24h-payday

Posts Tagged ‘defensibility’

Yet Another Victory: Court Rejects Sanctions for eDiscovery “Shortcomings”

Wednesday, May 29th, 2013

The news surrounding the eDiscovery industry is trending positive for organizations. Instances where companies have been sanctioned for alleged failures to preserve or produce electronically stored information (ESI) seem to be dropping. This is confirmed by various court opinions from 2012, together with reports from key industry players. In addition, the Civil Rules Advisory Committee is close to releasing for public comment draft amendments to Federal Rule of Civil Procedure 37(e) that might impact the sanctions equation. If enacted, the proposed changes could reduce the threat of sanctions relating to pre-litigation destruction of ESI.

Against this backdrop, organizations scored another sanctions victory this month as an Albany, New York-based federal court refused to impose sanctions on an enterprise for its so-called eDiscovery “shortcomings.” In Research Foundation of State University of New York v. Nektar Therapeutics, the defendant had sought an adverse inference instruction and monetary sanctions against the research foundation arm of the State University of New York for its alleged “grossly negligent” failure to preserve documents. The defendant argued that such punishment was justified given the foundation’s alleged failures to implement a timely litigation hold, to maintain “relevant backup-tape data” and to “suspend its auto-delete practices.”

The court, however, did not accept the defendant’s sweeping allegations of discovery misconduct. Instead, the court found that the foundation’s preservation efforts passed legal muster. Among other things, the foundation had issued timely hold instructions, preserved relevant backup tapes and acted to prevent the deletion of custodial data. Significantly, the court then explained that it would not get wrapped around the proverbial axel due to some isolated “shortcomings” with the foundation’s preservation efforts:

While there may have been some shortcomings in [the foundation’s] document retention protocol, it was, at most, negligent in its effort to preserve evidence related to this litigation.

Moreover, sanctions were not appropriate since the defendant had not established that relevant evidence had been destroyed. In what ultimately amounted to a “no-harm, no-foul” approach, the court observed that the “spoliation motion fails, then, on the ‘inability [of the defendant] to adduce evidence suggesting the existence, let alone destruction, of relevant documents.’”

The Research Foundation case is important for at least three reasons. First, the court’s reluctance to issue sanctions for mere preservation “shortcomings” is consistent with the general discovery principle that a party’s efforts need not be perfect. Instead of trying to reach a mythical benchmark of infallibility, Research Foundation confirms that a party’s preservation efforts need only satisfy the standards of reasonableness and proportionality.

The second lesson from Research Foundation flows naturally from the first: the misperception that courts acquiesce to knee-jerk sanctions motions. With the judiciary gaining a better understanding of the digital age nuances associated with the preservation and production of ESI, courts are less likely to go along with gotcha sanctions requests. This is particularly the case where sanctions are sought against companies that have an effective information governance plan in place.

This, in turn, gives rise to the third and final take-home from Research Foundation. Given the cooling judicial climate toward sanctions and the efforts being taken by the advisory committee to alleviate preservation burdens, the time is ripe for organizations to implement a defensible deletion strategy. Such a comprehensive approach, which aims to reduce the storage costs and legal risks associated with the retention of ESI, stands to benefit companies that can justify deletion decisions based on reasonable information retention practices. Like the foundation in Research Foundation, organizations that have done so have been successful in avoiding court sanctions while at the same time eliminating ESI that has little or no business value.

 

Q & A with Global Data Privacy Expert Christopher Wolf

Wednesday, January 16th, 2013

Data privacy is an issue that has only recently come to the forefront for many U.S. organizations and their counsel. Despite this generalization, there are some U.S. lawyers who have been specializing in this area for years. One of foremost experts in this field is Christopher Wolf, a partner with the international law firm of Hogan Lovells. Chris, who leads Hogan Lovells’ Privacy and Information Management practice group, has focused the last 15 years of his practice on data privacy issues. He also recently co-authored an industry leading white paper on the data privacy implications of the 2001 USA PATRIOT Act (Patriot Act). I recently had a chance to visit with Chris at the Privacy-Protected Data Conference about his practice and his work on the Patriot Act white paper.

  1. What made you transition into data privacy after 20 years as a litigation attorney?

I had the good fortune of handling a pro bono privacy litigation in the late 90s that opened the door to the world of privacy law for me.   I represented a gay sailor who was threatened with discharge under the Navy’s Don’t Ask Don’t Tell Policy when a Navy investigator used false pretenses to illegally obtain personal information about the sailor from his Internet Service Provider.  I was successful in obtaining an injunction against his discharge and a ruling that the Navy violated the Electronic Communications Privacy Act.  News of that case led to a paying client hiring me for privacy work.  And I was hooked!  I then created the first Practising Law Institute treatise on Privacy Law, and got involved in public policy discussions about privacy.  Through my law practice and think tank, The Future of Privacy Forum, I have tried to advance the causes of responsible and transparent data practices that respect individual privacy and comply with the law.

  1. What drove you to develop the Patriot Act white paper?

We had observed a trend of misinformation being propagated out of some countries, most notably in Europe, that invoked the Patriot Act as a kind of shorthand to imply that the U.S. government is alone in permitting governmental access to data stored in the cloud for law enforcement or national security purposes.  This misinformation had become so ingrained that it often was parroted without any basis and cited to support the offering of “national clouds” as a “safer” alternative to U.S.-based cloud service providers, who were painted as indiscriminately handing cloud data over to the U.S. government.  Our white paper examined the laws of ten major countries, including the United States, to demonstrate that these concerns were without basis.

