eDiscovery Cost Shifting – Why You Should be Considering it for All of Your Matters

Cost shifting is the concept of shifting the expense associated with your discovery obligations, in whole or in part, to the party requesting the material.  The concept is not new, but it is historically underused, in part because courts and third party decision makers have been hesitant at best, to grant costs shifting requests in the past.  This is primarily because traditionally, litigation expenses, and discovery related expenses in particular, are born by the party who has the data and is producing it – this is both rule based, but also very much culturally based as well.

However, there is starting to be a sea change as data volumes continue to grow exponentially and discovery costs grow with it, and there is a growing sentiment that in some situations, it is unfair and overly burdensome for a producing party to bear certain costs.  What this means for you is that any assertions, requests, or arguments to shift costs away from you are now more likely to be considered and granted then ever before.  I have noticed this in my practice working with clients, who are not only requesting cost shifting more than ever before, but being successful at it as well.  The rules makers are embracing this trend as well.  The new draft Federal Rules of Civil Procedure include modifications to Rule 26 allowing protective orders to be issued for good cause to protect against undue burden or expense and can include provisions allocating expenses, which can include cost shifting.  The courts are likewise picking up on the trend.  In the context of third party subpoena requests and Federal Rules of Civil Procedure Rule 45, the Ninth Circuit Court of Appeals endorsed, and seemingly mandated, cost shifting in some circumstances, in its decision Legal Voice v. Stormans, Inc., 738 F.3d 1178 (9th Cir. 2013), ruling that if the subpoena imposes expenses and those expenses are significant, the court must shift enough costs so that the expense is no longer significant for the responding party.

Making an effective cost shifting argument, particularly to a court or some third party neutral, is dependent on the case you can make regarding the burden and expenses, and nothing does that better than time and cost metrics that demonstrate what the dollar impact and burden would be; increasingly, courts are unwilling and unsympathetic to mere assertions that something will cost a lot or be unreasonably burdensome.  Having the facts to back up your statement will add to your credibility and make it much more likely you will win a cost shifting argument.  How you develop those metrics and cost points of reference depends.  For my clients, I keep detailed metrics on many different data points allowing my team to provide collection, processing, review, and production costs per document, per custodian, per GB and a variety of other measures.  Working with client we then develop cost affidavits that can be presented to the opposing party or the court and that have proved quite powerful.

Pragmatically, Why not ask? The other side may say yes, you may get some if not all of your costs shifted, and at a minimum, it may make the party requesting the data carefully tailor and narrow their request for what they truly want and need knowing they may have to pay for it.  Worst case is that they say no and you are then in about the same position as if you had not asked.  I have found it is best to first  make an informal request to shift the costs form the party itself (which will cost very little time or money), and if that is unsuccessful, consider making a formal request to the third party decision maker if you feel you have a good claim and reason for doing so.

Particularly for third party subpoena’s I work with some counsel who make that their standard negotiating stance.  As soon as they get the request, they reach out to counsel for the requesting party, let them know how much it will cost and ask them who we should bill for it.  Often they do not get any push back, and suddenly, the request for five custodians’ data shrinks to one or two; when they are bearing the cost burden, the requesting party suddenly does not need every potential source of data under the sun, and only ask for those that are most likely to contain relevant data.

Predictive Coding Part III – A Look at the State of the Technology, the Impact on Review and Review Attorneys, Case Law, and What the Future Holds

PART III of IV: A High-Level Overview of Predictive Coding Case Law and Its Impact on the Use of Predictive Coding

This is the third of four blogs on predictive coding that I will be posting.  The first entry focused on how the technology and use of predictive coding has changed and where exactly it stands in the industry today.  The second entry discussed the impact predictive coding has had on contract review attorneys.  This third installment will cover some case law on the topic. Finally, the fourth will provide predictions about what the future holds for predictive coding.

I am writing these blog entries in part due to my participation in the upcoming ACEDS conference, where I will be speaking on a panel about Information Governance.  If you are interested in the field of eDiscovery and pragmatic discussions about eDiscovery issues framed in the context of real life situations involving real people, I suggest you consider attending the conference, which will be held in Hollywood Beach, Florida, April 27-29.  Additionally, I believe the ACEDS eDiscovery certification is a worthwhile endeavor and certification.  If you would like more information about it, it can be found on the ACEDS website (www.aceds.org), or feel free to contact me as well. 

In many ways, 2012 was the peak of the predictive coding buzz.  It was being discussed at every eDiscovery conference, software vendors were scrambling to develop their own predictive coding technology, link to coding technology platforms, or spin doctoring the capabilities of their product so that it appeared to contain predictive coding functionality, and most blogs had a thing or two to say about the topic, even if they were just token comments.  Case law, or at least case law analyzed and discussed by legal blogs and publications, also seemed to be discussing the technology in some breadth and depth.  The most notable example of this being the Da Silva Moore case in which Judge Peck played a leading, if somewhat controversial, and frankly overstated, role.  But there were others as well.

Since 2012, cases discussing predictive coding have been few and far between, and even those that were heralded for bestowing judicial approval and endorsement of predictive coding in 2012, lacked the finality and power many predicted they would have; although important at the time, the lasting impact of these decisions on the outcome of the matter has been relatively small.  Arguably, we still do not have a seminal predictive coding case, although Da Silva Moore is probably the closest thing we have to it thus far.

