Wednesday, April 18, 2012, 8:00 am PT / 11:00 am ET

To understand why compliance tops the list of business concerns, just look at the headlines: fraud, data theft, lost information, corporate espionage, and leaks. The costs and risks of unmanaged content are staggering. EMC can help you identify and protect costly and potentially risky content throughout your organization so you can avoid the consequences of unmanaged information and meet compliance requirements.

Attend this webcast and learn how you can extend your current EMC solutions to:

Reduce the costs associated with managing unstructured content

Mitigate risk by identifying and securing content based on its value to the organization

Ensure compliance by automatically enforcing policies that govern access and retention—inside and outside the enterprise

Speakers:

Garth Landers
Director, Cross Category Marketing, EMC Information Intelligence Group

Lori McKellar
Director, Product Marketing,  EMC Information Intelligence Group

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Thursday, March 22, 2012
Networking & breakfast: 8:00 – 8:30 a.m. EST
Program: 8:30 – 10:00 a.m. EST

Register>>>

Location: Venable LLP
Rockefeller Center 1270 Avenue of the Americas (between 50th and 51st Streets)
Twenty-Fourth Floor New York, NY 10020

Speakers: Edwin M. Larkin, Esq. Partner at Venable LLP, James E. Nelson, Esq.
Partner at Venable LLP, James D. Shook, Esq.  Director of the eDiscovery and Compliance Team at EMC Corporation

In litigation matters, you are responsible for any relevant data that is in your “care, custody or control.” But what happens when that data is stored in “The Cloud”? Under such conditions, traditional notions of ownership and control no longer apply in the same manner as they have for physical goods, such as paper documents. What happens to your data – and your obligation to a court or regulator – when that provider will no longer access “your” data because they have terminated your account for non-payment or alleged mis-use? What if your provider needs 3 weeks to collect your data, but you have to respond within 3 days?

Join our panelists for a thought-provoking discussion in which we will discuss: the basic framework of regulatory and compliance issues that you need to know when you entrust your data with a third party;
questions to ask and contract terms to consider when you are entering into a “cloud” agreement; and
different types of cloud models to consider that might fit your needs.

Register>>>>

For questions about this event, please contact Dawn M. Mixon at DMMixon@Venable.com

Heidi Maher, Esq., eDiscovery Expert

At a recent a conference for compliance and IT professionals working in the state government sector, it quickly become evident that one of their main concerns was the tremendous increase in the number of open records requests that they have to deal with.   Both the federal and state governments give much lip service to the theory of transparency but few have made the necessary changes to properly deal with the onslaught of requests that appear almost daily.  Wisconsin’s Governor, Scott Walker’s administration has already produced 60,586 pages of open records in response to 222 requests in 13 months.  Compare that to 312 requests filled during the previous governor’s first 4 years[1].  It’s not just Wisconsin that is dealing with an explosion of open records and FOIA requests.  The U.S. Department of Defense received 67,434 in 2009 compared to 74,573 in 2010 and the National Archives and Records administration received 14,075 in 2008 compared to 18,129 in 2011[2].  Most government entities handle open records requests the same as they handle eDiscovery for litigation, manually and on an ad hoc basis.  Unfortunately for government agencies, the turnaround for a response is much quicker than for litigation.  Federal agencies have a statutory requirement to respond to requests within 20 business days [3].  State agencies have time limits ranging from 10-30 days or within “a reasonable time.”  For this reason, IT departments are struggling to keep up and there is a substantial backlog at most agencies.

Adding to their concerns, metadata could be a factor in public disclosure requests. Within the hard drive of any standard computer, metadata is created with each underlying electronic document. Metadata describes the document’s history, tracking and management. In Arizona and Washington that metadata, when requested, is now also subject to a public disclosure, along with the underlying document itself.  On a national level, a ruling by Judge Scheindlin in February of 2011 stated that responses by the federal government to FOIA requests must include metadata and be in a searchable format [4].  Although, she withdrew her opinion later that year (she said it was not based on a full and complete record), her original ruling will undoubtedly influence other courts grappling with public disclosure disputes, especially as they become more technologically savvy.

At this same conference, we heard from the CIO of a large state agency who revealed the tremendous cost of dealing with open records requests especially in a year where his agency has been the subject of several news stories and litigation [5].  The agency took several steps to reduce the cost and time associated in responding to these requests.  The first step was to perform file remediation on data that was not a record and met no legal, regulatory or business requirement for retention.  Next, they began the process of implementing an email archive in order to enforce retention and have one repository of record for all emails instead of dealing with local email storage on each hardware device.  In the meantime, they have installed in-house search technology that has allowed the agency to find and copy the requested information in a matter of minutes whereas the same action used to take several days.  When the occasional litigation notice came through, they have been able to utilize the same technology to put the requested information on hold.