  1. Vis-à-vis the laws of other nations such as Germany, Canada and others identified in the white paper, does the Patriot Act provide the U.S. government with greater access to data stored with cloud service providers?

When we compared the investigative methods available in the U.S. to each of the other nine jurisdictions we examined, we learned two important things.  First, every jurisdiction vested authority in the government to require a cloud service provider to disclose customer data, with almost all granting the ability to request data stored on foreign servers under the service provider’s control.  Second, in jurisdictions outside the U.S., there is a real potential of data relating to a person stored in the cloud being disclosed to governmental authorities voluntarily, without legal process and protections (the only exception being Japan which, like the U.S., requires the government to use legal process to obtain data from cloud service providers).  Ultimately, we concluded that people are misleading themselves if they believe that restricting cloud service providers to one jurisdiction better insulates data from governmental access.

  1. What are some of the other prevailing myths regarding the powers granted to the U.S. Government by the Patriot Act?

Notice that in my previous response, I didn’t reference the Patriot Act.  That is because most of the investigatory methods in the Patriot Act were available long before it was enacted, and the laws governing governmental access to data primarily are located in other U.S. laws.  It is more accurate to say that the Patriot Act did not create broad new investigatory powers but, rather, expanded existing investigative methods.  And despite this expansion, the U.S. government’s exercise of its authority under the Patriot Act is still limited by constitutional and statutory controls.  For example, in the past few years there have been some successful court challenges to the U.S. government’s use of the Patriot Act when the government has overstepped its bounds.

  1. Are you planning a sequel or other follow up materials to the white paper?

We are currently considering similar projects to dispel similar misinformation, such as by discussing the ability of non-U.S. citizens to contest the U.S. government’s collection and use of their data, and by demonstrating that it is lawful and safe for European companies to transfer data to U.S.-based cloud providers that are certified to the U.S.-EU Safe Harbor.  Stay tuned.

  1. Putting more of a human face on your work, what has been one of the most meaningful aspects of your practice?

It always has been important to me to have a steady pro bono docket.  Currently, I am national chair of the Civil Rights Committee of the Anti-Defamation League. In addition, it is gratifying to work in the area of privacy and information management law where clients really do want to do the right thing when it comes to protection information, and I enjoy helping them do that!

Thank you, Chris. We wish you the best in your practice.

Spotlighting the Top Electronic Discovery Cases from 2012

Friday, December 14th, 2012

With the New Year quickly approaching, it is worth reflecting on some of the key eDiscovery developments that have occurred during 2012. While legislative, regulatory and rulemaking bodies have undoubtedly impacted eDiscovery, the judiciary has once again played the most dramatic role.  There are several lessons from the top 2012 court cases that, if followed, will likely help organizations reduce the costs and risks associated with eDiscovery. These cases also spotlight the expectations that courts will likely have for organizations in 2013 and beyond.

Implementing a Defensible Deletion Strategy

Case: Brigham Young University v. Pfizer, 282 F.R.D. 566 (D. Utah 2012)

In Brigham Young, the plaintiff university had pressed for sanctions as a result of Pfizer’s destruction of key documents pursuant to its information retention policies. The court rejected that argument because such a position failed to appreciate the basic workings of a valid corporate retention schedule. As the court reasoned, “[e]vidence may simply be discarded as a result of good faith business procedures.” When those procedures operate to inadvertently destroy evidence before the duty to preserve is triggered, the court held that sanctions should not issue: “The Federal Rules protect from sanctions those who lack control over the requested materials or who have discarded them as a result of good faith business procedures.”

Summary: The Brigham Young case is significant since it emphasizes that organizations should implement a defensible deletion strategy to rid themselves of data stockpiles. Absent a preservation duty or other exceptional circumstances, organizations that pare back ESI pursuant to “good faith business procedures” (such as a neutral retention policy) will be protected from sanctions.

**Another Must-Read Case: Danny Lynn Elec. v. Veolia Es Solid Waste (M.D. Ala. Mar. 9, 2012)

Issuing a Timely and Comprehensive Litigation Hold

Case: Apple, Inc. v. Samsung Electronics Co., Ltd, — F. Supp. 2d. — (N.D. Cal. 2012)

Summary: The court first issued an adverse inference instruction against Samsung to address spoliation charges brought by Apple. In particular, the court faulted Samsung for failing to circulate a comprehensive litigation hold instruction when it first anticipated litigation. This eventually culminated in the loss of emails from several key Samsung custodians, inviting the court’s adverse inference sanction.

Ironically, however, Apple was subsequently sanctioned for failing to issue a proper hold notice. Just like Samsung, Apple failed to distribute a hold until several months after litigation was reasonably foreseeable. The tardy hold instruction, coupled with evidence suggesting that Apple employees were “encouraged to keep the size of their email accounts below certain limits,” ultimately led the court to conclude that Apple destroyed documents after its preservation duty ripened.

The Lesson for 2013: The Apple case underscores the importance of issuing a timely and comprehensive litigation hold notice. For organizations, this likely means identifying the key players and data sources that may have relevant information and then distributing an intelligible hold instruction. It may also require suspending aspects of information retention policies to preserve relevant ESI. By following these best practices, organizations can better avoid the sanctions bogeyman that haunts so many litigants in eDiscovery.