Some of the better known cases thus far include:

•  Da Silva Moore: The judge Peck case from 2012 in which he infamously endorsed predictive coding and was subsequently attacked by Plaintiff (often personally and unnecessarily) for doing so.  Although Judge Peck endorsed predictive coding he actually did no more than acquiesce to a plan submitted by both parties to use the technology. Since 2012, the predictive coding aspect of the case has been fairly quiet, and Judge Andrew Carter recently denied the motion for class action.
• Global Aerospace Inc., et al, v. Landow Aviation, L.P. dba Dulles, went a step further than Da Silva Moore.  In Global Aerospace, the defendants wanted to use predictive coding themselves, but plaintiffs objected.  Virginia County Circuit Judge James H. Chamblin, ordered that Defendants could use predictive coding to review documents.  Like Da Silva Moore, the court did not impose the use of predictive coding, rather, the court allowed a party to use it upon request.  In 2013, it became the first case in which a court approved the results of predictive coding.  Although the approval of the results is a success for proponents of predictive coding, the impact of this decision and its power to influence others will likely be limited as the details and results will not transfer to other matters.
•  Kleen Prods., LLC v. Packaging Corp. of Am. went farther yet in that the plaintiffs in Kleen asked the court to force the defendants to use predictive coding when defendants reviewed their own material.  Although an interesting question, it is one the court never ultimately answered as the parties agreed on a protocol leveraging key terms instead.
• Fed. Hous. Fin. Agency v. HSBC, 2014 WL 584300 (S.D.N.Y. Feb. 14, 2014), is another matter from the Southern District of New York, (like Da Silva Moore), in which the court, without much fanfare or publicity (unlike Da Silva Moore) approved of one defendant’s use of predictive coding despite objections from Plaintiff, noting that the technology had a “better track record in the production of responsive documents than the human review.” ---- As an aside, there are certainly studies that suggest this, and at times it is probably true, but not all predictive coding technologies are created equal, and not all implementations of it are created equal.  Just because you use predictive coding does not mean you will be accurate or have better precision and recall than key terms.  You must look beyond the fact that it is predictive coding if you want to know if it is being used properly and if it will lead to solid results; a Ferrari will only get you someplace without getting lost and more quickly than a minivan if the driver of the Ferrari knows where they are going and knows how to drive.
•  EORHB, Inc., et al v. HOA Holdings, LLC, C.A. No. 7409-VCL (Del. Ch. Oct. 15, 2012).  A matter in which a Delaware judge ordered both parties to use predictive coding.
• Anheuser-Busch InBev and Grupo Modelo 2^nd Request is an example of governmental endorsement of predictive coding.  This matter involved the merger and acquisition of these beverage industry giants, who obtained the DOJ’s agreement to use predictive coding on a second set of requested documents.  That agreement likely saved the companies the costs associated with reviewing millions of documents.
• Gabriel Techs. Corp. v. Qualcomm, Inc., 2013 WL 410103 (S.D. Cal. Feb. 1, 2013), suggests predictive coding fees may be recoverable.  In this matter, the court awarded the defendants attorney's fees under 35 U.S.C. § 285 based on plaintiff’s bad faith.  A portion of those fees included approximately $3 million paid for using predictive coding.  In addition to suggesting those fees were recoverable, its silence regarding whether or not to use the technology up front, is also indicative of the trend that predictive coding is de facto accepted by the industry and courts and its use is something not worth arguing before the court.

Why are there so few opinions about predictive coding at this point?  Is it just too common a practice to litigate absent the unusual?  Are the parties simply finding it not worth fighting over and that it does produce a reasonable result?  Yes and yes I would say.  Additionally, the use of predictive coding depends very much on the details of the matter: which technology is used, how it is used, and just as importantly how antagonistic the parties are.  All of that combined means it is difficult for any court to say predictive coding is acceptable across the board except at such a high-level that it is virtually meaningless as a guide or precedent for other matters.  So, while we are bound to see more cases and some opinions where it is approved or endorsed, the value and power of those will be very little as there will almost always be differences in cases that may or may not warrant the use of predictive coding.  Instead, decisions in the future will likely focus on the details and defensibility of implementation and results.

Regardless of case law or court or government endorsement and approval, the reality is that predictive coding is being used even without opinions discussing it or approving it. This use, often by agreement or at least knowledge between parties, but at times covertly, will certainly continue despite the paucity of  opinions touching on it or specifically endorsing it.

Predictive Coding Part II – A Look at the State of the Technology, the Impact on Review and Review Attorneys, Case Law, and What the Future Holds

PART II of IV: The Impact of Predictive Coding on Contract Review Attorneys

This is the second of four blogs on predictive coding that I will be posting.  This first entry focused on how the technology and use of predictive coding has changed and where exactly it stands in the industry today.  This second entry discusses the impact predictive coding has had on contract review attorneys.  The Third will cover case law on the topic. Finally, the fourth will provide some predictions about what the future holds for predictive coding.

I am writing these blog entries in part due to my participation in the upcoming ACEDS conference, where I will be speaking on a panel about Information Governance.  This four part blog series will appear in the conference material as a part of that panel.  If you are interested in the field of eDiscovery and pragmatic discussions about eDiscovery issues framed in the context of real life situations involving real people, I suggest you consider attending the conference, which will be held in Hollywood Beach, Florida, April 27-29.  Additionally, I believe the ACEDS eDiscovery certification is a worthwhile endeavor and certification.  If you would like more information about it, it can be found on the ACEDS website (www.aceds.org), or feel free to contact me as well.  

About two years ago, I succumbed to the notion that predictive coding was the future in the eDiscovery industry (which was actually fairly accurate) and that this potentially meant trouble for contract review attorneys and their jobs (which has not proven to be true thus far). Click here to read my article on the subject from two years ago.   I was not the only one to succumb to this, and even those outside the eDiscovery industry picked up on it, including the New York Times in a 2011 article by John Markoff, but I must now admit I was wrong and I was being too short sighted.

Two years later and two years wiser (I hope at least!) and document review and contract review attorneys are still common in the eDiscovery industry, and arguably have not been impacted much by predictive coding.  Why is this? In part because of when and if predictive coding is used: predictive coding, although much more accepted and utilized than it was two years ago, is still not universally used.  In my post last week, I briefly discussed some of the reasons for this (cost, trust, human time, sensitivity/importance of the material, objection from the opposing party).  Also in part because of how it is used.  In practice, predictive coding is often employed as a method to prioritize documents or to cull documents, but not as a complete review eliminator; common predictive coding workflows prioritize the responsive material to the front of the review but do not remove documents from the review population, or they may act to cull and remove some, but not all, of the data, leaving the remaining to still be reviewed. 