Another concern for government agencies is the prospect of moving some or all of their data to the cloud. In fact, federal agencies were directed by President Obama to consider cloud based services or storage systems for records keeping [6].  The challenge then becomes how to facilitate cloud management of that information while still responding quickly to public record requests.  Any agency contemplating that move must ensure that the data being managed by the cloud provider is maintained in an easily accessible manner and that the provider is contractually bound to have technology in place for easy and fast retrieval of data for responding to eDiscovery.  Otherwise each request may be billed as a special project and the cost savings initially realized can quickly dissipate.

A possible step in the right direction is the common web portal for FOIA requests launching in the fall of 2012.  According to The FOIA Ombudsman, the $1.3 million portal, being built mostly with funds from the Environmental Protection Agency and the Commerce Department, with some participation from NARA, could save the federal government $200 million over 5 years were it to be adopted government wide[7].  This is a big step toward giving the public a self service model (similar to a tool utilized by government agencies in Mexico[8]).  However a portal is only as good as the data behind it so only time will tell if this can serve as a national model.

Although the government is notoriously behind the private sector in modernizing its technology, the public’s need for an open and transparent government does appear to be speeding up the process to the benefit of agency budgets and more importantly, the taxpaying public.

[1] http://bit.ly/z1x2hf

[2] http://www.foia.gov/

[3] 5 U.S.C. § 552(a)(6)(A)

[4] Nat. Day Laborer Org. Network v. U.S. Immigration and Customs Enforcement Agency (“NDLON”) 2011 WL 381625 (S.D.N.Y. Feb. 7, 2011)

[5] While public disclosure rules allow for collecting fees and recovering costs, some requesters who qualify for placement in favored fee categories may be charged less or may not be charged at all. Educational, news media and noncommercial scientific requesters typically pay no search or review fees and only duplication costs after a certain number of pages (usually 100 or more).  The amount of paper that is created by these responses is unacceptable.  Taxpayers are right to question why so much of their money is spent creating paper documents when 93%+ of all communication is in an electronic format (David W. Degnan, Accessing Arizona’s Government: Open Records Requests for Metadata and other Electronically Stored Information after Lake v. Phoenix, 3 Phoenix L. Rev. 69 (2010)).

[6] http://www.whitehouse.gov/the-press-office/2011/11/28/presidential-memorandum-managing-government-records

[7] http://blogs.archives.gov/foiablog/2012/01/09/foia-portal-moving-from-idea-to-reality/

[8] http://indices.ifai.org.mx/wb2, also http://www.dhs.gov/xlibrary/assets/privacy/privacy_wkshop_04-2006_personal.pdf

James D. Shook, Esq., EMC eDiscovery Expert

By James D. Shook, Esq.

In light of Magistrate Judge Andrew Peck’s recent decision in Da Silva Moore v. Publicis, much has been written and discussed about the idea of using machine learning techniques to automatically classify documents during review, a process sometimes known as “predictive coding” or even “computer assisted review”.    (Although these terms may actually imply different technologies and processes this article adopts Judge Peck’s umbrella use of the term “predictive coding”).  This article explores some of the key issues around this promising intersection of law and technology.

What Is Predictive Coding?  How is It Used?

At a simple level, predictive coding is just a technological “lever” that allows a (relatively) small amount of review work – usually by humans — to be leveraged across a much larger set of documents.  Let’s say that we have a class action where the identification phase of eDiscovery has located about twenty million electronically stored information (ESI) items – email messages, word processing files, spreadsheets, powerpoint presentations, etc. – that are likely to be relevant, discoverable information for the issues in our case.

Traditionally, we have had a few choices about what to with all of this ESI.  First, we could just hand it all over to the other party without reviewing any of it for actual relevance or even privilege.  Second, we could negotiate search terms with the other side, which we would then run against the ESI in an attempt to locate the most relevant information.  All non-privileged ESI that was a “hit” with the search terms would be handed over to the other side.  Third, we could have human reviewers reach each item to determine what is relevant (and non-privileged), and then produce that information.  Each of these approaches has its benefits and problems, including the amount of time that the process takes, the cost of reviewing millions of items, the validity and usefulness of the process, etc.

