Best Practices for E-Discovery
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Andy Moore . . . 2
Who’s NOW In Charge of Information?
The balance—and I could call it tension—between the corporate legal counsel department and their IT/technology counterparts has never been greater. Nor has the need for cooperation between them ever been greater. That was my opening gambit in this month’s KMWorld White Paper opening article. It is not unknown to me that the role of IT versus (“versus” seems a little strong, but I’ll get to that in a minute) the legal side of the house has ratcheted up a few notches in recent years. In past years (all of five years ago) it was IT’s job to collect and "high-level analyze” (meaning “sort”) the various documents, email, financial content, etc. . . .
Jay Leib, kCura. . . 4
The New Axiom of Computer-assisted Review
Offering legal teams a forward-thinking solution to the problem of big data, the topic of computer-assisted review is the conversation du jour in the e-discovery marketplace. There’s good reason for that. According to a recent Rand Corporation survey, document review is the single most expensive step in the discovery process. Logically, the option to reduce time wasted on irrelevant documents can make a big difference in any case, particularly on costs. Therefore, when it comes to document review, legal teams see huge value in the ability to quickly separate the wheat from the chaff. . . .
Tim Leehealey, AccessData . . . 6
The Future of Mobile E-Discovery
In the business world, the use of mobile devices such as smartphones, cell phones and tablet devices is proliferating. This presents enormous challenges for attorneys who oversee electronic discovery (e-discovery) for organizations.
As of February 2012, 88% of American adults have a cell phone, 46% have a smartphone, 57% have a laptop, 19% have an ebook reader and 19% own a tablet, according to Mobify (mobify.com). Mobile devices are growing increasingly sophisticated, and the market shows no sign of slowing down.. . . .
John Felahi, . . . 8
Why the Smart Money Checks the Analytics Engine
Three elements characterize superior preparation for e-discovery: good document
housekeeping; precise extraction and distillation capabilities; and unified workflow from the left through to the right of the EDRM model. This article talks about the latter two, but it’s useful to quickly touch on housekeeping. Good housekeeping means saving, and properly categorizing, only what makes sense from the practical, regulatory, and legal points of view. The cleaner the corpus of documents, the better you are able to respond as discovery progresses through early case assessment, review, production and litigation. . . .
Prateek Kathpal, Accusoft . . . 9
Collaboration in E-Discovery
Anyone who has been involved in the e-discovery process for a case understands that it can be complicated, time-consuming and require the involvement of several people from cross-functional teams. Any lack of collaboration between the different teams can lead to severe consequences, such as additional time and cost, duplication of efforts and potentially not communicating critical observations. Even just a few years ago, most documents existed in the form of paper and the discovery process would involve going through that paper, along with the supplement request, to review the available electronic data. As the world has evolved, more and more documents are stored electronically. . . .
John Tredennick, . . . 10
Cloud vs. Appliance: Comparing Total E-Discovery Cost
An ongoing debate among e-discovery professionals is over which is the better platform for hosting document search and review: the cloud or a local appliance. Among those who favor an appliance, a common argument is that bringing e-discovery in-house will reduce costs. But will it? One way to find out is to analyze the total cost of ownership (TCO) of cloud-based and appliance-based e-discovery platforms. Only by laying out all of the expenses required to support an application—including infrastructure, technology, staff and ongoing operational expenses—can one accurately evaluate its cost. . . .
Content Analyst Company
an impact on e-discovery procedures and practices.
Tim answered first, by clarifying a little bit about how his company views the mar-ket landscape, and its opportunities. “The messaging of our company is about inves-tigation, and the many facets that takes. E-discovery is simply one of them. The dif-ference between e-discovery and data forensics is really subtle. But when you
talk about ‘forensics,’ you’re mainly talk-ing about criminal discovery. When you talk about ‘e-discovery,’ you’re probably talking about civil litigation discovery. But it’s really only the spectrum of the discov-ery, and the emphasis on the workflow that determines what is considered evidence. For example, if you look at the softwaxre applications used to do those two things, you’d say ‘Wow, these are very different. They don’t even fit the same market.’ But, a software developer would look at them and say: ‘They are exactly the same, just with a different user interface!’ So, it’s a matter of perspective.”
I get it. The difference between civil and criminal discovery is one of depth. The prod-ucts these guys sell can do both. It’s about the workflow, and the hoped-for end result. The only meaningful difference is the user inter-face. Flip one bit, and you got the same prod-uct, from a developer’s perspective.
Jay jumped in: “Yep, where it gets interesting is downstream, after the data has already been prepared and ‘cut up.’ It could be documents, emails, structured data... the important thing is to help the professionals who have to make decisions about the data... lawyers, paraprofession-als, support staff. These are mostly the bread-and-butter cases that just have a sin-gle custodian in charge, but they also range up to the cases that have hundreds of deci-sion-makers and thousands of documents.” But what also happens, they both told me, is a cross-over of interest. Forensic accountants have to get to the email that refers to the spreadsheets. Legal counsel needs help to wade through the vast infor-mation stores. Investigations take many different paths during their duration. It started to get interesting, from an organiza-tional viewpoint.
The Changing Roles
So I got right to it: To what degree, I asked, have the roles within the organiza-tion—legal, IT, line-of-business, executive suite—shifted in terms of their impact on e-discovery, and their relative importance as far as their influence over e-discovery efforts? To me, it seems like the roles that IT and busi-ness and legal play have subtly shifted.
Tim (correctly) jumped on that: “That dynamic you suggested will be the most sig-nificant change in the industry over the next several years. We think of it this way: foren-sic investigations gather the data from upstream. The analytics companies process it. The reviewers apply even higher analytics so finally decision makers can make deci-sions. But these people never sat down and said to each other, ‘Hey, you do this job and I’ll do that job.’ It’s more a function of the tools they use. It’s the technology tools that have dictated the various roles,” he said.
Who’s NOW In Charge
of Information?