Despite this, there is no doubt that predictive coding is used and reasonably often.  Since the advent and adoption of predictive coding, the underlying framework of litigation in US courts has not changed and litigants and subpoena recipient’s need to produce material pursuant to discovery obligations continues, and hence the need to cull that data in a defensible and reasonable manner still exists.   Predictive coding technology has become an entrenched part in this and is viewed as a reliable and acceptable tool by the industry now more than ever.

So if the tool that was designed to reduce document review is viewed as viable and is being used, why isn’t document review being reduced?  The answer is that it is in fact being reduced, but not from what it was, rather it is being reduced from what it would be absent the technology; year over year numbers may not decrease, but if the technology were not being used, current numbers would be greater than last years and greater than what they are using predictive coding technology. 

The fact is that data continues to grow exponentially.  One of my clients who is very proactive in their approach to eDiscovery, who is sophisticated and knowledgeable, and who is using predictive coding, is still reviewing the same if not more data per custodian than they were in previous years, even when using predictive coding, because the amount of data they preserve, collect, and search continues to rapidly grow; the new technology, although effective, is only allowing them maintain the status quo, if that.  Without the technology, they would be faced with an unmanageable amount of data to review/produce (at least from a cost perspective).  As an aside, another way that people are tackling big data is via information governance, including how to store less, collect less (searching pre-collection is increasingly a buzz topic), getting data off legal holds etc.   Big data and information governance will be the topic that the panel I am on at the annual ACEDS conference at the end of April will speak to.

What this glut of data means for contract review attorneys, is that even when there is approval and budget and acceptance of predictive coding technology and its use, there is still a place and need for document review and review attorneys.  Moreover, for the document reviewers, the technology has not changed their role or needed skill set much either.  Predictive coding generally adds a step to the process that takes place prior to contract review attorney involvement, and thus, by the time a review attorney is brought in, the process and what they are doing is very much what it has been as of late.

I fully expect predictive coding to continue to push the envelope and gain more and more acceptance and traction in the industry, however I do not see that translating into the extinction of document review or review attorneys.  I continue to think the larger and more real threat to document review comes from things like law schools producing a greater supply of attorneys then the market demands, as well as the proposed changes to the FRCP, and the sentiment those changes embody; corporations are saying enough is enough we need to scale back eDiscovery and the FRCP are a way to do that.

I and others were not wrong that predictive coding would have an impact on the legal industry, we just underestimated how much data growth would negate much of that impact, and in turn, we overestimated the impact of predictive coding on contract review attorneys, who, as it turns out, are not going anywhere for the time being. 

Predictive Coding – A Look at the State of the Technology, the Impact on Review and Review Attorneys, Case Law, and What the Future Holds

PART I of IV: How Far Have We Come and Where Do We Stand

This is the first of four blogs on predictive coding that I will be posting in the next month.  This first entry will focus on how the technology and use of predictive coding has changed and where exactly it stands in the industry today.  The second will analyze and discuss the impact predictive coding has had on reviews and review attorneys compared to predictions regarding the same.  The Third will cover case law on the topic. Finally, the fourth will provide some predictions about what the future holds for predictive coding (yes, more predictions).

I am writing these blog entries in part due to my participation in the upcoming ACEDS conference, where I will be speaking on a panel about Information Governance.  This four part blog series will appear in the conference material as a part of that panel.  If you are interested in the field of eDiscovery and pragmatic discussions about eDiscovery issues framed in the context of real life situations involving real people, I suggest you consider attending the conference, which will be held in Hollywood Beach, Florida, April 27-29.  Additionally, I believe the ACEDS eDiscovery certification is a worthwhile endeavor and certification.  If you would like more information about it, it can be found on the ACEDS website (www.aceds.org), or feel free to contact me as well.  Now, enough with the longwinded introduction and onto the actual substance of the entry:

For the past several years, predictive coding has been the topic de jour in the eDiscovery industry.  It was discussed at every conference and software vendors were scrambling to add a predictive coding module or functionality to their tool and clamoring to show its ROI and impact, often unrealistically overstating reality.  The former is no longer the case, as the industry has moved on to Bring Your Own Device (“BYOD”) as the current hot topic.  However, this is not because predictive coding was a fad or no longer matters, rather it is because it has maturated as a concept within the industry; when you mention predictive coding now in the legal industry, there is a general understanding of the concept and paradigm, and you will receive nods of general awareness rather than blank stares from those you are talking to.  Within the group of those intimately familiar with predictive coding, the distrust of the technology has subsided, and the distrust is often now focused on the process employed to run it and whether there has been sufficient training rather than the concept or idea itself.

The term Predictive coding AKA Technology assisted review (“TAR”) or Computer Assisted Review (“CAR”) among others, has itself grown and expanded, and although people have different thoughts of which is the most accurate term to use, in a very broad sense it is understood within the industry to refer to a technology and process whereby advanced mathematics is leveraged in combination with human input (generally coding) to cull or group a population of documents.  The exact workflow and technology differs by platform and matter, but generally the idea is to leverage technology to reduce the amount of material that is reviewed by humans in an accurate and defensible manner.  The concept itself has gained enough traction that EDRM developed a framework for it known as the Computer Assisted Review Reference Model (“CARRM”):

You can read more about that on their website at: http://www.edrm.net/resources/carrm

Despite the growing knowledge base and understanding of the concept, (as opposed to just the knowledge of the term), that has not necessarily translated into vastly increased use of the technology.  I was at a recent industry event where the presenter engaged in a bit of ad hoc polling.  One question they asked was how many people knew what predictive coding is.  The response was universally yes, the participants did know what predictive coding is.  He then asked how many had actually used predictive coding on a live project.  About 60% of the audience indicated they had.  However, when asked how many times they had used the technology, for most, the answer was only once or at most twice.  This can be attributed to many things including the fact that the industry has only started to accept predictive coding technology relatively recently and hence there have not been many opportunities for many companies to use the technology multiple times.  But while lack of opportunity speaks to this number in part, there is more to the story.  Most people who I have spoken to not only used predictive coding technology relativity few times, but they have done so despite having multiple opportunities to use it, but for which they chose not to.  I would say many companies will use the technology in one in ten or one in fifteen cases, by choice after considering the predictive coding option.