**Another Must-Read Case: Chin v. Port Authority of New York, 685 F.3d 135 (2nd Cir. 2012)

Judicial Approval of Predictive Coding

Case: Da Silva Moore v. Publicis Groupe, — F.R.D. — (S.D.N.Y. Feb. 24, 2012)

Summary: The court entered an order that turned out to be the first of its kind: approving the use of predictive coding technology in the discovery phase of litigation. That order was entered pursuant to the parties’ stipulation, which provided that defendant MSL Group could use predictive coding in connection with its obligation to produce relevant documents. Pursuant to that order, the parties methodically (yet at times acrimoniously) worked over several months to fine tune the originally developed protocol to better ensure the production of relevant documents by defendant MSL.

The Lesson for 2013: The court declared in its order that predictive coding “is an acceptable way to search for relevant ESI in appropriate cases.” Nevertheless, the court also made clear that this technology is not the exclusive method now for conducting document review. Instead, predictive coding should be viewed as one of many different types of tools that often can and should be used together.

**Another Must-Read Case: In Re: Actos (Pioglitazone) Prods. Liab. Litig. (W.D. La. July 10, 2012)

Proportionality and Cooperation are Inextricably Intertwined

Case: Pippins v. KPMG LLP, 279 F.R.D. 245 (S.D.N.Y. 2012)

Summary: The court ordered the defendant accounting firm (KPMG) to preserve thousands of employee hard drives. The firm had argued that the high cost of preserving the drives was disproportionate to the value of the ESI stored on the drives. Instead of preserving all of the drives, the firm hoped to maintain a reduced sample, asserting that the ESI on the sample drives would satisfy the evidentiary demands of the plaintiffs’ class action claims.

The court rejected the proportionality argument primarily because the firm refused to permit plaintiffs or the court to analyze the ESI found on the drives. Without any transparency into the contents of the drives, the court could not weigh the benefits of the discovery against the alleged burdens of preservation. The court was thus left to speculate about the nature of the ESI on the drives, reasoning that it went to the heart of plaintiffs’ class action claims. As the district court observed, the firm may very well have obtained the relief it requested had it engaged in “good faith negotiations” with the plaintiffs over the preservation of the drives.

The Lesson for 2013: The Pippins decision reinforces a common refrain that parties seeking the protection of proportionality principles must engage in reasonable, cooperative discovery conduct. Staking out uncooperative positions in the name of zealous advocacy stands in sharp contrast to proportionality standards and the cost cutting mandate of Rule 1. Moreover, such a tactic may very well foreclose proportionality considerations, just as it did in Pippins.

**Another Must-Read Case: Kleen Products LLC v. Packaging Corp. of America (N.D. Ill. Sept. 28, 2012)

Conclusion

There were any number of other significant cases from 2012 that could have made this list.  We invite you to share your favorites in the comments section or contact us directly with your feedback.

What Abraham Lincoln Teaches about Defensible Deletion of ESI

Monday, November 19th, 2012

The reviews are in and movie critics are universally acclaiming Lincoln, the most recent Hollywood rendition regarding the sixteenth president of the United States. While viewers may or may not enjoy the movie, the focus on Abraham Lincoln brings to mind a rather key insight for organizations seeking to strengthen their defensible deletion process.

Lincoln has long been admired for his astute handling of the U.S. Civil War and for his inventive genius (he remains the only U.S. President who patented an invention). Nevertheless, it is Lincoln’s magnanimous, yet shrewd treatment of his rivals that provides the key lesson for organizations today. With a strategy that inexplicably escapes many organizations, Lincoln intelligently organized his documents and other materials so that he could timely retrieve them to help keep his political enemies in check.

This strategy was particularly successful with his Secretary of the Treasury, Salmon Chase, who constantly undermined Lincoln in an effort to bolster his own presidential aspirations. To blunt the effect of Chase’s treachery, Lincoln successfully wielded the weapon of information: Chase’s letters to Lincoln that were filled with problematic admissions. Doris Kearns Goodwin chronicled in her Pulitzer Prize winning book, Team of Rivals, how Lincoln always seemed to access that information at a moment’s notice to save him from Chase’s duplicity.

Lincoln’s tactics reinforce the value of retaining and retrieving important information in a time of need. Lacking the organizational and technological capacity to do so may prevent companies from pulling up information at a crucial moment, be it for business, legal or regulatory purposes. For this and many other reasons, industry experts are recommending that organizations implement a defensible deletion strategy.

Defensible Deletion Requires Deletion                    

Such a strategy could have some success if it is powered by the latest in effective retention technologies such as data classification and automated legal hold. Such innovations will better enable organizations to segregate and preserve business critical ESI.

And yet, it is not enough to just adopt the preservation side of this strategy, for the heart of defensible deletion requires just that – deleting large classes of superfluous, duplicative and harmful data – if its benefits are ever to be realized. Companies that fail to delete such ESI will likely never come off conqueror in the “battle of the data bulge.” Indeed, such a growing waistline of data is problematic for three reasons. First, it can place undue pressure on an organization’s storage infrastructure and needlessly increase the cost of data retention. It can also result in higher eDiscovery costs as the organization is forced to review and analyze all of that ESI largesse. Finally, a potentially fatal risk of producing harmful materials – kept beyond the time required by law – in eDiscovery will unnecessarily increase. All of which could have been obviated had the enterprise observed the rule of “good corporate housekeeping” by eliminating ESI in a manner approved by courts and the rules makers.

For organizations willing to get rid of their digital clutter, defensible deletion offers just what they need so as to reduce the costs and risks of bloated ESI retention. Doing so will help companies make better use that information so, like Honest Abe, they can stave off troublesome challenges threatening the enterprise.