With predictive coding, we have another choice to help determine what information is relevant.  In this approach, we carefully review a small subset of the 20,000,000 item set – maybe as few as 2,500 items depending upon the margin of error that we can tolerate in our result.  We then use predictive coding technology to “learn” from that set, applying that “knowledge” to the remaining 19,997,500 items.

Is Predictive Coding Worth the Trouble?

The effective use of predictive coding impacts the litigation process by substantially reducing the cost and time for review.   In our example, in applying a predictive coding process we might manually review just 2,500 documents of the 20,000,000 set, depending on the specific technology, case requirements and tolerance for potential errors.  If we assume a cost of $5 per document for high-level manual review (by a more experienced attorney) and just $0.50 for bulk review (by contract attorneys and paralegals), we would spend about $12,500 in review (plus the costs of the predictive coding technology process).  This cost is in stark contrast to a complete manual review – which in this case could cost up to $10,000,000!  (Note that in Da Silva, there were about 3.2 million documents.  At one point the parties estimated a cost of $5 document to produce a projected set of 40,000 documents.  Hearing Transcript at 62; Order at 6).

The predictive coding process takes less time because the computers handling the review are much faster, more consistent and can work longer hours than people.  If we assume a review rate of two documents per minute, then the manual phase of our predictive coding process requires about 2 people-days (the machine-based review would come after this phase).  In contrast, a complete, eyes-on review process would take 20,833 people-days!  Even with a large team of 100 reviewers, that process would take over 200 working days and require strong project management to complete properly.

Perhaps more important, according to recent studies the predictive coding process is also more effective than human or keyword review.  Unfortunately, it is difficult to determine the true accuracy of human review because opinions, even among experts, can vary on whether a document is relevant to a case.  (Maura Grossman & Gordon Cormack, Technology-Assisted Review in E-Discovery Can Be More Effective and More Efficient Than Exhaustive Manual Review, XVII Rich. J.L. & Tech. 11 92011 at 9).  But the bulk of available information implies that machine coding is better.  In fact, some studies put a human reviewer’s recall– the percentage of relevant documents actually located – at less than 50%.  The use of basic keywords is even worse, dropping recall to about 25%.  (Grossman/Cormack at 18-19).  Some predictive coding studies indicate that the process is far more accurate, in the range of 70% recall (Grossman/Cormack at 36-37).  Given the lower cost and speed, recall that’s even close to the human level should be acceptable.  (Note that other measures, such as precision and F1 (the harmonic mean of recall and precision) – are also important in this process.  For more information see Grossman/Cormack at 9).

What are the Barriers to Using Predictive Coding?

Despite Judge Peck’s opinion, there are number of real-world barriers to using predictive coding on a regular basis:

-        The underlying technology and math can appear complicated, and Judges and lawyers may not jump at the chance to use predictive coding until they better understand the process and there is more guidance from the bench on when and how to use it.  Although Judge Peck has stated that the requirements of Daubert do not apply to predictive coding, there remains a comfort level and learning curve that will probably take some time to achieve;

-        There are not yet many studies establishing that predictive coding is better than human or keyword review, even though many believe that is the case.  Further, “predictive coding” is just an umbrella term for

-        There is not a clear process of how to approach the problem when one side wants to use predictive coding by is opposed by the other party.  In Da Silva Moore v. Publicis, both parties agreed to use predictive coding and Judge Peck’s order addresses issues related to the protocol and process of how it is to be used in the case.  However, in Kleen Products LLC v. Packaging Corp. of America, Magistrate Judge Nan Nolan will be focusing on that issue:  can a party require computer-assisted review over the objection of another party?  Stay tuned — Kleen Products has another hearing scheduled for April 2012.

What Are the Barriers to Not Using Predictive Coding?

Interestingly, the continued massive growth of data may ultimately force the use of predictive coding technologies.  IDC projects that most companies will be dealing with 50 times the amount of data in 2020 than they had in 2011. People working in the eDiscovery industry also know that most cases today ignore many potentially relevant repositories of data, either by agreement or thru lacking of knowledge.  If the additional repositories are included, along with the enormous projected growth of data, it’s likely that the amount of ESI in many cases will soon be too expensive for “normal” review by humans — or it will take too long.

In addition, while it may seem farfetched today, the requirements of proportionality could soon mandate that parties use predictive coding technologies to insure that the litigation process remains just, speedy, and inexpensive.

What is the Future?

