All posts tagged EDA

The Five Biggest Ediscovery Issues to Watch in 2014

1. Converging tools and processes blur lines between early data assessment (EDA) and review

Does an organization really need two separate tools for EDA and review? For over 15 years, organizations have been adopting litigation technologies a la carte (e.g., a review tool) that solve maybe one piece of a much larger ediscovery puzzle. Only now are practitioners finally stepping back to see the forest for the trees: this cycle of one-off adoption has bred a lot of inefficiency.  Every time electronically stored information (ESI) is exported, processed, and ingested into a different tool downstream, time and money is lost. If one tool empowered legal teams to filter, test and review in one place, many of these inefficiencies could be reduced. With an eye toward repeatability and long-term project management, expect industry leaders in 2014 to critically reexamine what is—and, perhaps more importantly, what is not—really necessary to react to ediscovery.

2.       The lack of legal avenues to shift ediscovery costs will become unavoidable

One of the biggest concerns ediscovery experts voiced in 2013 was that there are no well-paved paths for seeking ediscovery costs in court. In 2013, the Fourth and Federal Circuit joined the Race Tires America court in reasoning that 28 U.S.C.  § 1940(4) only applies to ediscovery functions that can be construed as “exemplification” or “making copies”—thereby excluding the bulk of ediscovery costs. At the same time, the rules espoused in Zubulake III and found in Federal Rule 26(b)(2)(B) are conditioned on a finding of some level of data inaccessibility, which, quite frankly, is becoming less of a problem than the gobs and gobs of accessible data increasingly wreaking havoc on producing parties. In 2014, expect more legal professionals to take issue with this rigid cost-shifting framework. Given the emphasis on increased proportionality radiating from the current federal rulemaking efforts, courts will probably become more creative and comfortable using less clear forms of authority and clever ESI protocols to rein in disproportionate discovery.

3.       Search law will move forward

One issue left in the wake of Da Silva Moore is whether a party may obtain discovery of training decisions made during the machine learning stage of a predictive coding case. The court in In re Biomet tackled this question for the first time in 2013, reasoning that a party’s request for the identification of coding decisions made on training documents was unfounded because parties are not permitted discovery of irrelevant and potentially privileged documents. Touching on the permissible bounds of the work product doctrine as it applies to the most talked about next-gen review tool, this exemplifies the type of intricate search dispute that will likely be opinion worthy in 2014. Because district courts from independent circuits so often look to each other for support in ediscovery opinions, it wouldn’t be surprising to see this hot-button issue revisited multiple times in the new year.

4.       Proposed amendments to the Federal Rules shake up preservation and sanctions standards

There is undeniable inconsistency across the nation with regard to the culpability standards required for different levels of spoliation sanctions. Proposed Federal Rule 37(e)—one of a handful of ediscovery amendments under public commentary—essentially replaces this inconsistency by requiring a showing of substantial prejudice plus willfulness or bad faith to allot serious sanctions. This is a higher standard than those imposed in many circuits and notably forecloses courts from issuing serious sanctions where gross negligence or negligence resulted in the loss of potentially relevant ESI. Despite the fact that the Committee on Rules of Practice and Procedure wants to wrap up this process by early 2015, many question whether any of these amendments will actually change anything, while others wonder whether the threshold for serious sanctions as espoused by Proposed Rule 37(e) has been set too high.

 5.       Predictive coding will become a question of when, not if

Predictive coding has been around since 2010. It was first endorsed for use in the ‘right cases’ in Da Silva Moore and was later ordered to be used sua sponte in EOHRB. In 2013, courts went even further by: (1) accepting—over the opposition’s objection—a party’s decision to apply predictive coding after culling the majority of a data set with keyword search (In re Biomet), and (2) opining that disclosure of training documents was not required (In re Biomet). Outside of the judicial arena, the notion of curbing costs with modern technology has spurred amendments to the ABA Model Rules, proposed amendments to many provisions of the Federal Rules, and amendments to several state rules of civil procedure (e.g., Minnesota). If one looks to recent commentary about how to really get to the nub of proportionate discovery, predictive coding is increasingly being offered as a potential answer. While 2014 probably won’t be the year this technology goes mainstream, massive change has probably become inevitable.