New Gartner Report Spotlights Significance of Email Archiving for Defensible Deletion

Thursday, November 1st, 2012

Gartner recently released a report that spotlights the importance of using email archiving as part of an organization’s defensible deletion strategy. The report – Best Practices for Using Email Archiving to Eliminate PST and Mailbox Quota Headaches (Alan Dayley, September 21, 2012) – specifically focuses on the information retention and eDiscovery challenges associated with email storage on Microsoft Exchange and how email archiving software can help address these issues. As Gartner makes clear in its report, an archiving solution can provide genuine opportunities to reduce the costs and risks of email hoarding.

The Problem: PST Files

The primary challenge that many organizations are experiencing with Microsoft Exchange email is the unchecked growth of messages stored in portable storage tablet (PST) files. Used to bypass storage quotas on Exchange, PST files are problematic because they increase the costs and risks of eDiscovery while circumventing information retention policies.

That the unrestrained growth of PST files could create problems downstream for organizations should come as no surprise. Various court decisions have addressed this issue, with the DuPont v. Kolon Industries litigation foremost among them. In the DuPont case, a $919 million verdict and 20 year product injunction largely stemmed from the defendant’s inability to prevent the destruction of thousands pages of email formerly stored in PST files. That spoliation resulted in a negative inference instruction to the jury and the ensuing verdict against the defendant.

The Solution: Eradicate PSTs with the Help of Archiving Software and Retention Policies

To address the PST problem, Gartner suggests following a three-step process to help manage and then eradicate PSTs from the organization. This includes educating end users regarding both the perils of PSTs and the ease of access to email through archiving software. It also involves disabling the creation of new PSTs, a process that should ultimately culminate with the elimination of existing PSTs.

In connection with this process, Gartner suggests deployment of archiving software with a “PST management tool” to facilitate the eradication process. With the assistance of the archiving tool, existing PSTs can be discovered and migrated into the archive’s central data repository. Once there, email retention policies can begin to expire stale, useless and even harmful messages that were formerly outside the company’s information retention framework.

With respect to the development of retention policies, organizations should consider engaging in a cooperative internal process involving IT, compliance, legal and business units. These key stakeholders must be engaged and collaborate if a workable policies are to be created. The actual retention periods should take into account the types of email generated and received by an organization, along with the enterprise’s business, industry and litigation profile.

To ensure successful implementation of such retention policies and also address the problem of PSTs, an organization should explore whether an on premise or cloud archiving solution is a better fit for its environment. While each method has its advantages, Gartner advises organizations to consider whether certain key features are included with a particular offering:

Email classification. The archiving tool should allow your organization to classify and tag the emails in accordance with your retention policy definitions, including user-selected, user/group, or key-word tagging.

User access to archived email. The tool must also give end users appropriate and user-friendly access to their archived email, thus eliminating concerns over their inability to manage their email storage with PSTs.

Legal and information discovery capabilities. The search, indexing, and e-discovery capabilities of the archiving tool should also match your needs or enable integration into corporate e-discovery systems.

While perhaps not a panacea for the storage and eDiscovery problems associated with email, on premise or cloud archiving software should provide various benefits to organizations. Indeed, such technologies have the potential to help organizations store, manage and discover their email efficiently, cost effectively and in a defensible manner. Where properly deployed and fully implemented, organizations should be able to reduce the nettlesome costs and risks connected with email.

Federal Directive Hits Two Birds (RIM and eDiscovery) with One Stone

Thursday, October 18th, 2012

The eagerly awaited Directive from The Office of Management and Budget (OMB) and The National Archives and Records Administration (NARA) was released at the end of August. In an attempt to go behind the scenes, we’ve asked the Project Management Office (PMO) and the Chief Records Officer for the NARA to respond to a few key questions. 

We know that the Presidential Mandate was the impetus for the agency self-assessments that were submitted to NARA. Now that NARA and the OMB have distilled those reports, what are the biggest challenges on a go forward basis for the government regarding record keeping, information governance and eDiscovery?

“In each of those areas, the biggest challenge that can be identified is the rapid emergence and deployment of technology. Technology has changed the way Federal agencies carry out their missions and create the records required to document that activity. It has also changed the dynamics in records management. In the past, agencies would maintain central file rooms where records were stored and managed. Now, with distributed computing networks, records are likely to be in a multitude of electronic formats, on a variety of servers, and exist as multiple copies. Records management practices need to move forward to solve that challenge. If done right, good records management (especially of electronic records) can also be of great help in providing a solid foundation for applying best practices in other areas, including in eDiscovery, FOIA, as well as in all aspects of information governance.”    

What is the biggest action item from the Directive for agencies to take away?

“The Directive creates a framework for records management in the 21st century that emphasizes the primacy of electronic information and directs agencies to being transforming their current process to identify and capture electronic records. One milestone is that by 2016, agencies must be managing their email in an electronically accessible format (with tools that make this possible, not printing out emails to paper). Agencies should begin planning for the transition, where appropriate, from paper-based records management process to those that preserve records in an electronic format.

The Directive also calls on agencies to designate a Senior Agency Official (SAO) for Records Management by November 15, 2012. The SAO is intended to raise the profile of records management in an agency to ensure that each agency commits the resources necessary to carry out the rest of the goals in the Directive. A meeting of SAOs is to be held at the National Archives with the Archivist of the United States convening the meeting by the end of this year. Details about that meeting will be distributed by NARA soon.”

Does the Directive holistically address information governance for the agencies, or is it likely that agencies will continue to deploy different technology even within their own departments?