T
he balance—and I could call it tension— between the corporate legal counsel depart-ment and their IT/technology counterparts has never been greater. Nor has the need for coop-eration between them ever been greater.That was my opening gambit in this month’s KMWorld White Paper opening article. It is not unknown to me that the role of IT versus (“versus” seems a little strong, but I’ll get to that in a minute) the legal side of the house has ratcheted up a few notches in recent years. In past years (all of five years ago) it was IT’s job to col-lect and “high-level analyze” (meaning “sort”) the various documents, email, financial content, etc., and then be a good boy and give it to the kind attorney who knew what to do with it. And for a while, that seemed like a good plan. IT had plen-ty to do anyway, and legal was a league of specialized gentlemen that would “just take it from here.”
I call it the “throwing it over the wall” era. That time has passed, ladies and gen-tlemen, and the revolving door of “who’s in charge” when it comes to civil litigation, legal disposition and even criminal foren-sics has turned around.
As usual, I found some experts in the field to inform me, because I am a neo-phyte to this area. Pretty much like all the other ones. I spoke with AccessData’s CEO Tim Leehealey and Jay Leib, chief strategy officer for kCura.
It is not unusual during the interviews for these monthly articles for the parties to polite-ly agree and also politepolite-ly disagree. This con-versation was no different, except for one thing: they entirely agreed that the roles of IT and the roles of the legal departments in cor-porations—especially big ones—have been utterly altered. And guess why? Technology.
My opening question was, as always: What’s new? In this case, we went through a period of massive change (here in the US and abroad as well) but mainly starting in early 2006 with the FRCP amendments. Please educate me on any more recent decisions/findings/updates that have had
Andy Moore is the publisher of KMWorld Magazine. In addition, as the editorial director of the KMWorld Specialty Publishing Group, Andy Moore oversees the content of the monthly “KMWorld Best Practices White Paper series,” in print and online, as well as assisting with the creation and content of several single-sponsored “positioning papers” per year. He is also the host and moderator of the popular KMWorld Web event online broadcast series. Moore is based in Camden, Maine, and can be reached at [email protected]
Andy Moore
By Andy Moore,
Editorial Director, KMWorld Specialty Publishing Group“The difference
between civil and
criminal discovery
is one of depth.
The only meaningful
difference is the
user interface.”
“Five years ago, IT people gathered data, and then passed it off. They threw it over the wall to some analytics company, which threw it over another wall to an investigation company, who then threw it over to the final decision-makers. But today, the IT people WANT to do more. And in-house legal counsel wants to do more also. Nobody wants to hand it over to a third-party that is going to charge through the nose,” said Tim.
“It’s because the tools have become more powerful,” Tim argued. “They allow you to gather, collect and analyze from beginning to end. We’re seeing major com-panies where the IT department literally does it all, from beginning to end. Only at the very end does legal jump in to make the final decisions... because they don’t want to do it until they are absolutely forced to,” he laughed. “Legal is willing to concede dis-covery to IT, and IT is willing to take it on, because it’s a big value-add they can bring to the company. Because the tools are bet-ter, this dynamic of throwing over the wall is totally disappearing.”
So, I wondered, what has changed so dra-matically to create this utter dissolution of the usual pattern of “collect/analyze/decide” spectrum? Is e-discovery a noun or a verb? In other words, should companies be preparing for “e-discovery” as an ongoing, constant activity (that’s the “verb” part”)? Or is prepa-ration for e-discovery OK to do only when forced to (that’s the “noun” part)? And why? Is it an economical issue? A risk issue?
Jay Leib is nothing if not pragmatic. He jumped in: “The very implication of e-dis-covery and investigation means it’s a downstream, reactive scenario. That’s what the industry has been catching up to: an event happened, now we need tools. But the general counsel’s office doesn’t have any budget! They are a cost center. The GC office doesn’t have the money to spend on the necessary tools. So they are required to partner with IT to pay for it,” he explained.
“What the more sophisticated compa-nies are realizing is that they’re spending money through the nose on reactive scenar-ios. They know they have to get out in front of these e-discoveries and investigations,
and they are now considering it a business issue,” insists Jay.
“That stems from a variety of reasons: the amount of data, first. Then the retention policies, the applications we use and the freedom we allow employees. So how do we include in-house counsel, outside coun-sel, IT and business to have a risk profile that makes sense?” he asked somewhat rhetorically. “Well, it can take many forms: You can have internal review that takes into account everything from the email down to the review system, or you can outsource everything and focus on selling widgets. The new difference is that they’re now looking upstream, and trying to figure out how to reduce costs. How do we get this legal and litigation spend lower?” said Jay. The answer, I think, seems to be bring it in-house, and use automation tools to cover the difference.
Who’s In Charge of Costs?
I asked about the cost-avoidance issue: To what degree are companies avoiding/under-playing information governance in response to current economic conditions? Or, is it the other way around...are your customers seek-ing out information governance as a cost-sav-ing measure?
“IT has been wanting to get more involved and add more value for years,” added Tim. “But legal would push back and say, ‘You just do the collection; we’ll take care of the rest.’ And the way they did that was to outsource it. IT would say, ‘Wait we can do more. Just give us the chance!’ What’s happening now is that IT is proving that they CAN do more, and that legal is sitting there with tons of egg on their face because of the costs. IT can now say, ‘Remember those guys you were spending $30 million for no value? Watch me press this one button and do the same thing.’ IT has become such a powerful player as a result that it is really difficult for legal to say ‘Just be quiet.’”
Jay wanted in: “IT has become MUCH more business savvy. And much more strate-gic. They’re connecting the dots between dif-ferent groups. They are the connection between strategic groups, information governance groups, compliance officers,
regulatory concerns... that is absolutely what has changed. It is no longer about throwing more horsepower and renting rack space...” It’s not just the plumbing anymore.
Is information governance something that can be taught as an employee policy? Or, because of its importance and potential risk, something that needs to be imposed as a system or technology effort? Or is it a combination?
“Governance and information manage-ment has largely been a failure,” said Jay, somewhat surprisingly. But he had a point. “90% of the world’s information has been created within the past two years. No mat-ter what policies you have in place, it’s like
Jurassic Park... employees will figure out
a way around it.