So why are companies choosing not to use predictive coding in every matter or project?  There are a number of reasons, a few of which include:

• The Cost of the Technology – predictive coding is often an extra or add on expense to purchase that is not included as a part of standard technology licensing or even for use on an ad hoc basis.  Even if a company or attorney would like to use the technology, there simply may not be budget to purchase the technology.  If the cost comes down, not surprising it will be used more often.
• The Technology is not Viewed as Being Effective Enough– not all predictive coding tools are created equal, even if the core technology they rely on is very similar or even the same at times.  Whether it is the base technology, the user interface, or the transparency and reporting of a particular tool, perceived deficiencies regarding some or all of these aspects can turn a user off of a particular tool.  If the tool a company spent large amounts to license and work into their processes has sub-par predictive coding functionality, they are not likely to abandon the tool just to utilize predictive coding, at least not quickly.  I work with one client who has an ECA tool and they were given the predictive coding module for that tool as a part of their license.  Nevertheless, after testing they are hesitant to use the module on live data because it lacks transparency and therefore trustworthiness regarding how it makes its decisions and the developers/sales people are unable or willing to explain and clarify better.  This is not a judgment or decision on predictive coding as a whole, but rather on the particular tool available to this client.  For them it poses too great of a risk to use outside of testing.
• The Human Cost to Use the Tool is Too High For the Matter – even if you can afford to purchase or license the of your choice technology, it takes human time and expertise to use and train the predictive coding technology.  Often the person training the system is one who is the most knowledgeable about a matter.  At the beginning of the matter this is often a partner or high-level associate, both of whom bill at a higher rate than a junior associate and certainly more than a review attorney.  While the technology generally works the same on small and big cases, due to the mathematics of sampling, there is a minimum amount of training and sampling that must normally be done in a predictive coding project regardless of population size.  If the document count falls below a certain threshold, normally 50,000 documents give or take, it can often cost more for the higher priced lawyers to complete that training than will be gained by reducing the review population via the technology.  Additional related considerations is finding the time and pressure to make that partner or high-level associate actually review and train the system on several thousand documents, which can take days.  This is not an activity they typically perform and it can be like pulling teeth to get them to do so.  Thus, actually implementing a predictive coding project can be difficult to coordinate and implement.
• The Matter or Material is Too Sensitive – there are simply some matters that are so important to a client, perhaps because the matter at issue threatens the very core and existence of their business, or the money and negative PR at issue is just so great, that they want eyes on review of every document.  While you could still use predictive coding technology to group and organize such a review, given that all documents will be looked at, decision makers often feel the time and expense of predictive coding is simply not worth it in such a case.
• The Party Receiving the Data Does Not Agree – this is most applicable when the government is requesting something.  If the DOJ “suggests” you not use predictive coding, most people listen.   That is not to say that the DOJ is necessarily opposed to using predictive coding, in fact they have agreed to its use previously, including the high profile Anheuser-Busch InBev/Modelo merger (more on that in part three of this series), but they do not always agree to its use as a matter of course, which will obviously impact the responding party

What my experience has taught me is that at the end of the day, the clients and companies footing the bill like predictive coding because it saves costs.  Most are hands off in the process and details and are only generally aware that it is going on or being used.  While they want to comply with their duties to produce, it is the cost savings, not the arguably more accurate and consistent results that drives their adoption of the technology.  If the cost savings are not there they are not using it, and often that decision is being made on a matter by matter basis.  Even when the cost savings are there, that provides the motivation to push counsel to agree to its use, which is not always easy either.  Just as there are attorneys who still prefer to review paper, there are many more that are unwilling to avoid review of documents that hit on a search term just because a computer indicated they possibly could.  So on any given project, there are multiple hurdles to pass before utilizing predictive coding, even when the technology itself works well or even when the economics of it make sense.

What does all this mean?  Well, I suggest that it means the concept and idea is stable and accepted (even if understood on a superficial level by many, it is nevertheless understood now), and it will continue to be used and in fact its use should increase.  Similarly, software developers will continue to develop the technology because their customers will demand they do so.  However, and despite that, predictive coding will not be used in all matters, and may not even be used in most matters, and it will not spell the end of document review or the position of document reviewer.

For a further discussion of, and thoughts on, predictive coding’s impact on document review and document reviewers, please read part two of this series, which will be posted in the coming days.

Olympics of eDiscovery – One Can Dream

Most evenings the past week and a half my wife and I have managed to catch some of the Olympic competition currently taking place in Sochi, Russia.  Something we tune into with some interest every few years.  The Olympics really are a great concept, men and women athletes of diverse background and culture converging together for a few weeks of competition and sport, putting aside differences, history, and politics (for the most part) to compete and prove who is the best at various disciplines.

The competition has inspired me (no not to compete, that would be too cliche) to wonder, what if we could have an Olympics of eDiscovery?  In a geeky eDiscovery way, wouldn't that be great?  I image a competition amongst the various software and tool providers to determine who is best at different tasks: collection, processing, culling, review, TAR, and production to name a few.  This would not be a Gartner style report (which I do find helpful and a must read by the way) but instead, the tools would go head to head at the same time and place using the same data set and hardware horsepower.  Everything would be transparent and there would be a level playing field – no marketing or PR spun statistics, and no closed door exercise where only the “results” are presented.

Medals would be given in each category for different aspects such as speed, accuracy, efficiency, cost, and ease of use for example.  The end result would be bragging rights for the software producers and real useful knowledge and results for consumers like you and me who would finally have some objective data points to make apples to apples comparisons to the extent that is possible in this industry, and also hopefully a little fun as well.

I invite all software vendors big and small to consider this idea and throw your hat in the ring.  If you agree to participate, we, the users, will come.  So kCura, Symantec, Ipro, Kroll, Lexis, FTI, and any others, are you up for it?  I for one would love to see this, and think it would be of great interest to the eDiscovery community.