“In general, as long as agencies are properly managing their records, it does not matter what technologies they are using. However, one of the drivers behind the issuance of the Memorandum and the Directive was identifying ways in which agencies can reduce costs while still meeting all of their records management requirements. The Directive specifies actions (see A3, A4, A5, and B2) in which NARA and agencies can work together to identify effective solutions that can be shared.”

Finally, although FOIA requests have increased and the backlog has decreased, how will litigation and FOIA intersecting in the next say 5 years?  We know from the retracted decision in NDLON that metadata still remains an issue for the government…are we getting to a point where records created electronically will be able to be produced electronically as a matter of course for FOIA litigation/requests?

“In general, an important feature of the Directive is that the Federal government’s record information – most of which is in electronic format – stays in electronic format. Therefore, all of the inherent benefits will remain as well – i.e., metadata being retained, easier and speedier searches to locate records, and efficiencies in compilation, reproduction, transmission, and reduction in the cost of producing the requested information. This all would be expected to have an impact in improving the ability of federal agencies to respond to FOIA requests by producing records in electronic formats.”

Fun Fact- Is NARA really saving every tweet produced?

“Actually, the Library of Congress is the agency that is preserving Twitter. NARA is interested in only preserving those tweets that a) were made or received in the course of government business and b) appraised to have permanent value. We talked about this on our Records Express blog.”

“We think President Barack Obama said it best when he made the following comment on November 28, 2011:

“The current federal records management system is based on an outdated approach involving paper and filing cabinets. Today’s action will move the process into the digital age so the American public can have access to clear and accurate information about the decisions and actions of the Federal Government.” Paul Wester, Chief Records Officer at the National Archives, has stated that this Directive is very exciting for the Federal Records Management community.  In our lifetime none of us has experienced the attention to the challenges that we encounter every day in managing our records management programs like we are now. These are very exciting times to be a records manager in the Federal government. Full implementation of the Directive by the end of this decade will take a lot of hard work, but the government will be better off for doing this and we will be better able to serve the public.”

Special thanks to NARA for the ongoing dialogue that is key to transparent government and the effective practice of eDiscovery, Freedom Of Information Act requests, records management and thought leadership in the government sector. Stay tuned as we continue to cover these crucial issues for the government as they wrestle with important information governance challenges. 

 

Breaking News: Kleen Products Ruling Confirms Significance of Cooperation and Proportionality in eDiscovery

Tuesday, October 2nd, 2012

While the truce in Kleen Products v. Packaging Corporation of America has cooled off the parties’ predictive coding dispute until next year, eDiscovery motion practice in this case is just now intensifying. In response to the current round of motions surrounding plaintiffs’ interrogatories and document requests, U.S. Magistrate Judge Nan Nolan has issued a lengthy order emphasizing that the parties’ discovery efforts should be collaborative and not combative. In particular, Judge Nolan has highlighted the significance of both cooperation and proportionality in conducting discovery.

Just as she did to resolve the parties’ disagreement over the use of predictive coding, Judge Nolan relied on a Sedona Conference publication to decide the instant dispute. Citing The Sedona Conference Cooperation Proclamation, Judge Nolan urged counsel to not “confuse advocacy with adversarial conduct” in addressing discovery obligations. In that regard, the plaintiffs were singled out for propounding an interrogatory that “violated the spirit of cooperation that this Court has encouraged.” The interrogatory was particularly troublesome because it requested information about defendant Georgia-Pacific’s organizational structure that plaintiffs agreed not to seek since defendant voluntarily provided plaintiffs with the names, titles and company division of the 400 employees who received litigation hold notices. Given that the court itself had brokered this arrangement, Judge Nolan opined that plaintiffs’ tactic “could have a chilling effect on both litigants and courts to engage in candid discussions.”

The interrogatory was additionally objectionable because it violated the proportionality standards found in Federal Rule 26(b)(2)(C). Not only did the laundry list of details that the interrogatory sought regarding the defendant’s 400 employees create an undue burden, such information was readily available from sources that were “more convenient, less burdensome, and less expensive.” Relying on the proportionality rule and The Sedona Conference Commentary on Proportionality in Electronic Discovery, the court granted the defendant’s motion for protective order and quashed the interrogatory.

Judge Nolan’s opinion repeatedly spotlights the role that cooperation and proportionality play in accomplishing discovery in a “just, speedy and inexpensive” manner. Moreover, the judge repeatedly praised the litigants for approaching eDiscovery in cooperative fashion: “The Court commends the lawyers and their clients for conducting their discovery obligations in a collaborative manner.” Indeed, the court went so far as to identify the numerous instances where motion practice had been avoided, including the predictive coding and search methodology dispute.

The Kleen Products case demonstrates that courts have raised their expectations for how litigants will engage in eDiscovery. Staking out unreasonable positions in the name of zealous advocacy stands in stark contrast to the clear trend that discovery should comply with the cost cutting mandate of Federal Rule 1. Cooperation and proportionality are two of the principal touchstones for effectuating that mandate.

From A to PC – Running a Defensible Predictive Coding Workflow

Tuesday, September 11th, 2012

So far in our ongoing predictive coding blog series, we’ve touched on the “whys” and “whats” of predictive coding, and now I’d like to address the “hows” of using this new technology. Given that predictive coding is groundbreaking technology in the world of eDiscovery, it’s no surprise that a different workflow is required in order to run the review process.

The traditional linear review process utilizes a “brute force” approach of manually reading each document and processing it for responsiveness and privilege. In order to reduce the high cost of this process, many organizations now farm out documents to contract attorneys for review. Often, however, contract attorneys possess less expertise and knowledge of the issues, which means that multiple review passes along with additional checks and balances are often needed in order to ensure review accuracy. This process commonly results in a significant number of documents being reviewed multiple times, which in turn increases the cost of review. When you step away from an “eyes-on review” of every document and use predictive coding to leverage the expertise of more experienced attorneys, you will naturally aim to review as few documents as possible in order to achieve the best possible results.