“Technology solutions to this point have not been designed with the workforce in mind,” said Jay. “But now we’re in the gold-en age of collaboration. Coming out of this financial crisis, business leaders are starting to say: ‘Communicate more. Collaborate with your colleagues. Tweet.’ But the poli-cies have not caught up yet,” he said.
“What we need is the right technology in place to find the important data, no mat-ter where it is,” added Tim. “And eliminate irrelevant data. But data storage policies have been a failure to this point.”
“Having a policy that is published and distributed in a three-ring binder is good, but it doesn’t mean you’re not hosed,” said Tim. “Maybe the CEO doesn’t go to jail, and that’s a good thing, but the larger repository technologies just aren’t working. I just don’t think the technologies are on the market to do what the market wants.”
“The problem with policy,” Jay said, “is that it usually sits on a shelf. But policy is fluid and organic. Who anticipated DropBox three years ago? The issue is that there are so many versions of information, saved and kept and generated… that’s what’s changed. It’s just harder to find the
substantive documents.”
Please read on for more insight into discovery, and governance and the role that various corporate departments play in the mitigation of risk and the enhance-ment of control in the corporate informa-tion universe. ❚
“The very implication of e-discovery and investigation means it’s a
downstream, reactive scenario. That’s what the industry has been
catching up to: an event happened, now we need tools. But the general
The Experts
When using computer-assisted review, what teams are finding—and what we’re consistently encouraging our users to con-sider early on in a case—is that the review-ers involved in a computer-assisted review are the ones actually producing the results that the computer suggests. As much as it may seem like a black box, the computer results do not magically appear.
The reason for that is simple: someone needs to train the computer to do its job, and there’s no one better for that task than the reviewers with expertise and insight into a case. As with human reviewers, an out-of-the-box algorithm won’t automatically know what to look for when it’s faced with thou-sands or millions of documents. It, too, needs to learn from an expert teacher how to do its job well. The benefit of the computer, of course, is that it can apply this learning much faster while still giving reviewers the opportu-nity to validate the results with statistics, which we’ll discuss in more detail later.
The trick behind that quick learning is the computer’s absolute acceptance of what it’s being told. During a training round, an incor-rect—or even borderline—decision submitted to the computer may train the algorithm inac-curately. At the same time, a document that may be relevant to the case, but that does not contain the right amount of text to train the text-based system—a calendar invitation, for example—could also confuse the computer. Thus, it is extremely important to have reviewers not only understand the issues, but understand how to properly train the system. Solid results from a smaller manual effort can be replicated across a document uni-verse, slashing review time and cost while maintaining validated, defensibly sound and effective results.
In one recent case, Am Law 100 firm McDermott Will & Emery used computer-assisted review for a second request. Surrounding a large merger, the document universe included more than 1.6 million records after de-duplication and initial date filtering. Based on McDermott’s calculations, a linear review of those documents would’ve cost $2.4 million—an unsatisfying price tag. However, the team had plenty of expertise in the case, so they could easily use computer-assisted review to train the system with good
examples and ultimately amplify their efforts. The team removed more than 1.1 million of the original documents from traditional review. In the end, McDermott saved their client more than $2 million.
In another example, Am Law 200 firm Dickstein Shapiro received a production set of 1,000,000 pages of documents from opposing counsel. Rather than using the projected staffing of 10 contract attorneys and 2,800 hours of review time, the team used computer-assisted review and managed to review the data set with three of their own attorneys and 250 hours of review time. Based on projec-tions, the firm anticipated savings of more than $120,000 on review—while, at the same time, using their own expert team rather than con-tract attorneys. They had the benefit of training the system with true subject matter experts— which made the process quick and easy with great results—without sacrificing cost.
As is clearly indicated by these cases, human expertise is the foundational element in a successful computer-assisted review. A human team establishes the rules and issues of any review; in an assisted process, the com-puter simply propagates that judgment across a document universe in a faster, more cost-effective and more consistent way.
The Engine
The engine under the hood of a strong computer-assisted review workflow relies on categorization technology. In short, this engine is programmed for two tasks: first, to understand the logic it’s given by its operators; and second, to propagate that logic against a larger population.
In the context of review, that means the engine is taught to recognize the original coding decisions of an expert, and then amplify that expert’s efforts across the doc-ument universe. The lessons it takes from
The New Axiom of
Computer-assisted Review
O
ffering legal teams a forward-thinkingsolution to the problem of big data, the topic of computer-assisted review is the conver-sation du jour in the e-discovery marketplace. There’s good reason for that. According to a recent Rand Corporation survey, document review is the single most expensive step in the discovery process. Logically, the option to reduce time wasted on irrelevant docu-ments can make a big difference in any case, particularly on costs. Therefore, when it comes to document review, legal teams see huge value in the ability to quickly separate the wheat from the chaff via battle-tested computer-assisted review software.
When the computer-assisted review con-versation first started, however, there was skepticism and those in the industry ques-tioned the efficacy of the approach. But times are already changing: four major court cases involved decisions based on the use of com-puter-assisted review. In Da Silva Moore, Judge Peck ordered the use of computer-assisted review despite the plaintiffs’ objec-tion. More recently, a Delaware Chancery Court judge ordered its use despite the fact that neither party had mentioned the work-flow. Granted, there’s still some skepticism to be overcome—and some education on the topic to be shared—but, as Judge Peck put it, we should no longer “fear the black box.”
Those examples tell us that the conversa-tion has shifted, and we’ve seen addiconversa-tional support through real-world stories from review teams we work with. In these cases, teams have proven that they understand how the computer-assisted review process is more than technology, but that it’s driven by a tal-ented group of people working hand-in-hand with an effective methodology. As a result, these teams have been able to leverage the technology to great effect. Additionally, the number of active cases running analytics in our software has increased by more than 150% in the last year—further demonstrating its acceptance.
