients ‘do more with less’.”

So, what do you think?  Do any of those numbers and trends surprise 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 Trends: The Da Silva Moore Case Has Class (Certification, That Is)
 

As noted in an article written by Mark Hamblett in Law Technology News, Judge Andrew Carter of the U.S. District Court for the Southern District of New York has granted conditional class certification in the Da Silva Moore v. Publicis Groupe & MSL Group case.

In this case, women employees of the advertising conglomerate Publicis Groupe and its U.S. subsidiary, MSL, have accused their employer of company-wide discrimination, pregnancy discrimination, and a practice of keeping women at entry-level positions with few opportunities for promotion.

Judge Carter concluded that “Plaintiffs have met their burden by making a modest factual showing to demonstrate that they and potential plaintiffs together were victims of a common policy or plan that violated the law. They submit sufficient information that because of a common pay scale, they were paid wages lower than the wages paid to men for the performance of substantially equal work. The information also reveals that Plaintiffs had similar responsibilities as other professionals with the same title. Defendants may disagree with Plaintiffs' contentions, but the Court cannot hold Plaintiffs to a higher standard simply because it is an EPA action rather an action brought under the FLSA.”

“Courts have conditionally certified classes where the plaintiffs have different job functions,” Judge Carter noted, indicating that “[p]laintiffs have to make a mere showing that they are similarly situated to themselves and the potential opt-in members and Plaintiffs here have accomplished their goal.”

This is just the latest development in this test case for the use of computer-assisted coding to search electronic documents for responsive discovery. On February 24, Magistrate Judge Andrew J. Peck of the U.S. District Court for the Southern District of New York issued an opinion making it likely the first case to accept the use of computer-assisted review of electronically stored information (“ESI”) for this case.  However, on March 13, District Court Judge Andrew L. Carter, Jr. granted plaintiffs’ request to submit additional briefing on their February 22 objections to the ruling.  In that briefing (filed on March 26), the plaintiffs claimed that the protocol approved for predictive coding “risks failing to capture a staggering 65% of the relevant documents in this case” and questioned Judge Peck’s relationship with defense counsel and with the selected vendor for the case, Recommind.

Then, on April 5, Judge Peck issued an order in response to Plaintiffs’ letter requesting his recusal, directing plaintiffs to indicate whether they would file a formal motion for recusal or ask the Court to consider the letter as the motion.  On April 13, (Friday the 13th, that is), the plaintiffs did just that, by formally requesting the recusal of Judge Peck (the defendants issued a response in opposition on April 30).  But, on April 25, Judge Carter issued an opinion and order in the case, upholding Judge Peck’s opinion approving computer-assisted review.

Not done, the plaintiffs filed an objection on May 9 to Judge Peck's rejection of their request to stay discovery pending the resolution of outstanding motions and objections (including the recusal motion, which has yet to be ruled on.  Then, on May 14, Judge Peck issued a stay, stopping defendant MSLGroup's production of electronically stored information.  Finally, on June 15, Judge Peck, in a 56 page opinion and order, denied the plaintiffs’ motion for recusal. 

So, what do you think?  What will happen in this case next?  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: Types Of Metadata and How They Impact Discovery
 

If an electronic document is a “house” for information, then metadata could be considered the “deed” to that house. There is far more to explaining a house than simply the number of stories and the color of trim. It is the data that isn’t apparent to the naked eye that tells the rest of the story. For a house, the deed lines out the name of the buyer, the financier, and the closing date among heaps of other information that form the basis of the property. For an electronic document, it’s not just the content or formatting that holds the key to understanding it. Metadata, which is data about the document, contains information such as the user who created it, creation date, the edit history, and file type. Metadata often tells the rest of the story about the document and, therefore, is often a key focus of eDiscovery, such as in cases like this one we recently covered here.

There are many different types of metadata and it is important to understand each with regard to requesting that metadata in opposing counsel productions and being prepared to produce it in your own productions.  Examples include:

  • Application Metadata: This is the data created by an application, such as Microsoft® Word, that pertains to the ESI (“Electronically Stored Information”) being addressed. It is embedded in the file and moves with it when copied, though copying may alter the application metadata.
  • Document Metadata: These are properties about a document that may not be viewable within the application that created it, but can often be seen through a “Properties” view (for example, Word tracks the author name and total editing time).
  • Email Metadata: Data about the email.  Sometimes, this metadata may not be immediately apparent within the email application that created it (e.g., date and time received). The amount of email metadata available varies depending on the email system utilized.  For example, Outlook has a metadata field that links messages in a thread together which can facilitate review – not all email applications have this data.
  • Embedded Metadata: This metadata is usually hidden; however, it can be a vitally important part of the ESI. Examples of embedded metadata are edit history or notes in a presentation file. These may only be viewable in the original, native file since it is not always extracted during processing and conversion for eDiscovery.
  • File System Metadata: Data generated by the file system, such as Windows, to track key statistics about the file (e.g., name, size, location, etc.) which is usually stored externally from the file itself.
  • User-Added Metadata: Data created by a user while working with, reviewing, or copying a file (such as notes or tracked changes).
  • Vendor-Added Metadata: Data created and maintained by an eDiscovery vendor during processing of the native document.  Don’t be alarmed, it’s impossible to work with some file types without generating some metadata; for example, you can’t review and produce individual emails within a custodian’s Outlook PST file without generating those out as separate emails (either in Outlook MSG format or converted to an image format, such as TIFF or PDF).