How do you review the minimum number of documents with predictive coding? For starters, organizations should prepare their case to use predictive coding by performing an early case assessment (ECA) in order to cull down to your review population prior to review. While some may suggest that predictive coding can be run without any ECA up front, you will actually save a significant amount of review time if you put in the effort to cull out the profoundly irrelevant documents in your case. Doing so will prevent a “junk in, junk out” situation where leaving too much junk in the case will result in having to necessarily review a number of junk documents throughout the predictive coding workflow.

Next, segregating documents that are unsuitable for predictive coding is important. Most predictive coding solutions leverage the extracted text content within documents to operate. That means any documents that do not contain extracted text, such as photographs and engineering schematics, should be manually reviewed so they are not overlooked by the predictive coding engine. The same concept applies to any other document that has other reviewable limitations, such as encrypted and password protected files. All of these documents should be reviewed separately as to not miss any relevant documents.

After culling down to your review population, the next step in preparing to use predictive coding is to create a Control Set by drawing a randomly selected statistical sample from the document population. Once the Control Set is manually reviewed, it will serve two main purposes. First, it will allow you to estimate the population yield, otherwise referred to as the percentage of responsive documents contained within the larger population. (The size of the control set may need to be adjusted to insure the yield is properly taken into account). Second, it will serve as your baseline for a true “apples-to-apples” comparison of your prediction accuracy across iterations as you move through the predictive coding workflow. The Control Set will only need to be reviewed once up front to be used for measuring accuracy throughout the workflow.

It is essential that the documents in the Control Set are selected randomly from the entire population. While some believe that taking other sampling approaches give better peace of mind, they actually may result in unnecessary review. For example, other workflows recommend sampling from the documents that are not predicted to be relevant to see if anything was left behind. If you instead create a proper Control Set from the entire population, you can get the necessary precision and recall metrics that are representative of the entire population, which in turn represents the documents that are not predicted to be relevant.

Once the Control Set is created, you can begin training the software to evaluate documents by the review criteria in the case. Selecting the optimal set of documents to train the system (commonly referred to as the training set or seed set) is one of the most important steps in the entire predictive coding workflow as it sets the initial accuracy for the system, and thus it should be chosen carefully. Some suggest creating the initial training set by taking a random sample (much like how the control set is selected) from the population instead of proactively selecting responsive documents. However, the important thing to understand is that any items used for training should accurately represent the responsive items instead. The reason selecting responsive documents for inclusion in the training set is important is related to the fact that most eDiscovery cases generally have low yield – meaning the prevalence of responsive documents contained within the overall document population is low. This means the system will not be able to effectively learn how to identify responsive items if enough responsive documents are not included in the training set.

An effective method for selecting the initial training set is to use a targeted search to locate a small set of documents (typically between 100-1000) that is expected to be about 50% responsive. For example, you may choose to focus on only the key custodians in the case and use a combination of tighter keyword/date range/etc search criteria. You do not have to perform exhaustive searches, but a high quality initial training set will likely minimize the amount of additional training needed to achieve high prediction accuracy.

After the initial training set is selected, it must then be reviewed. It is extremely important that the review decisions made on any training items are as accurate as possible since the systems will be learning from these items, which typically means that the more experienced case attorneys should be used for this review. Once review is finished on all of the training documents, then the system can learn from the tagging decisions in order to be able to predict the responsiveness or non-responsiveness of the remaining documents.

While you can now predict on all of the other documents in the population, it is most important to predict on the Control Set at this time. Not only may this decision be more time effective than applying predictions to all the documents in the case, but you will need predictions on all of the documents in the Control Set in order to assess the accuracy of the predictions. With predictions and tagging decisions on each of the Control Set documents, you will be able to get accurate precision and recall metrics that you can extrapolate to the entire review population.

At this point, the accuracy of the predictions is likely to not be optimal, and thus the iterative process begins. In order to increase the accuracy, you must select additional documents to use for training the system. Much like the initial training set, this additional training set must also be selected carefully. The best documents to use for an additional training set are those that the system would be unable to accurately predict. Rather than choosing these documents manually, the software is often able to mathematically determine this set more effectively than human reviewers. Once these documents are selected, you simply continue the iterative process of training, predicting and testing until your precision and recall are at an acceptable point. Following this workflow will result in a set of documents identified to be responsive by the system along with trustworthy and defensible accuracy metrics.

You cannot simply produce all of these documents at this point, however. The documents must still go through a privileged screen in order to remove any documents that should not be produced, and also go through any other review measures that you usually take on your responsive documents. This does, however, open up the possibility of applying additional rounds of predictive coding on top of this set of responsive documents. For example, after running the privileged screen, you can train on the privileged tag and attempt to identify additional privileged documents in your responsive set that were missed.

The important thing to keep in mind is that predictive coding is meant to strengthen your current review workflows. While we have outlined one possible workflow that utilizes predictive coding, the flexibility of the technology lends itself to be utilized for a multitude of other uses, including prioritizing a linear review. Whatever application you choose, predictive coding is sure to be an effective tool in your future reviews.