As adoption grows, the industry is learn-ing how a combination of factors makes a computer-assisted review successful. Experts,
engine and validation is the axiom that
defines computer-assisted review. These three items are the core components of an effective computer-assisted review process. They are in no particular order; all three affect the end results, and each is critically important.
Jay Leib is kCura’s chief strategy officer and resident computer-assisted review expert, providing clients with insight and guidance on computer-assisted review workflows and text analytics. He has been a speaker on computer-assisted review, and has authored several articles and white papers on the process. Before joining kCura, Leib was a senior manager with Ernst & Young’s Fraud Investigation & Dispute Services practice. Prior to Ernst & Young, he founded Advocate Solutions, Inc., where he architected the world’s first shrink-wrapped e-discovery application, Discovery Cracker. His software applications have been recognized by numerous awards in the litigation support and e-discovery fields.
Jay Leib
that expert’s instruction are the basis of its work behind the scenes, because the algo-rithm relies on that logic to make its deci-sions on all other documents.
While users are now gaining a better understanding of the human element in computer-assisted review, the machine-learning algorithms themselves are backed by years of research and use, and similar technology is widely used in other indus-tries—ranging from product suggestions in online marketplaces to law enforcement officials honing in on criminal records dur-ing a search—on a daily basis.
We’re seeing increased acceptance in the legal sphere, too. The amount of data, in giga-bytes, we’ve seen running through our text analytics engine has nearly tripled in the last year. That means more review teams are put-ting more data through the engine, trusput-ting the technology to help cut review costs and time. In a recent white paper, Content Analyst— developer of the analytics technology that drives our computer-assisted review work-flow—performed a study on latent semantic indexing (LSI) technology. The paper high-lights differentiators of LSI compared to other categorization engines and evaluates the efficacy of the technology. Citing several real-world applications of the technology, as well as academic studies, the authors find that LSI is proven to be effective and accurate in a number of use cases.
The Validation
Statistical sampling on a population of items is used in a variety of fields, ranging from use as a defect control in factories to a means of evaluating transactions in general ledger systems. This process, called valida-tion, is used to gauge whether a given process is yielding its expected results.
So what about the validation in a comput-er-assisted review? When you’re told that this
1,000-document sample is a good representa-tive of your entire document universe, what does that mean? And is it true?
From any angle, a document count that reaches from the thousands to millions is intimidating. It’s hard to comprehend how many words, concepts, and nuances exist in such a vast scope of data. In a manual workflow, a large team of reviewers is required to work through a massive set of documents one by one. Each individual, subject to his or her own interpretation of the case and its key issues, makes his or her own decision on each document they study. We already know that such subjec-tivity can mean inconsistency throughout a project. Sometimes those inconsisten-cies breed bigger problems. Other times they go unnoticed.
In a computer-assisted workflow, a much smaller team of specialized reviewers will manually review a smaller number of docu-ments. These select few folks are domain experts in the case, and they confer openly and often about the goals of their review and the weight of the issues at hand. If they are inconsistent in training the system, the dis-crepancies will appear very clearly in overturn reports, which can be interpreted to identify disagreements between the computer’s cate-gorization of a document and human review-ers’ decisions.
When it comes to validation, computer-assisted review gives the review team an added benefit: a built-in quality control system.
In a computer-assisted workflow, there are two types of review rounds: the training round, where the experts manually review a subset of documents and select appropriate content on which the system can be trained, and the validation round, where experts are given a randomly selected group of docu-ments to evaluate the computer’s decisions. In the first round, reviewers tell the system
how to categorize; in the second, they tell the system if it has come to the right con-clusions. Following the validation round, case teams can check something we call an overturn report to see how often the reviewers and the computer have dis-agreed. As the project continues, the train-ing and validation rounds occur in pairs until the team is satisfied with the statisti-cal results they’re seeing across the board.
We’ve seen that, often, consistently high overturn rates result from inconsis-tences in the human decisions on which the computer is trained. In one case, for exam-ple, a discouraging overturn rate prompted a case manager to keep her firm’s partners confined to the same conference room over several weekends. There, the attorneys dis-cussed the facts, goals and relevant issues in the case in extreme detail. Emerging from those conversations, they went on to give a computer-assisted review another try. The result was a much lower overturn rate, more consistent results and a success-ful review.
So the benefit of a built-in quality control process is clear, but what about the accuracy? Recently, Dr. David Grossman, associate director of the Georgetown Information Retrieval Laboratory and adjunct professor at Chicago’s IIT, performed a study on the accu-racy of the statistical validation process in our computer-assisted review. He found that the process is mathematically sound.
In his study, Dr. Grossman evaluated a fully reviewed population’s occurrence of responsive and non-responsive documents compared to a statistically sampled set with-in the population. The graphic illustrates the precision of the sampling methodology. In five repeated rounds of statistical sampling, the difference between the samples and the overall population varied an average of just 0.45%—meaning the sample very accurate-ly represented what was in the overall docu-ment universe.
Statistical sampling, therefore, is an accurate and widely accepted method of validating large swaths of data. When a computer-assisted review is deliberately implemented and validated correctly, you can be confident in the end results you’re seeing in your reports and productions.
With growing data volumes and increasingly tech-savvy attorneys and clients, computer-assisted review has a strong future in the e-discovery world. It’s key for professionals to understand the technology and execute the workflow in a way that ensures validation. Close, com-prehensive attention to the experts, engine, and validation of every case helps instill confidence in the results of a computer-assisted review—and makes the problem of big data a little easier to handle. ❚
Illustrating the precision of the sampling methodology, in five repeated rounds of statistical sampling, the difference between the samples and the overall population varied an average of just 0.45%—meaning the sample very accurately represented what was in the overall document universe.
have a search warrant or the owner gives consent. What can get lost in this sort of back and forth is that law enforcement has been using forensic mobile device software to extract discoverable information for years and with great success. However the asso-ciation with criminal investigations has given the software an aura of being compli-cated or difficult to use and of little use in civil litigation. The reality is that mobile device e-discovery is coming to the civil law world whether it's ready or not.