Quality Control in eDiscovery – The difference Between Luck and Repeatable Success

As an eDiscovery project manager and Director of Client services responsible for ensuring the successful management of my client’s eDiscovery needs, having in place solid processes and procedures that are repeatable and defensible are keys to my success, my team’s success, and most importantly the success of my clients’ projects individually and collectively. Quality Control (“QC”) efforts are a crucial component to my processes and to the success of any project and I strongly encourage you to build them in to your eDiscovery processes and procedures in order for you and your clients to have full confidence in your eDiscovery.

Price, reputation, and plans are all important things to question your eDiscovery vendor about, but so too is QC, and it is not something you should wait until the end of a project to discuss.  All too often at the beginning of a project, people are focused on things like search terms and deadlines, and only turn to QC once the project is ready to wrap up, but really QC should be thought of from the start and should be built into any eDiscovery process, whether it be for preservation, collection, review or production (or any others).  QC will have its greatest impact and save you the most time and money the sooner you start it.  While it can be a cleanup tool at any time in the process, it can serve to prevent further error if started early in a project and its results are then used to identify points of misunderstanding or deficiency in your training or process.  Particularly in review (although not exclusively), once identified, the lessons learned during QC can become examples to provide to your team and retrain them to prevent future error and minimize the amount of recoding or other rework needed at the end of a project, which could blow budget and deadlines.

How much QC you perform and how you carry it out are secondary to the fact that you are performing it; amount QC’d and method of QC are only means to the end, which is accuracy.  If you are correcting the mistakes and have a clean product, that is ultimately what matters.  That being said, there is no one universal QC method to employ in all cases or all situations.  My teams have certain standard QC processes that we perform across clients and across projects, but for each project we also devise QC procedures unique to the purpose and idiosyncrasies of that project. 

My team’s familiarity with our clients, the tools we use, and our eDiscovery subject matter expertise allow us to properly craft these.  However, more and more eDiscovery tools are building methods and applications to assist even non-savvy users in QC.  One such functionality that many document review platforms are starting to incorporate is a method for creating random samples either by front end users or on the back end by administrators.   But even if you program does not offer this capability, you could use Excel to create a random sample of your material for QC; QC is not limited to only those who are technologically sophisticated or have the funds to afford expensive eDiscovery software.

To close out this article, I would like to again stress that while how you QC is important, the fact that you are doing it and doing it early in your project are what matters most.  Although performing QC will still have utility if you start it late in a project (and indeed at times it may be unavoidable),  in most instances the sooner you start the better, so you can identify issues and correct them before they perpetuate and potentially blow your budget or deadlines at the end.  That is not to say that performing QC at the start of a project alleviates the needs to QC at the end, rather QC at the beginning sets up a successful, succinct, and efficient QC at the end of a project.

QC may not make your product perfect, and it does not mean mistakes will not happen and still may not be caught, but what it will do is minimize those risks, while also providing an air of reasonableness to your actions so that if something does go wrong you can stand behind your efforts to avoid the error and point to your repeatable defensible process.

Musing on the First Day of the Third Annual ACEDS Conference

Last evening, while pondering such existential questions as who would win in a fight between the Retrivika pink elephant and the Megaputer sphinx, or who would dominate a closed ring wrestling match between Charles Itriago and Patrick Oot, my mind slowly turned to the panels and participants from the first day of the third annual ACEDS eDiscovery conference.

Speaking with attendees, it seems the conference delivered on educational content (panels included predictive coding, malpractice, data retention and project management) and creative delivery format – the most interesting format included a parade of 20-30 experts who each provided a best practice tip in one to two minutes.  ACEDS’ genuine effort put into developing new content and formats is commendable and something that the participants stated leads to an enjoyable conference experience.

The predictive coding panel, like most of its kind, focused very much on the future and what will be next with that technology.  Somewhat conversely, the malpractice session offered advice and tips for preventing and preparing for malpractice and obtaining malpractice insurance today.   Essentially the message was: get your ducks in a row before the issue arises or before an event occurs.  The other panels delivered everyday tips for pragmatic application and use.

One interesting observation came from a vendor attendee.  This individual noted that there were fewer sponsors at the conference this year compared to the previous year.  Interestingly this individual said this is a trend they are seeing across the eDiscovery conference industry.  What does this indicate?  Is the conference scene too saturated?  Is the ROI for attending a conference the past few years no longer attractive?  Are the conferences not bringing value from the vendor perspective?  More importantly, what is the impact if this trend of fewer sponsors continues, and will it have a negative impact on the knowledge base and discussion in the eDiscovery field?  I certainly hope that is not the case and that this trend does not have a negative impact on the eDiscovery industry.

ACEDS Third Annual Conference Begins – Predictive Coding in the Spotlight

The third annual ACEDS conference kicked off today.  The conference, which takes place in South Florida brings together top industry experts and focuses on the delivery of eDiscovery related knowledge from both a legal and technology perspective to individuals who are eDiscovery novices, experts, and all those in between. 

The agenda for this year’s conference covers a wide array of topics, but, not surprisingly has a heavy focus on predictive coding; indeed predictive coding has been a hot topic in eDiscovery for at least the last year, and will continue to be the main talking point in the industry for this coming year as well.  If the conference did not address this topic it would be odd indeed.

I am attending the conference as a participant and as a sponsor/vendor for the company I work for.  I thought this would be a good opportunity to end my hiatus from blogging.  I hope to provide you analysis and summaries of some of the sessions, as well as my thoughts that are inspired by the sessions.

The first panel of the conference discussed predictive coding and provided a primer or introduction to its current state and what it is.

The panel noted aptly that there are currently about 7 cases that have written opinions addressing the topic, but that number will likely will be 70 by this time next year – right now you have can have a firm, detailed, grasp of all case law on the subject, but in the future that will not be the case.  This demonstrates how this is an emerging trend and technology that the courts are catching up to.  The cases thus far point in the direction of predictive coding becoming more important in the sense that if the technology is really better at identifying responsive material that current practices (with the corollary that that data will be produced) then it should be used – potential implications include sanctions if you do not use the technology because of the inference that you are not turning over relevant data if you are not using predictive coding – of course we are probably a long way from any such a finding or opinion, but it is a glimpse into judicial thinking and a future distant but growing closer every day.