Falcon Discovery Ushers in Savings with Transparent Predictive Coding

Tuesday, September 4th, 2012

The introduction of Transparent Predictive Coding to Symantec’s Clearwell eDiscovery Platform helps organizations defensibly reduce the time and cost of document review. Predictive coding refers to machine learning technology that can be used to automatically predict how documents should be classified based on limited human input. As expert reviewers tag documents in a training set, the software identifies common criteria across those documents, which it uses to “predict” the responsiveness of the remaining case documents. The result is that fewer irrelevant and non-responsive documents need to be reviewed manually – thereby accelerating the review process, increasing accuracy and allowing organizations to reduce the time and money spent on traditional page-by-page attorney document review.

Given the cost, speed and accuracy improvements that predictive coding promises, its adoption may seem to be a no-brainer. Yet predictive coding technology hasn’t been widely adopted in eDiscovery – largely because the technology and process itself still seems opaque and complex. Symantec’s Transparent Predictive Coding was developed to address these concerns and provide the level of defensibility necessary to enable legal teams to adopt predictive coding as a mainstream technology for eDiscovery review. Transparent Predictive Coding provides reviewers with complete visibility into the training and prediction process and delivers context for more informed, defensible decision-making.

Early adopters like Falcon Discovery have already witnessed the benefits of Transparent Predictive Coding. Falcon is a managed services provider that leverages a mix of top legal talent and cutting-edge technologies to help corporate legal departments, and the law firms that serve them, manage discovery and compliance challenges across matters. Recently, we spoke with Don McLaughlin, founder and CEO of Falcon Discovery, on the firm’s experiences with and lessons learned from using Transparent Predictive Coding.

1. Why did Falcon Discovery decide to evaluate Transparent Predictive Coding?

Predictive coding is obviously an exciting development for the eDiscovery industry, and we want to be able to offer Falcon’s clients the time and cost savings that it can deliver. At the same time there is an element of risk. For example, not all solutions provide the same level of visibility into the prediction process, and helping our clients manage eDiscovery in a defensible manner is of paramount importance. Over the past several years we have tested and/or used a number of different software solutions that include some assisted review or prediction technology. We were impressed that Symantec has taken the time and put in the research to integrate best practices into its predictive coding technology. This includes elements like integrated, dynamic statistical sampling, which takes the guesswork out of measuring review accuracy. This ability to look at accuracy across the entire review set provides a more complete picture, and helps address key issues that have come to light in some of the recent predictive coding court cases like Da Silva Moore.

2. What’s something you found unique or different from other solutions you evaluated?

I would say one of the biggest differentiators is that Transparent Predictive Coding uses both content and metadata in its algorithms to capture the full context of an e-mail or document, which we found to be appealing for two reasons. First, you often have to consider metadata during review for sensitive issues like privilege and to focus on important communications between specific individuals during specific time periods. Second, this can yield more accurate results with less work because the software has a more complete picture of the important elements in an e-mail or document. This faster time to evaluate the documents is critical for our clients’ bottom line, and enables more effective litigation risk analysis, while minimizing the chance of overlooking privileged or responsive documents.

3. So what were some of the success metrics that you logged?

Using Transparent Predictive Coding, Falcon was able to achieve extremely high levels of review accuracy with only a fraction of the time and review effort. If you look at academic studies on linear search and review, even under ideal conditions you often get somewhere between 40-60% accuracy. With Transparent Predictive Coding we are seeing accuracy measures closer to 90%, which means we are often achieving 90% recall and 80% precision by reviewing only a small fraction – under 10% – of the data population that you might otherwise review document-by-document. For the appropriate case and population of documents, this enables us to cut review time and costs by 90% compared to pure linear review. Of course, this is on top of the significant savings derived from leveraging other technologies to intelligently cull the data to a more relevant review set, prior to even using Transparent Predictive Coding. This means that our clients can understand the key issues, and identify potentially ‘smoking gun’ material, much earlier in a case.

4. How do you anticipate using this technology for Falcon’s clients?

I think it’s easy for people to get swept up by the “latest and greatest” technology or gadget and assume this is the silver bullet for everything we’ve been toiling over before. Take, for example, the smartphone camera – great for a lot of (maybe even most) situations, but sometimes you’re going to want that super zoom lens or even (gasp!) regular film. By the same token, it’s important to recognize that predictive coding is not an across-the-board substitute for other important eDiscovery review technologies and targeted manual review. That said, we’ve leveraged Clearwell to help our clients lower the time and costs of the eDiscovery process on hundreds of cases now, and one of the main benefits is that the solution offers the flexibility of using any number of advanced analytics tools to meet the specific requirements of the case at hand. We’re obviously excited to be able to introduce our clients to this predictive coding technology – and the time and cost benefits it can deliver – but this is in addition to other Clearwell tools, like advanced keyword search, concept or topic clustering, domain filtering, discussion threading and so on, that can and should be used together with predictive coding.

5. Based on your experience, do you have advice for others who may be looking to defensibly reduce the time and cost of document review with predictive coding technology?

The goal of the eDiscovery process is not perfection. At the end of the day, whether you employ a linear review approach and/or leverage predictive coding technology, you need to be able to show that what you did was reasonable and achieved an acceptable level of recall and precision. One of the things you notice with predictive coding is that as you review more documents, the recall and precision scores go up but at a decreasing rate. A key element of a reasonable approach to predictive coding is measuring your review accuracy using a proven statistical sampling methodology. This includes measuring recall and precision accurately to ensure the predictive coding technology is performing as expected. We’re excited to be able to deliver this capability to our clients out of the box with Clearwell, so they can make more informed decisions about their cases early-on and when necessary address concerns of proportionality with opposing parties and the court.