Some metadata, such as user-added tracked changes or notes, could be work product that may affect whether a document is responsive or contains privileged information, so it’s important to consider that metadata during review, especially when producing in native format.

So, what do you think? Have you been involved in cases where metadata was specifically requested as part of discovery? 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: You May Need to Collect from Custodians Who Aren’t There
 

A little over a week ago, we talked about how critical the first seven to ten days are in the case once litigation hits.  Key activities to get a jump on the case include creating a list of key employees most likely to have documents relevant to the litigation and interviewing those key employees, as well as key department representatives, such as IT for information about retention and destruction policies.  These steps are especially important as they may shed light on custodians you might not think about – the ones who aren’t there.

No, I’m not talking about the Coen brothers’ movie The Man Who Wasn’t There, starring Billy Bob Thornton, I’m talking about custodians who are no longer with the organization.

Let’s face it, when key employees depart an organization, many of those organizations have a policy in place to preserve their data for a period of time to ensure that any data in their possession that might be critical to company operations is still available if needed.  Preserving that data may occur in a number of ways, including:

  • Saving the employee’s hard drive, either by keeping the drive itself or by backing it up to some other media before wiping it for re-use;
  • Keeping any data in their network store (i.e., folder on the network dedicated to the employee’s files) by backing up that folder or even (in some cases) simply leaving it there for access if needed;
  • Storage and/or archival of eMail from the eMail system;
  • Retention of any portable media in the employee’s possession (including DVDs, portable hard drives, PDAs, cell phones, etc.).

As part of the early fact finding, it’s essential to determine the organization’s retention policy (and practices, especially if there’s no formal policy) for retaining data (such as the examples listed above) of departed employees.  You need to find out if the organization keeps that data, where they keep it, in what format, and for how long.

When interviewing key employees, one of the typical questions to ask is “Do you know of any other employees that may have responsive data to this litigation?”  The first several interviews with employees often identify other employees that need to be interviewed, so the interview list will often grow to locate potentially responsive electronically stored information (ESI).  It’s important to broaden that question to include employees that are no longer with the organization to identify any that also may have had responsive data and try to gather as much information about each departed employee as possible, including the department in which they worked, who their immediate supervisor was and how long they worked at the company.  Often, this information may need to be gathered from Human Resources.

Once you’ve determined which departed employees might have had responsive data and whether the organization may still be retaining any of that data, you can work with IT or whoever has possession of that data to preserve and collect it for litigation purposes.  Just because they aren’t there doesn’t mean they’re not important.

So, what do you think?  Does your approach for identifying and collecting from custodians include those who aren’t there?  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: First Pass Review – Domain Categorization of Your Opponent’s Data
 

Even those of us at eDiscoveryDaily have to take an occasional vacation; however, instead of “going dark” for the week, we thought we would republish a post series from the early days of the blog (when we didn’t have many readers yet)  So chances are, you haven’t seen these posts yet!  Enjoy!

Yesterday, we talked about the use of First Pass Review (FPR) applications (such as FirstPass®, powered by Venio FPR™) to not only conduct first pass review of your own collection, but also to analyze your opponent’s ESI production.  One way to analyze that data is through “fuzzy” searching to find misspellings or OCR errors in an opponent’s produced ESI.

Domain Categorization

Another type of analysis is the use of domain categorization.  Email is generally the biggest component of most ESI collections and each participant in an email communication belongs to a domain associated with the email server that manages their email.

FirstPass supports domain categorization by providing a list of domains associated with the ESI collection being reviewed, with a count for each domain that appears in emails in the collection.  Domain categorization provides several benefits when reviewing your opponent’s ESI:

  • Non-Responsive Produced ESI: Domains in the list that are obviously non-responsive to the case can be quickly identified and all messages associated with those domains can be “group-tagged” as non-responsive.  If a significant percentage of files are identified as non-responsive, that may be a sign that your opponent is trying to “bury you with paper” (albeit electronic).
  • Inadvertent Disclosures: If there are any emails associated with outside counsel’s domain, they could be inadvertent disclosures of attorney work product or attorney-client privileged communications.  If so, you can then address those according to the agreed-upon process for handling inadvertent disclosures and clawback of same.
  • Issue Identification: Messages associated with certain parties might be related to specific issues (e.g., an alleged design flaw of a specific subcontractor’s product), so domain categorization can isolate those messages more quickly.

In summary, there are several ways to use first pass review tools, like FirstPass, for reviewing your opponent’s ESI production, including: email analytics, synonym searching, fuzzy searching and domain categorization.  First pass review isn’t just for your own production; it’s also an effective process to quickly evaluate your opponent’s production.

So, what do you think?  Have you used first pass review tools to assess an opponent’s produced ESI?  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.