Personally, I know that proponents will continue to push this technology, and rightly so, but concepts such as proportionality, accessibility, and fairness still override.  Meaning that due to cost or some other factor, predictive coding still may not be the best solution for any given matter.  A $50,000 matter is still only a $50,000 matter and extensive discovery costs will rarely be warranted in such a matter regardless of how effective a technology is or is not.  Likewise, a $100 million dollar matter with millions of documents comprised largely of spreadsheet type data is not a good use case for predictive coding despite the value and data volume, because at this point in time, the technology does not work well on that data type.  There are still many variables that need to be considered on a case by case basis when deciding if you will use predictive coding in a given instance; evaluate all of your options including, but not limited to, predictive coding technologies.

Importantly, as this technology develops, what companies need to start looking for are experts in predictive coding technology, its use, its limits, and when and how to use it efficiently and effectively.  Such experts may or may not exist at this time, but one thing that the past development of eDiscovery related technology has taught us is that today’s expert and today’s top performing tools, may be outdated and archaic next year.  The eDiscovery field, and particularly the applications that support it, are ever evolving at a pace far greater than many other areas of technology, and certainly much faster than virtually all other legal related technologies.  This makes it difficult for individuals and corporations, whose sole focus is not eDiscovery, to stay on the cutting edge and ensure they are meeting their needs (whether that be the best of the best technology or something that at a minimum adequately gets the job done, even if it not the best tool).  For such individuals and corporations, their eDiscovery and technology experts and vendors will be key drivers of their success (or lack thereof) and readiness to adopt the best technology. 

My advice to you is be aware of and understand the predictive coding concept, so that you can ensure your vendor has the requisite knowledge and is actively participating in the predictive coding discussion and is on the cutting edge of this trend, vetting and finding the best solutions for you and your case(s). 

eDiscovery 2012 – Where We Have Been and Where We are Going – A Look Back At the First Half of the Year and Predictions For the Last Half of the Year

2012 has been an active and interesting one on the eDiscovery front thus far.  What follows are a few trends from the first part of the year and some predictions for the remainder of 2012 and beyond.

Where the eDiscovery Industry has been Over the First Part of 2012

1.  Predictive Coding – It is all the rage and this year’s hot topic in eDiscovery.  Will it revolutionize the industry and document review in particular?  Possibly.   Is it going away anytime soon?  Nope.  As an eDiscovery practitioner, do you need to know about it?  You bet you do.  The first part of 2012 has witnessed all of the major platform providers rushing to integrate this technology into their product, and some will ultimately have better products and be more successful than others are.  Remember, not all so-called predictive coding tools and technologies are created equal.  So, while the trend is to offer predictive coding, time and customer satisfaction will sort out who offers the best product for the right price.  Regardless of which company or companies win this battle, quality predictive coding products are starting to be, and in the future certainly will be, major players in the field for years to come.

2. Da Silva Moore – Any discussion of predictive coding in 2012 would not be complete without a mention of the Da Silva Moore case.  The most highly discussed and scrutinized eDiscovery case in years, Da Silva Moore once focused on judicial approval of predictive coding but quickly denigrated into a motion battle focused on Judge Peck’s actions rather than the merits and proper use of predictive coding.  Nevertheless, the case has brought tons of publicity to predictive coding, and may yet have a larger impact on the technology, as the case, and all the acrimony, churn slowly on without a definitive resolution to the predictive coding aspects.

3.  Spoliation and Proportionality – These topics have played second fiddle to predictive coding this year, but case law indicates that courts are considering these principals more and more and they are holding litigants to tighter standards.  No longer can clients or their attorneys get away with claims of being unaware or ignorant when it comes to spoliation.  Likewise, litigants are becoming bolder in challenging requests for large amounts of data, and judges are agreeing to limit requests in greater frequency.  Furthermore, it is a proportionality argument that lies at the heart of predictive coding’s value and reason for use; given the ever-expanding amount of data in the world, it is no longer proportional to review every document without the aid of technology and technology assisted review, such as predictive coding.

4.  Consolidation – The software products used in the eDiscovery field and the companies that create them are in an arms race to see who can add the most functionality to their product across the EDRM spectrum.  This creates one-stop shop products, but may also drive niche, one function, products out of the market and raise prices.  Additionally, although the products may do it all, they may not do it all well.  Similarly, law firms are challenging eDiscovery vendors by creating their own eDiscovery practice groups and bringing the latest technology in house in an effort to bring those billable hours back into the firm, but at what cost to clients?

5. Model Orders, State Rules, and Pilot Programs Oh My –  Since late 2011, there have been a plethora of eDiscovery related standards, rules, model orders, and programs unveiled by different entities around the country, including: the U.S. Court of Appeals for the Federal Circuit, the U.S. District Court for the Southern District of New York, the U.S. District Court for the Eastern District of Texas, the U.S. District Court for the District of Delaware, the State of Pennsylvania, and the State of Florida.  Additionally, the Seventh Circuit recently concluded phase two of its Pilot Program on eDiscovery.   These various efforts are driven by a desire to standardize procedures and practices to contain eDiscovery costs and avoid unnecessary delays and disagreements.  Some will have greater longevity than others will, but they are all evidence of a growing judicial and administrative recognition of the impact eDiscovery is having on our legal system and the need to do something to improve the situation.  Likewise, the diversity of solutions offered is evidence of eDiscovery’s complexity and the lack of consensus regarding how to approach and manage it.

Where will the eDiscovery Industry Go Over the Next Six Months and Beyond

1.  Da Silva Moore – The Da Silva Moore case will continue to dominate the eDiscovery headlines, both as theater, and eventually as precedent (even if unofficial).  This is by far the highest profile predictive coding case that exists and everyone in the eDiscovery industry is waiting to see how it turns out.  Given its high profile, there will undoubtedly be much analysis and commentary on the outcome of the predictive coding battle and the case itself.  Hopefully, the scrutiny will shed some light on the cost, accuracy, and efficiency of predictive coding in a real case using real data.  If that does in fact occur, that will be lasting legacy of Da Silva Moore on the eDiscovery world, one that is much nobler and of higher value than the soap opera it currently perceived as.