As of February 2012, 88% of American adults have a cell phone, 46% have a smart-phone, 57% have a laptop, 19% have an ebook reader and 19% own a tablet, according to Mob-ify (mobMob-ify.com). Mobile devices are growing increasingly sophisticated, and the market shows no sign of slowing down. The worldwide smartphone market grew 54.7% year over year in the fourth quarter of 2011, according to Inter-national Data Corporation (IDC).
With these devices, users are generating more and different types of data, which are all potentially responsive in both civil and criminal proceedings, including: call logs, email, texts, GPS data, photos, video files, voicemail, Web browsing history, address book, search history, calendar and so forth.
Once, organizations involved in civil liti-gation could argue that it was too difficult to collect this type of information during dis-covery, and therefore, they did not have to worry about acquisition, review, processing and production. Today, though, litigants should not expect to be able to claim this much longer. There is simply too much potentially relevant information being generated and stored on mobile devices. Those in the law enforcement area have been successfully extracting and capturing mobile device data for several years, making it difficult for those involved with civil litigation to claim that it’s impossible for them to do the same.
In-house counsel need to understand how the mobile device landscape is chang-ing e-discovery, and what they will have to do in order to comply with changing expec-tations of the court in the future in order to avoid sanctions.
Mobile Device Discovery
within Corporations
Traditionally, corporations have been able to argue that discovery of this type of ESI is “unduly burdensome” for their own matters. However, since the technology has become so prevalent, corporate legal depart-ments should not expect to be able to use this argument much longer.
While in-house attorneys are not usually concerned about the Fourth Amendment implications inherent in criminal mobile device investigations, they face unique com-plications when it comes to mobile device extraction for civil litigation, HR matters and regulatory issues.
Increasingly at many companies, the mobile device policy is basically “BYOD,” or bring your own device. Employees may use their personal devices for work-related emails or to transfer files back and forth
The Future of Mobile
E-Discovery
I
n the business world, the use of mobile devices such as smartphones, cell phones and tablet devices is proliferating. This pres-ents enormous challenges for attorneys who oversee electronic discovery (e-discovery) for organizations.Mobile Discovery and
Criminal Litigation
In criminal law, there is a long tradition of mobile device forensics. In many instances, though, the technology has been overshadowed by potential Fourth Amend-ment violations and privacy concerns. For example, the Michigan State Police utilize mobile forensic devices that are capable of extracting information from smartphones in a matter of minutes. For several years now, the ACLU of Michigan has been filing free-dom of information requests regarding the use and access of these portable devices. In a series of dueling press releases in 2011, the ACLU accused the state police of using the technology to “quickly download data from cell phones without the owner of the cell phone knowing.” In its own press release, the Michigan State Police insisted that it only uses the devices when officers
Tim Leehealey is the CEO of AccessData, which has pioneered digital investigations and litigation support for more than twenty years and is the maker of the industry-standard computer forensics technology, FTK, as well as the leading legal review technology, Summation. Tim’s philosophy via AccessData is to make it possible for an organization to address all its digital investigations needs with one company. Prior to joining AccessData, Tim was VP of corporate development at Guidance Software and before entering the software development field, he was an investment banking analyst covering the security market at Wedbush Morgan. Tim regularly blogs his unique take on the e-discovery industry at www.ediscoveryinsight.com.
Tim Leehealey
By Tim Leehealey,
CEO, AccessDatabetween work and home computers. Even when employees strictly use work-related devices for work-related purposes, mobile devices allow them to take data out of the office and off the network much more eas-ily. However, companies have several options when it comes to controlling and containing the use of electronically stored information on mobile devices, all of which have real or perceived drawbacks. Issue company-owned mobile devices.
Employers should make every effort to encourage their employees to keep their work-related files and communications off their personal devices, which will make dis-covery far more manageable. One way to do this? Pay for the latest technologies. This is an expensive option, but it will help to ensure that employees aren’t tempted to send a quick text to a colleague on their personal iPhone, which could then become part of the e-discovery process. It will also help IT and legal to control the number of apps that employees download, which can create even more challenges when retrieving potentially responsive ESI from mobile devices.
However, in many organizations, this may not be financially or procedurally
feasible. Some employees may feel stifled or choose to use their own devices anyway without telling managers or supervisors. Create backup policies.
Companies can also develop strict poli-cies that require employees to synchronize and backup their mobile devices on the orga-nization’s networks. Unfortunately, this can create ever-larger stores of data that could ultimately become discoverable. There may be changes to the metadata when location or time-specific files are downloaded from mobile devices, which could eventually cause chain-of-custody issues.
Most servers and some current discovery software are also not designed to capture texts, photos and other common files gener-ated by mobile devices.
Embrace new mobile device forensic technologies.
Adding mobile device forensics may also seem expensive, and many attorneys in cor-porate legal departments and law firms have voiced concerns that e-discovery vendors do not offer products and services that cover this area. Once they capture the data, the legal team must be able to review it. Even if
the technology exists, legal teams must con-sider the costs and the amount of training involved in mastering it.
Increasingly sophisticated tablets and smartphones also have security features that could cause attorneys to be leery of new soft-ware. So they worry that this vast source of ESI is being overlooked, putting them at risk of sanctions.
Fortunately, cost-effective, defensible, user-friendly solutions are now available that can capture ESI directly from mobile devices.
The question is not if corporate legal departments will need to collect ESI from mobile devices, but when. Many depart-ments are already faced with this require-ment and pay by the GB or by the hour for service. Fortunately, this type of collection is no longer limited to the realm of forensic investigators or law enforcement. ❚
AccessData provides a broad spectrum of stand-alone and enterprise-class solutions that enable digital investigations of any kind, including computer forensics, incident response, e-discovery, legal review, IP theft compliance auditing and information assurance. More than 130,000 users in law enforcement, government agencies, corpora-tions, consultancies and law firms around the world rely on AccessData software solutions.For additional information, access www.accessdata.com.
With AccessData’s MPE+ technol-ogy, in-house counsel now have an easy and affordable way to make mobile device discovery a part of the routine e-discovery process.