To find out more about Transparent Predictive Coding, visit http://go.symantec.com/predictive-coding

The Malkovich-ization of Predictive Coding in eDiscovery

Tuesday, August 14th, 2012

In the 1999 Academy Award-winning movie, Being John Malkovich, there’s a scene where the eponymous character is transported into his own body via a portal and everyone around him looks exactly like him.  All the characters can say is “Malkovich” as if this single word conveys everything to everyone.

In the eDiscovery world it seems lately like predictive coding has been Malkovich-ized, in the sense that it’s the start and end of every discussion. We here at eDiscovery 2.0 are similarly unable to break free of predictive coding’s gravitational pull – but we’ve attempted to give the use of this emerging technology some context, in the form of a top ten list.

So, without further ado, here are the top ten important items to consider with predictive coding and eDiscovery generally…

1. Perfection Is Not Required in eDiscovery

While not addressing predictive coding per se, it’s important to understand the litmus test for eDiscovery efforts. Regardless of the tools or techniques utilized to respond to document requests in electronic discovery, perfection is not required. The goal should be to create a reasonable and repeatable process to establish defensibility in the event you face challenges by the court or an opposing party. Make sure the predictive coding application (and broader eDiscovery platform you choose) functions correctly, is used properly and can generate reports illustrating that a reasonable process was followed. Remember, making smart decisions to establish a repeatable and defensible process early will inevitably reduce the risk of downstream problems.

2. Predictive Coding Is Just One Tool in the Litigator’s Tool-belt

Although the right predictive coding tools can reduce the time and cost of document review and improve accuracy rates, they are not a substitute for other important technology tools. Keyword search, concept search, domain filtering, and discussion threading are only a few of the other important tools in the litigator’s tool-belt that can and should be used together with predictive coding. Invest in an eDiscovery platform that contains a wide range of seamlessly integrated eDiscovery tools that work together to ensure the simplest, most flexible, and most efficient eDiscovery process.

3. Using Predictive Coding Tools Properly Makes All the Difference

Electronic discovery applications, like most technology solutions, are only effective if deployed properly. Since many early-generation tools are not intuitive, learning how to use a given predictive coding tool properly is critical to eDiscovery success. To maximize chances for success and minimize the risk of problems, select trustworthy predictive coding applications supported by reputable providers and make sure to learn how to use the solutions properly.

4. Predictive Coding Isn’t Just for Big Cases

Sometimes predictive coding applications must be purchased separately from other eDiscovery tools; other times additional fees may be required to use predictive coding. As a result, many practitioners only consider predictive coding for the largest cases, to ensure the cost of eDiscovery doesn’t exceed the value of the case. If possible, invest in an electronic discovery solution that includes predictive coding as part of an integrated eDiscovery platform containing legal hold, collection, processing, culling, analysis, and review capabilities at no additional charge. Since the cost of using different predictive coding tools varies dramatically, make sure to select a tool at the right price point to maximize economic efficiencies across multiple cases, regardless of size.

5. Investigate the Solution Providers

All predictive coding applications are not created equal. The tools vary significantly in price, usability, performance and overall reputation. Although the availability of trustworthy and independent information comparing different predictive coding solutions is limited, information about the companies creating these different application is available. Make sure to review independent research from analysts such as Gartner, Inc., as part of the vetting process instead of starting from scratch.

6. Test Drive Before You Buy

Savvy eDiscovery technologists take steps to ensure that the predictive coding application they are considering works within their organization’s environment and on their organization’s data. Product demonstrations are important, but testing products internally through a proof of concept evaluation is even more important if you are contemplating bringing an eDiscovery platform in house. Additionally, check company references before investing in a solution to find out how others feel about the software they purchased and the level of product support they receive.

7. Defensibility Is Paramount

Although predictive coding tools can save organizations money through increased efficiency, the relative newness and complexity of the technology can create risk. To avoid this risk, choose a predictive coding tool that is easy to use, developed by an industry leading company and fully supported.

8. Statistical Methodology and Product Training Are Critical

The underlying statistical methodology behind any predictive coding application is critical to the defensibility of the entire eDiscovery process. Many providers fail to incorporate a product workflow for selecting a properly sized control set in certain situations. Unfortunately, this oversight could unwittingly result in misrepresentations to the court and opposing parties about the system’s performance. Select providers capable of illustrating the statistical methodology behind their approach and that are capable of providing proper training on the use of their system.

9. Transparency Is Key

Many practitioners are legitimately concerned that early-generation predictive coding solutions operate as a “black box,” meaning the way they work is difficult to understand and/or explain. Since it is hard to defend technology that is difficult to understand, selecting a solution and process that can be explained in court is critical. Make sure to choose a predictive coding solution that is transparent to avoid allegations by opponents that your tool is ”black box” technology that cannot be trusted.

10. Align with Attorneys You Trust

The fact that predictive coding is relatively new to the legal field and can be more complex than traditional approaches to eDiscovery highlights the importance of aligning with trusted legal counsel. Most attorneys defer legal technology decisions to others on their legal team and have little practical experience using these solutions themselves. Conversational knowledge about these tools isn’t enough given the confusion, complexity, and risk related to selecting the wrong tool or using the applications improperly. Make sure to align with an attorney who possesses hands-on experience and who are able to articulate specific reasons why they prefer a particular solution or approach.

Hopefully this top ten list can ensure that your use of “predictive coding” isn’t Malkovich-ized – meaning you understand when, how and why you’re deploying this particularly eDiscovery technology. Without the right context, the eDiscovery industry risks overusing this term and in turn over-hyping this exciting next chapter in process improvement.