What Do Robin Thicke and the EDRM Have in Common?

The answer: blurred lines.

…Okay, now that I have your attention, I should note that post doesn’t really have anything to do with the controversial and provocative Robin Thicke song that was all over the airwaves this summer. Instead, I’m talking about two equally appealing topics (at least to those in ediscovery): Early Data Assessment (EDA) and Technology Assisted Review.

We have written a lot lately about ways to cut ediscovery costs, and both EDA and TAR (or predictive coding) are keys to reducing costs and maximizing ediscovery efficiencies. While both tools empower attorneys to build a better picture of the data and documents involved in a case, TAR solutions are often viewed as wholly separate tools. However, many practitioners now employ TAR at various stages of the EDRM workflow, and TAR often performs the analysis that is so imperative to the EDA process. Practically, TAR is a complimentary tool that enhances EDA, rather than a standalone solution.

For a more critical analysis this evolution, be sure to attend Analysis 360: Blurring the Lines Between EDA and TAR on November 20, hosted by Anthony J. Diana, partner at Mayer Brown, and Jonathan Sachs, Account Executive at Kroll Ontrack.

A Quick and Dirty Guide to Ediscovery Project Management (Part 2)

Ediscovery Project Management - EDRM

In a complicated litigation landscape, it’s a relief that ediscovery project management (EDPM) and the Electronic Discovery Reference Model (EDRM) fit together. An effective project manager will consider each stage of the EDRM, from identification to production, when creating the perfect ediscovery game plan for the given set of circumstances. Let’s take a look at the most important stages of the EDRM from a project management standpoint.


Project managers are key players in coordinating the effort to identify all data that may be potentially relevant to a specific matter. Ask specific questions of document custodians and walk through a comprehensive list of business and personal data sources – if a device has memory, keep it in your purview. In Coleman (Parent) Holdings v. Morgan Stanley, a 2005 Florida case, Morgan Stanley was unaware of where it stored its electronic data, and was thus sanctioned for discovery abuses. Morgan Stanley faced compensatory and punitive damages to the tune of $1.4 billion. It’s an extreme example, but nonetheless a pertinent one that shows what effective ediscovery project management should avoid.

 Collection & Preservation

This stage of the EDRM is the origin of many “gotchas” in the ediscovery process. It is certainly where most judicial sanctions stem from in the ediscovery realm. Project managers can help guide their organization and document custodians to a successful avoidance of preservation sanctions by ensuring that they know and comply with their obligations pertaining to a litigation hold. They may also play a key role in implementing and managing the organization’s overall retention plan before and during litigation.

 Early Data Assessment (EDA)

By this point in the ediscovery process, the body of knowledge that project managers have gained in coordinating the matter may qualify them as a subject matter expert and an invaluable resource to the legal analysis team. During the EDA process, ED project managers wear many hats and perform many functions. They often work with attorneys, other litigation support professionals and third party providers to separate data between critical and non-critical data groups, narrow the number of key players/custodians, test key search terms,  and identify critical case arguments.

 Review/Technology-assisted Review

Technology-assisted Review (TAR) is one of the most cost-effective, consistent and accurate methods by which to distill the mountains of data inevitably unearthed during major litigation or investigations. To connect back to the EDPM framework discussed in Part I of this post, project managers serve well to promote TAR when discussing process, budget and cost.


So, you’ve finally reached the glorious end of your ediscovery project – production! Project managers (depending on where they sit) function as a useful link between the organization, counsel and the third party ediscovery provider. Many ED project managers are responsible for actually creating and validating productions. They may also ensure that the finished product gets delivered promptly and in its entirety to the appropriate party(ies).

The ABC’s of EDA vs. ECA in Ediscovery – It’s as easy as 1,2,3, right?