With cases like Kleen Products on the near horizon, it seems likely that we will be receiving some judicial guidance on predictive coding over the next year.  That’s certainly good news, as the more guidance we receive, the more likely that lawyers and litigants grow more comfortable with the process.

In addition, predictive coding technologies show promise outside of the litigation process to help with our information management overload issues.  Imagine training your email, fileshare or Sharepoint archive, or even your records management system, to recognize and automatically classify information as it is received or created.  “I’ll get milk on the way home” messages could be flagged for quick deletion, while employee reviews, contract modifications and other records could be stored according to your file classification plan.  (This technology already exists; improvements, higher comfort level and better understanding of the technologies caused by their use in litigation will help with the adoption rate).

For more, check out the references in “Dive Into Machine Classification and Coding”, part of my New Year’s Wish list. 

Rounding Up the 10 Biggest IP Litigation Wins of 2011

Today, many organizations are looking to the Cloud for answers for controlling escalating information management costs.  However, organizations cannot just be focused on the perceived information technology infrastructure cost savings offered by the Cloud.  Organizations must be equally focused on laws, regulations and information governance issues.  If your organization has governance issues currently, then the Cloud will only exacerbate them.  Discover what the Cloud means to others and why it’s critical to place Pervasive Governance ahead of any Cloud initiative in your organization.

Speakers:

Fiona Schrader, Principle Product Manager Records Retention, Compliance, and Governance

Tom Reding, CRM, EMC – Principal eDiscovery and Compliance Practice

William O’Neil, Jr., Esq., EMC – Principal eDiscovery and Compliance Practice

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The case for using machine coding and classification of documents in the eDiscovery review process has never been stronger.  As costs and ESI volumes continue to grow, machine coding promises faster, cheaper – and better.  Yet there remain many concerns about how to properly use these technologies, and the potential for risk when used incorrectly.  Hear what a prominent member of the Judiciary and members of the Bar have to say about the promising future – and their concerns for reaching it.

Speakers:

Honorable Andrew J. Peck

Ed Larkin, Esq., Partner, Venable LLP

James D. Shook, Esq., Director of Compliance and eDiscovery team EMC

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Search has become a cornerstone of all legal technology, from legal research to early case assessment to document review. As search becomes more accessible, it also becomes more powerful, requiring experts in the technology to take full advantage of the available tools. There is still a gap though, as search methodologies used in different stages of a case are vastly different. Case teams need to assess what strategies must be used, engage experts in both subject matter and search technology, and be aware of potential pitfalls. This session will provide attendees an opportunity to hear from experts in the field, preparing them to tackle search more effectively in their own cases.

Speakers:

Charlie Kaupp, eDiscovery Consultant, Digital Strata, Inc.

Don C. McLaughlin, Jr., Esq., President and CEO, Falcon Discovery

Dan Brassil, Principal Consultant, H5

Kenneth Rashbaum –  Rashbaum Associates LLC

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“Although the FRCP amendments were enacted back in late 2006, their practical application is an evolving process for business, information technology, and legal professionals, as both  Discovery technologies and case law mature.”, notes David Yerich, Esq., Director of eDiscovery at Minneapolis based UnitedHealth Group and Advisory Board Member of CEDS.  “At its core eDiscovery is about technology, and technology is constantly evolving.  Taking a wait-and-see strategy, for the proverbial eDiscovery dust to settle, before addressing an organization’s litigation needs around electronically stored information (ESI), isn’t a good risk reduction strategy.  Judicial eDiscovery expectations around handling the ever changing types of ESI continue to increase. So by remaining static and not moving your organization forward, you are actually falling behind.”  Yerich notes that LegalTech is a great event to explore and learn about these risks, and potential ways to help minimize them.  “The LegalTech event offers a huge number of opportunities to discuss emerging legal challenges, showcase new technologies, and share best practices, so frontline business managers can develop concrete plans to help reduce litigation exposure in managing ESI.  I’m looking forward to attending.”

The LegalTech Session:

Overcoming the FUD to Bring More e-Discovery In-House   10:30 am – 11:30 am

Bringing more of the eDiscovery process in-house can result in substantial savings and better control over the process.  Yet many corporate IT and in-house counsel are afraid to assume the responsibility for the process.  Listen to a panel of experts discuss the most common concerns and how to overcome them to improve your process.

Speakers:

David Yerich, Esq., Director of eDiscovery, UnitedHealth Group

Ian Campbell, Co-founder and Chief Business Development Officer, iCONECT Development, LLC

James D. Shook, Esq., Director eDiscovery and Compliance Practice,  EMC Corp.

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