2.  The Cream Will Rise to the Top – Certifications, conferences, and eDiscovery education providers will continue to vie for prestige, patronage, and above all your long-term support.  Over the past few years, we have seen numerous eDiscovery organizations and conferences spring up, including, among others, ACEDS and its annual conference, the Carmel Valley eDiscovery Retreat, and the Electronic Discovery Institute’s EDI Leadership Summit.  At times, these events have directly competed against each other and the various organizations and conferences that already exist.  At the same time, longstanding original players like Sedona and EDRM are looking at their purpose and goals and deciding on what and how they should focus their energy in the future to remain relevant and influential.  The eDiscovery conference market has reached a point of saturation, with people in the industry only willing to attend so many events a year and recognizing that there are only so many relevant panel topics.  From a participant’s perspective, why would you spend thousands of dollars to attend a conference that has four to five panels on the same topic (which topic by the way is also discussed at every other industry conference)?  From a vendor’s perspective, why would you spend thousands of dollars for an exhibit at a conference that is primarily attended by other vendors?  These competing organizations and conferences must find ways to differentiate themselves and provide a unique value proposition or the market may force them out.

3.  Smart Phones, Tablets, and Social Media are Game Changers - More and more I am hearing how e-mail will soon be replaced as a communication medium by methods such as texting and tweeting among others.  While I am not ready to declare e-mail dead (or even dying), there is no doubt that data created by non-traditional devices and/or in non-traditional sources (such as smart phones and tablets and on social media sites) will continue to proliferate both in data volume as well as in potential collection sources.  New niche industries and players (X1 is an example) will develop to preserve and collect this data in an accurate and useable format, and practitioners will need to adapt and fit this data and this new technology into their processes and workflows.  Individual social media sites and companies may disappear, as may technology brands and models, but the mobile social media lifestyle itself, and the challenges it poses for eDiscovery will not disappear.  The eDiscovery industry needs to catch up as quickly as it can.

What exactly the next big thing or big case in eDiscovery will be is difficult to predict, but regardless, the eDiscovery industry has been, is, and will continue to be an interesting, evolving, fast pace industry that is one to keep an eye on.

Gartner Releases 2012 “Magic Quadrant for E-Discovery Software”

Gartner recently released its now yearly report “Magic Quadrant for E-Discovery Software.”  The report analyzes the biggest names in the eDiscovery software field and categorizes them into one of four groups: Leaders, Challengers, Visionaries, or Niche players.  The report focuses heavily on consolidation within the industry as well as the EDRM lifecycle, placing a high value on companies and software that service the entire EDRM lifecycle.

The writers designated six companies as leaders:

- AccessData

- Autonomy

      - Guidance Software

      - Recommind

      - Symantec (Includes Clearwell)

      - ZyLAB

To be leader the company had to offer functionality that covers the complete EDRM lifecycle.  Additionally, offering predictive coding technology was an important positive factor in this analysis.

Some changes from the 2011 report include the exclusion of Epiq and IPRO because they no longer met at least one criteria for inclusion in the Magic Quadrant, the inclusion of KPMG and UBIC in the Magic Quadrant, and the change in status for FTI and kCura from leaders to challengers. 

kCura and FTI were no longer considered leaders because both focus on the right hand side of the EDRM only, rather than focusing on the complete model.  This fact emphasizes how much weight the Gartner writers placed on servicing the EDRM lifecycle.  To be clear, the report noted that kCura’s Relativity product is still a best in class product.  It also spoke very highly of FTI noting “[t]he company performs well all over the world, whereas others in its class do not necessarily have the presence or ‘bench strength’ to cover the globe, which is what many corporations need.”  Nevertheless, it likewise noted that many vendors are responding to the market with “broader end-to-end” functionality.

I agree with the report that the industry is moving toward greater consolidation and products that do it all, and I have written about that movement on this blog (http://ediscoverynewssource.blogspot.com/2012/04/consolidation-of-services-and.html )  However, I believe that Gartner placed too much emphasis on this factor by making it a requirement to be a leader in the Magic Quadrant.  Certainly, one-stop products and companies that do it all offer convenience, and perhaps cost savings, and can absolutely be the best choice for you and your companies.  Likewise, I continue to think that more and more products will move in that direction.  However, at this point in time, choosing a product that does it all means sacrificing quality and functionality for convenience; products and companies that service the entire EDRM lifecycle may be competent at each area, but they are not going to be the best at each area.  Depending on your situation, choosing multiple products that are the best product available for each task may be a better option.  You should ask yourself, do you want one product that does everything, but only one of those things really well, or do you want three or four products that are all the best at what they do?  There is no one answer, but it is something to consider, and this will remain a choice you have to make until there is one product that is the best at everything, which could take a while.

Although the Gartner report is subjective and by no means does it analyze every product or company in the industry, overall, the creators did a good job and the report provides some interesting information and analysis.  The report concludes that the eDiscovery software industry will remain relevant while becoming more competitive, and that consolidation and the proliferation of one-stop shops and products will continue.  This prediction is spot on.

Contract Attorneys – The Latest Addition to the Endangered Species List

Last week I read an article on law.com titled “Does Predictive Coding Spell Doom for Entry-Level Associates?”  The article was prompted in part by the attention predictive coding is currently receiving as the de jure eDiscovery topic and the starring role it has played in the increasingly soap opera like Da Silva Moore case.  The article concluded that entry-level associates were still necessary and vital assets, even with the rise of predictive coding. 

I agree with the article’s conclusion, and am happy for the associates, but what about their less well placed colleagues, contract attorneys?   The threat for survival that contract attorneys face comes not just from predictive coding but from law schools that spill new graduates like a broken faucet, as well as from employers that take advantage of the situation by offering unscrupulously low wages knowing that for every position they have, there are several applicants willing to fill it at almost any rate or cost.  So, is there still a place for contract attorneys?  Will predictive coding and the deluge of law school graduates wipe out their positions, or depress their value to the point where the attorneys would make more money working at McDonalds?  I hope the answer is no, and the answer should be no if the legal community takes a moment to realize they need to treat contract attorneys  like the nonfungible assets they can be, rather than as pariahs who are undeserving of earning even $20 an hour. 