The ABC’s of EDA vs. ECA in Ediscovery – It’s as easy as 1,2,3, right?

Now, now, now, I’m gonna teach you

Teach you, teach you

All about love, dear, all about love

Sit yourself down, take a seat

All you gotta do is repeat after me


Abc, easy as 123

Or simple as do, re, mi

Abc, 123, baby, you and me


Michael Jackson, my childhood heartthrob (and okay, maybe my adult heartthrob, too), tried to teach us the ABC’s of love back in the 1970’s.  According to MJ, love was as easy as ABC….right.

Just as love is more complicated than ABC, so is ediscovery – especially when it comes to early assessment of your data….or is it early assessment of your case?  EDA v. ECA — Why does it seem that these two terms are used interchangeably in ediscovery circles?  Is there really an important difference?

Understanding the Differences

The difference between EDA (early data assessment) and ECA (early case assessment) is subtle, but critically important.  Whereas ECA involves the entire legal matter—before discovery and beyond data analysis—EDA is a smaller subset, isolated to discovery activities. For example, ECA encompasses fact finding, venue research, liability analysis, damage assessment, adversary investigation, and litigation budget forecasting.  EDA, on the other hand, aids in fact-finding and narrows the scope of important data early on. During the process of EDA, data is separated between critical and non-critical groupings, the number of key players is narrowed, key search terms are tested, and critical case arguments are identified.  A robust EDA strategy (especially if data volumes are immense) usually involves ediscovery technology – a platform with searching, foldering, clustering, topic grouping, email threading, and maybe even predictive coding (or TAR) capabilities.  However, EDA is more than a technology—it is a methodology that involves people, processes, and the right technology. By using EDA, organizations tasked with the production of documents are able to drastically narrow immense fields of potentially relevant information into smaller, refined clusters of pertinent data. That data can then be feasibly analyzed with test search terms and other input parameters.

So, even though one small letter distinguishes EDA from ECA, the differences are significant to ediscovery practitioners.  Early assessment of data volumes in a matter is as critical to the case strategy as ABC and definitely more complicated than 123.

Asynchronous Search? Increase Your Flexibility

Asynchronous Search? Increase Your Flexibility

Running a search in a large data set and expecting a ton of results? Rather than waiting for results to generate, in Ontrack Inview, Ontrack Advanceview, Verve EDA and Verve Review you can opt to run a search in the background while you do additional work in the application—granting you greater flexibility while the asynchronous search culls your data set.

To run a search in the background, use the Search Wizard by following these steps:

  1. On the Home tab, click Search to start a new search
  2. Specify your search criteria in the Query tab
    1. Enter a name for the search
    2. Determine whether you’re searching text, metadata, or both
    3. Enter your search terms in the Terms and Connectors section
  3. Select Run search in background to run an asynchronous search.
  4. Click Search to begin

You can continue working in the application once your search criteria is analyzed and the search is ready to begin. Once your search has been analyzed, it will appear under the Searches folder in the Document Reviewers pane. Once your asynchronous search begins running, you will be able to tell whether your search was complete by checking for one of two icons in front of the specified search folder:

Description: C:\Users\mthompson\Desktop\Capture.JPG

While your search is running in the background, you will not be able to view results until the search is complete. To update the status of an “in progress” folder, simply right click it to refresh the status of your search folder.Once your search is completed, you will have full access to all results and reports on the search.

Next time you need to cull down data with a broad keyword search, consider running an asynchronous search to cut out the wait and maximize your efficiency.

For additional help, see your User Guide or contact your Case Manager at 1-800-347-6105.

Early Data Assessment – Too Valuable To Ignore

Electronic discovery continues to be viewed as one of the most expensive parts of litigation.

Upon recognition that electronically stored information (ESI) grows more exorbitant as the information and technology bubble expands, attorneys must be attuned to essential ediscovery savings available through the utilization of advanced technologies, including early data assessment (EDA). Using EDA to reduce data before proceeding with data review and processing can corral discovery costs, allow for greater efficiency and increase defensibility in the courtroom. Through EDA, counsel can conduct a true “assessment” of the data before making strategic decisions and incurring costs that may prove to be unnecessary.