Designed specifically to allow users to collect and view mobile device data, MPE+ supports more than 6,800 mobile phones and smart devices, including iPhones, iPads, iPods, Android and BlackBerry devices.
MPE+ is a standalone mobile forensics software solution that
provides legal teams with the broad capabilities of competing solutions at a fraction of the total cost of owner-ship. MPE+ can be purchased as a software-only solution, but it is also available preconfigured on a touch-screen field tablet.
MPE+ is easy to use, with a graphical interface and data review organization that mimics the phone’s own look and organization of data. Once data is collected, it can be reviewed within MPE+ or exported to the full range of AccessData’s products, including AccessData eDiscovery, ECA or Summation Express & Pro, through an AD1 file. The use of the forensically sound AD1 container file ensures that the chain of custody is maintained throughout. This allows members of the legal team to either view the data independently or combined with other case data to allow for a more complete picture. It also smoothly integrates with AccessData’s Forensic Toolkit (FTK) if collective analysis of more data sources is required
including multiple cellphones, lap-tops, iPads or other other types of digital evidence.
MPE+ is also affordable and works quickly, allowing legal teams to acquire mobile device data in a mat-ter of minutes.
MPE+ Highlights
◆Executes a full forensic level capture instead of just active data capture, meaning MPE+ can collect deleted items and all appropriate metadata as well;
◆Data can be reviewed on a tablet, within the MPE+ software, or on a number of AccessData review solu-tions such as Summation and AD eDiscovery; and
◆Generates advanced reports detail-ing all phone data—includdetail-ing call history, contacts, messages, photos, voice recordings, video files, calen-dar, tasks, notes and more. The sys-tem will correlate data with contacts in the phone so that users can sort files by custodian.
MPE+ displays all text, email and call history
But the underlying technology—the analytics engine that does the heavy lifting—is the key element governing the speed, accuracy and effectiveness of today’s e-discovery solutions. A proven integrated analytics engine that pro-vides a wide spectrum of analysis options also provides a solid foundation on which to build a consistent suite. Its components have been developed to work together, and can cleanly hand off data from one step in the workflow to the next without having to re-factor it.
In addition, an integrated advanced ana-lytics engine also simplifies maintenance, upgrades, improvements and support require-ments. Consistent analytics technology in combination with an intuitive e-discovery application makes both training and knowl-edge simultaneously more focused and more broadly useful. This contributes to lower cost and higher productivity.
Analytics Engines Make
All The Difference
The goal in discovery is to find all of the relevant information without the process cost-ing two arms and three legs. Comprehensive, defensible computer-assisted review is a key part of achieving this since it substantially reduces, and more effectively focuses, costly human-review time.
Today’s combination of robust integrated analysis options combined with improvements in power and performance enable companies to cost-effectively derive a higher-quality, concise review set from continuously growing document collections. Different, integrated cuts at the source information produce the best results, particularly in early case analysis when you’re figuring out whether the action has any merit.
As advanced analytics technologies con-tinue to scale in speed and volume, consider one example of how a company can change its operational approach to respond better to an action: eliminating the up-front culling of information in order to reduce the initial vol-ume of docvol-uments for analysis.
The value of culling information prior to running advanced analytics is rapidly dimin-ishing. It makes more sense now in terms of
both quality and cost to evaluate the larger universe of documents. Although analyzing 10 million documents instead of a million adds time, if you do it right, you might find useful information that you never expected or wouldn’t have found otherwise.
With greater insight upfront and clearer focus on responsive information, you can make more informed decisions much sooner— for instance, about whether to settle before going to court, or to push your case harder sup-ported by more facts.
Zeroing-in Without Breaking the Bank
Companies deploying an integrated e-dis-covery suite powered by a comprehensive advanced analytics engine have multiple, complementary options for analysis. These capabilities go far beyond the familiar keyword searches and text-comparison.
Conceptual evaluation, for example, uses
concepts reflected in example documents to find those with similar content that traditional keyword search would likely miss because the words aren’t exactly the same. Clustering groups documents that appear conceptually related—very useful when you’re not sure what’s in the corpus. Categorization puts doc-uments into different folders by comparing them to example documents, and powers technology assisted review. The difference? Clustering = “Show me what’s there;” Categorization = “Find me things like this.”
Automated analysis, such as email
thread-ing, can also reduce a number of related
emails down to a concise review set that includes all the relevant information. Consider a 10-email thread in which the 6thand 7th
con-tain all the relevant information from 1 though 5; and 8, 9 and 10 simply add “Got it,” “Thanks,” and “See you!” Analysis will indi-cate that reviewing 6 and 7 will show every-thing of relevance, eliminating the need for a person to review eight others.
Near-duplicate analysis based on
con-cepts, and not simply text comparison, further reduces the collection that represents the entire body of case-related information. For exam-ple, it will recognize two documents as con-ceptually nearly identical even though a few paragraphs have been rearranged. More literal text-comparison analysis will see them as dif-ferent documents to be reviewed by a human. The net result of analyses like these is to produce the smallest possible collection of likely relevant documents for human review. E-discovery suites powered by an intelligently integrated advanced analytics engine will give you a range of options to perform comprehensive, effective and cost-efficient discovery. ❚
Content Analyst’s software provides advanced, conceptual-based search, classification and document analysis for a wide range of customers. For further information on the capabilities and value of advanced analytics, please visit ContentAnalyst.com or [email protected].
Integrated E-Discovery Suites
Why the Smart Money
Checks the Analytics Engine
I
n both senses of the word, fortune favors theprepared when it comes to litigation: fortune as treasure and fortune as positive outcome.
Three elements characterize superior preparation for e-discovery: good docu-ment housekeeping; precise extraction and distillation capabilities; and unified work-flow from the left through to the right of the EDRM model. This article talks about the latter two, but it’s useful to quickly touch on housekeeping.
Good housekeeping means saving, and properly categorizing, only what makes sense from the practical, regulatory and legal points of view. The cleaner the corpus of documents, the better you are able to respond as discov-ery progresses through early case assessment, review, production and litigation.