Despite their persona non grata reputation, a quality contract attorney is worth their weight in gold, and the legal industry should do everything it can to ensure they do not go the way of the dodo, whether because of technology, wages, or anything else.  Contract attorneys’ hands-on expertise and knowledge of review platforms and software can add great efficiency and effectiveness to a project.  Their in-depth familiarity with the documents and details of a case can be illuminating, and their understanding of the eDiscovery process can be a difference maker.  The truly good contract attorneys are knowledgeable experts that can be leveraged to your advantage and provide valuable input and consultation to your case and how you prepare for it.  More than hired mercenaries whose goal it is to plow through data as quickly as possible, contract attorneys can be your eyes and ears in the data.

At the end of the day, you get what you pay for, and nowhere is that more true than with contract attorneys.  You may be able to fill positions offering wages as low as $15 an hour, but that will not get you much more than a warm body.  With such a low rate of pay, a contract attorney will have every incentive to look everywhere and anywhere for a different job.  They will lack quality, consistency, motivation, and loyalty, resulting in a poor quality review, even if cheap.

Alternatively, as with most positions in life, the more faith and responsibility you show contract attorneys (along with paying them a decent wage for someone with a law degree) the more you obtain from them and the more value they will add to your case.  I urge you to look beyond the mere number efficiencies technology such as predictive coding can provide, to look beyond the hourly rate you are paying, and to focus instead on the intangible values added to your overall case.  That is where you find the true value and worth of your contract attorneys, and where you will find, if utilized properly, the good ones are invaluable and indispensible.  Do not get me wrong, I am not suggesting that you should forgo the use technology or that you should be offering your contract attorneys partner level compensation.  I am simply saying that technology should be used to supplement and enhance your contract attorneys’ value and capabilities, not replace them. 

Despite advances in technology, the human element of eDiscovery remains more vital and important than ever.  A key component of this human element is the contract attorney.  Even with the advance of predictive coding and like technologies, skilled contract attorneys should continue to be valuable commodities undeserving of a place on any endangered list.

Native Redactions – An Emerging Trend

It is a commonly accepted practice within the eDiscovery industry to image documents for production.  Likewise, it is now a commonly accepted practice, and indeed even a preferred practice, to exempt spreadsheets (and some other file types) from that requirement, instead producing those documents natively.  The idea being that parties would rather obtain native spreadsheets allowing them to work with and view the content in a meaningful manner rather than receive spreadsheet images that can be useless, cumbersome, or exceedingly difficult to accurately use and understand.  There is a nascent trend of not only producing spreadsheets in native format, but redacting them in native format as well (the concept has existed for years but is becoming an increasing point of emphasis as of late).  

The inherent nature of a spreadsheet means that it often contains complex data located in multiple rows, columns, and tabs. The data often includes or involves the use of formulas, sorting, or filtering amongst other features.  Macros, pivot tables, and hidden content add to the complexity.  If printed, the data often falls across multiple pages in a less than complete and less than orderly manner resulting in a confusing mess that is difficult to cobble together, let alone read and use.  The fact of the matter is that images simply are unable to capture the complexities many spreadsheets contain, so if the document and its content are to be useful and meaningful, you must produce them natively.  Most litigants now recognize this and are comfortable with, and often require, the native production of spreadsheets.  Yet, traditionally they have been less than enthusiastic about redacting spreadsheets in native format. 

Given that it is an accepted practice to produce spreadsheets natively, because that is how they will be most useful, why should redactions change that?  The answer is that it should not, and more and more practitioners are beginning to realize this.  Redacting changes the data in the spreadsheet, but it does not change the nature of the spreadsheet, the functionality of it, or how one uses the spreadsheet.  If a spreadsheets needs to be produced natively to be useful in its non-redacted original state, then logically it should be produced natively to be useful in a redacted state.

Anecdotally speaking, as time goes on, I am seeing much more acceptance and understanding of the native redaction practice across the industry.  My colleagues are telling me that they are seeing the same thing.   I am confident that it is only a matter of time before redacting spreadsheets in native format is the norm and an accepted standard and practice by courts and litigants alike; native redactions simply make the most sense for spreadsheets.

One of the hang-ups for those who are unfamiliar with native redactions lays in the subconscious or gut feeling associated with making redactions to a native document.  Redacting (i.e. deleting) content from native format documents that you are producing somehow feels inherently wrong, as if there is somehow a difference between covering up the data in an image redaction and deleting it in a native redaction.  In reality, and despite this feeling, if done properly, there is no meaningful difference between image and native redactions, or between covering up and deleting.  With each method, you are hiding data in an attempt to ensure the opposing party does not see it.  Whether the data is hidden beneath a box or darkened out area on an image, or deleted from a native document, the goal and result (hopefully) is the same: the data is not visible or searchable.  As long as you redact properly, and are open and honest with the opposing part about what type of redactions you are making, why, and how, there should be very little issue when redacting spreadsheets natively rather than via image.

Of course there are risks with native redactions, and native productions in general, including the loss of metadata, loss of formulas, changing dependencies (e.g. cell values based on formulas or the values in other cells) and the risk of manipulation by the opposing party to name a few.  However, there are methods and mechanisms for addressing these risks, and you can, and should, discuss them with your eDiscovery experts and the opposing party, before taking action.

However, from a strictly results perspective, if done properly there is no reason why the native redaction of spreadsheets should not be acceptable.  This argument carries even more weight if the parties are producing non-redacted spreadsheets natively; in that instance the parties identified value in producing non-redacting spreadsheets natively, and that same value would exist for redacted spreadsheets.  Driven by this logic and the comfort that will come as litigants gain familiarity with native redactions, more and more parties will turn to native redactions for documents like spreadsheets.  In the not so distant future, natively redacting spreadsheets will be a commonly accepted practice and standard in the eDiscovery industry.