EDA as an Advantage

The first vital step in reducing litigation costs can be accomplished by narrowing the scope of potentially relevant data. Because attorneys who are involved in complex litigation struggle to review epic volumes of ESI, reducing the number of custodians prior to document review substantially minimizes review efforts later. In doing so, attorneys need to “weed out” irrelevant custodians and maintain only the pertinent custodian files. An overall reduction in the number of custodians decreases the amount of electronic files, which diminishes time associated with data processing and allows for greater expense forecasting.

When using EDA, also take advantage of email analytics – a technology-enabled process where emails in the document set are organized and analyzed. This process recognizes and visually represents relationships between people, events, timelines and communication patterns through advanced visualizations. By representing data in this fashion, people involved in the ediscovery process can analyze emails quickly, form legal case strategy, investigate any potential internal incidents and intelligently collect data in preparation for discovery.

Important Advanced Searching Techniques

A proper EDA tool will also include advanced features such as concept searching, topic grouping, email threading and near-duplication that will allow for a quicker, more efficient and accurate review of the data sets. Using these tools prior to exporting the data for review will further aid in narrowing data sets to save money during the document review process.

Concept searching allows a user to enter a keyword or phrase and obtain conceptually related items. Using this search technique can identify associated terms and concepts, even if they do not match exact search terms. This technological capability delivers faster and more accurate results than conventional searches. For example, in the case of litigation related to the crash of a Boeing 727 aircraft, a query for that phrase would also retrieve documents concerning “Boeing,” “77,” “B77,” “airliner,” “plane” and other pertinent topics without having to search for each permutation individually. The search may also turn up technical terms associated with the structure of the aircraft or other crashes, even if the user is not familiar with those terms and would therefore not be able to search on them.

Another advanced searching technique is topic grouping, which groups similar documents together while labeling them for quick identification. With this technique, users do not need to “seed” the processing engine by providing keywords. Likewise, email threading also allows for greater efficiency in the identification process, by allowing users to identify, group and review email conversations based on content. Using the actual content of the emails to identify threads is a reliable method, as it will not fail to recognize a thread if the subject line changes or if emails are exchanged across different email applications.

Finally, users can also use near-duplication technology to identify and compare documents that are very similar to one another, but are not exact duplicates. This technology assesses the document set’s similarities, identifying the most uniquely representative documents as “the core.” All related documents are then grouped around the core, allowing the user to engage in a side-by-side comparison of the data to quickly determine whether the near-duplicate documents in the set can be discarded as irrelevant, or whether the differences should be reviewed.

Preparing for the Rule 26(f) Conference

Using EDA also aids in preparation for the Rule 26(f) conference. Using visualization, search and reporting features to identify relevant custodians and formulate keyword and date criteria for filtering can inform and support counsel’s arguments on whether and how to reduce or augment the scope of the discovery. Search features allow counsel to test out proposed filtering criteria before they commit to using it in their case. They allow counsel to determine whether a given search term is over- or under-inclusive, or will result in a multitude of false hits. In addition, EDA reporting features can be used to quantify the number of documents or GBs that are responsive to certain keyword or date criteria and thereby estimate the corresponding ediscovery costs that would likely be incurred to process, review and produce those documents. Visualization features can also be used to identify and prioritize custodians for discovery, bolstering arguments for or against the necessity of preservation of data held by certain custodians.


Litigation is a strategic endeavor, but EDA cultivates information shortcuts that prove fertile to subsequent discovery processes. Although discovery consumes most of the costs associated with litigation, those costs can be mitigated by effective case strategy and data-narrowing efforts. EDA not only increases defensibility, but also reduces cost and promotes efficiency in the long run, and any reduction in the amount of electronic data that must be reviewed translates to immediate and sizeable cost reductions.