E-discovery capabilities and the quality of coordination as the process moves from left to right are the most impactful in terms of comprehensive discovery and cost effi-ciency. (While poor document housekeep-ing can complicate matters, it’s comparative-ly easy, though expensive, to correct.)
The State of the Art Has Shifted
The combination of structural advances in computer-assisted review and growing realization of the value it delivers has dramatically changed how organizations approach e-discovery and adapt their proce-dures to take advantage of evolving analyti-cal capabilities. For example, Gartner pre-dicts in its May 2012 Magic Quadrant for
E-Discovery Softwarereport that e-discovery techniques “will become ever more widely accepted, and within five years they will be part of standard operating procedure.”
Moving beyond the model of stringing together discrete best-of-breed point solu-tions, companies now see the workflow from left to right as a continuum. Integrated e-dis-covery suites designed to work together pro-vide a consistent user experience throughout the processing and analysis phases—early case analysis, email threading, text near-dup, clustering, concept search, categorization, etc. A consistent user experience is important to improving the efficiency of people’s work.
browser without the need to install any addi-tional software or ActiveX controls on the client machine. A typical legal case may involve several different types of documents to be reviewed during the examination process, which would require the use of multiple viewers for different file formats. One cost-effective strategy for corporations with an enterprise content management system
is to select a multi-tasking viewer that can be used as a daily document access tool for staff. The same viewer can then be used as a native viewer during e-discovery efforts. A thin-client viewer allows remote, mobile access by anyone participating in the project, such as remote legal aids.
3
Annotations, mark-ups and.
redactions.Annotations are crucial to the e-discovery process. A typical viewer should enable anno-tations such as highlighting, color coding and text notes to be created and displayed with doc-uments stored not only in TIFF, JPEG, or PDF formats, but in native formats as well, such as MS Office or email files. An original version of the document is preserved, while annotated versions can be updated and shared throughout the e-discovery process. A redaction module allows redactions to be “burned in” to docu-ments, effectively removing the underlying confidential text and producing an otherwise indexed and searchable PDF document. An intuitive visual interface allows a user to select text or define a region of a document to be permanently redacted from the document. A
strong annotation system can be used in an automated manner to redact regions of content based on location, search results or other rules. Redacted documents can then be published to PDF, TIFF or other image formats and shared with other users. Knowing that sensitive or confidential information has been permanently stripped away from your documents, you can feel safer in sharing your content with legal services or opposing legal teams. Underlying text is not only hidden, but completely removed so that it’s not returned in search results, and can’t be highlighted or copied. Integrating redaction into your workflow in combination with digital rights management reduces the risk of oversight or error, while locking redacted documents to read-only status for users.
4
.
Digital rights management.Digital rights management enables docu-ment permissions to be assigned at the user level. Integrating this procedure within the viewing engine simplifies the process of allow-ing and disallowallow-ing printallow-ing, savallow-ing, annota-tion and redacannota-tion based on each user’s needs, without modifying the original legal version of the document. By adding a digital rights man-agement control on the document, you can ren-der the document as read-only and control printing, navigation, pan control and saving within a work group, across departments, or with partners and suppliers outside the firewall. The review process depends on the review workflow and protocol set up by counsel. However, the use of these emerg-ing technologies can aid the modern elec-tronic litigation process, save money and help enable online analytics, processing and accelerate collaboration on the data. ❚
Prateek Kathpal is the founder of Adeptol, a software company focused on developing imaging applications, which was acquired by Accusoft in 2011. He is currently responsible for the viewing products strategy at Accusoft. Kathpal founded Adeptol to create an enterprise wide view-ing platform and associated solutions, to replace traditional thick-client products. Prior to founding Adeptol, Kathpal held senior positions within the content management division of EMC. He has also worked with EMC Documentum, NEC, Sapient, Cognizant, JPMorgan Chase and other organizations. Prateek is an Engineering graduate with an MBA in Marketing.
Accusoft provides a full spectrum of document, content and imaging solutions. With its broad range of solutions, Accusoft is committed to deliver best-in-class, enterprise grade and fully supported applications and a globally recognized suite of software development kits (SDKs). Accusoft products work reliably behind the scenes for capturing, processing, storing and viewing images, doc-uments and more. Add barcode, compression, DICOM, image processing, OCR/ICR, forms processing, PDF, scanning, video, and image viewing to your applications. Products are delivered as applications and toolkits for multiple 32-bit/64-bit platforms and development envi-ronments, including iOS, Android, .NET, Silverlight, ASP.NET, ActiveX, Java, Linux, Solaris, Mac OSX, and IBM AIX. For more information, visit www.accusoft.com.
Collaboration in
E-Discovery
A
nyone who has been involved in the e-discovery process for a case understands that it can be complicated, time-consuming and require the involvement of several peo-ple from cross-functional teams. Any lack of collaboration between the different teams can lead to severe consequences, such as additional time and cost, duplication of efforts and potentially not communicating critical observations.Even just a few years ago, most documents existed in the form of paper and the discovery process would involve going through that paper, along with the supplement request to review the available electronic data. As the world has evolved, more and more documents are stored electronically and discovery now typically starts by looking at the electronically stored information.
Collaboration plays an important role in the e-discovery process. Once the source of information has been identified, the next steps involve collecting the findings and making them presentable, easy to understand, and specific to the task. This requires constant review, processing and analysis and is also the most expensive stage of the e-discovery work-flow. Depending on the source of information, the cost of the review process can be up to 80% of the total cost of e-discovery.
There are several emerging technologies that can help limit these costs and streamline the review stage:
1
.
Full-text extensive search.In a full-text search, the search engine examines all of the words in every stored doc-ument as it tries to match search criteria or words supplied by a user. Full-text guided navigational search allows users to actively browse/filter the search collection by metadata and categories that have been extracted from the index. Keyword hits can then be passed to a document viewer client, enabling the team to quickly identify the context of the match, further increasing the efficiency of the file inclusion and exclusion process.
2
Document viewing with remote.
accessibility.A unified document viewer can simplify the e-discovery review process, allowing users to view documents directly in the
By Prateek Kathpal,
Vice President of Viewing Product Strategy, Accusoft“Depending on the
source of information,
the cost of the review
process can be up to
80% of the total cost
◆Excluded business impact due to downtime because it varies too greatly among companies.
Server downtime is a real risk. If down-time costs are included, then the cost-effec-tiveness of an on-demand, cloud-based service is even more dramatic.
Up-front costs: One advantage of the cloud is the absence of start-up costs. Because the cloud provider hosts and maintains the application, no up-front investment is required for hardware and installation.
Up-front system installation expenses for an appliance platform total $372,000 for the cost of new servers, storage and a backup library.
For our analysis, servers and storage were configured to meet the specification requirements of the selected processing and hosting platforms. Servers were con-figured to fulfill Web application, process-ing, search, analytics and database roles.
Other one-time fees: Typical fees for a cloud-based system include site set-up, processing and production fees. We estimated these to total $682,700 for each year in the three-year scenario for a cloud platform.
For the cloud platform, the site setup fee includes site consultation, instructor-led Web training and setting up standard fields, review forms, dynamic folders and user accounts. The processing fee includes ingestion—the extraction of metadata, text and native files— and culling—filtering the data via de-NISTing, deduplication, filetype filtering and date filtering.
There would be no processing fees for the in-house platform because the equip-ment costs and software licensing are accounted for in other expense categories.
Recurring fees: Although both cloud and in-house applications involve recurring fees, the fees differ widely in nature.
The in-house appliance would incur annual recurring fees relating to hardware maintenance and software subscriptions associated with the processing and hosting platforms. These are estimated to total $388,600 in year one, $587,400 in year two and $789,400 in year three.
For the cloud-based application, there are no maintenance or licensing fees. There would be a recurring monthly hosting fee, charged by the GB. Assuming a cull rate of 67%, then the data being hosted is 1,100 GB the first year, 2,200 GB the second year and 3,300 the third year. Corresponding costs for the cloud appli-cation are $330,000 in year one, $660,000 in year two and $990,000 in year three.
Ongoing operating expenses: Just as the cloud platform required no up-front costs, it also requires no ongoing operational expens-es. The same cannot be said for the in-house platform, which is projected to incur $1,112,540 in year one, $1,353,540 in year two and $1,715,040 in year three in opera-tional and staffing expenses. The ongoing operational expenses required to support the in-house platform include:
◆Data center colocation to house hardware equipment and provide redundancies in power, cooling and 24x7x365 manned security versus an on-premise server room; ◆Point-to-point connectivity between the data center colocation and office. Due to very high traffic volumes for ESI, we fac-tored in a dedicated GigE link offering speeds up to 1,000 mbps;
◆Cost for staff office space. We estimated 2,000 square feet at $30 per square foot annually to accommodate a staff of seven; ◆IT staff includes one network administrator,
one help-desk analyst and one database administrator to manage and maintain the infrastructure. We also included one programmer to assist with customization projects; and
◆E-discovery staff includes one e-discovery manager and three e-discovery analysts to support the in-house appliance. We budgeted for three project managers in the first year, five in the second year and eight in the third year.
To set the salaries for e-discovery staff, we used the average salaries identified by The Cowen Group in its 2011 salary survey of law firm litigation support staff. For IT salaries, we used data from CBSalary.com. When the costs over the three years are added up, the total for the cloud platform is $4 million versus $6.3 million for the in-house platform. That represents a savings of 36% with the cloud platform.
A 36% cost savings using the cloud over an in-house appliance is clearly dramatic. A further advantage of the cloud, not shown by these numbers, is that it provides flexibility to quickly ramp-up when activity increases and terminate costs when the project is finished.
With an in-house platform, operating expenses continue, regardless of the level of activity, and there is constant worry about the investment becoming a useless expense. ❚
For additional information, visit www.catalystsecure.com.
Cloud vs. Appliance
Comparing Total
E-Discovery Cost
A
n ongoing debate among e-discoverypro-fessionals is over which is the better platform for hosting document search and review: the cloud or a local appliance. Among those who favor an appliance, a common argument is that bringing e-discovery in-house will reduce costs. But will it?
One way to find out is to analyze the total cost of ownership (TCO) of cloud-based and appliance-based e-discovery platforms. Only by laying out all of the expenses required to support an application—including infra-structure, technology, staff and ongoing operational expenses—can one accurately evaluate its cost.
We constructed a hypothetical, but typical, e-discovery client—a large law firm with a mix of large and small cases—and analyzed the total costs over a three-year span, using either a cloud or an in-house e-discovery platform. The outcome was dra-matic: Using our most conservative figures, the cloud produced cost savings of 36%— $2.3 million—over in-house.
Methodology
We assumed that the law firm is managing 200 small cases of 25 GB each and 25 large cases of 200 GB each. That is a total of 10 TB of data, but since it is rare for all the data in a case to arrive at once, we spread that over the three-year span, or 3,333 GB per year.
We also assumed that the total data would be culled at a rate of 67%—the average rate reported by a recent industry survey—bring-ing the annual quantity of data to 1,100 GB after culling. We further assumed a maximum of 500 users on the system.
To establish the expenses to build the TCO model, we did the following: ◆Selected popular in-house and cloud-based
processing and hosting platforms that are widely available on the market today; ◆Obtained actual quotations from hardware
and software suppliers;
◆Calculated annual hardware and software maintenance fees at 20% of the up-front capital expenditures;
◆Accounted for technology refresh by giving hardware a three-year useful life; ◆Excluded full redundancy for the in-house
platform; and
2013 WHITE PAPER CALENDAR
BEST PRACTICES IN
...
January 2013 Reservations: 10/12 Materials: 11/2 Mail Date: 12/20 February 2013 Reservations: 11/9 Materials: 11/30 Mail Date: 1/22• RM• Retention Practices• Email• Compliance•
❯Enterprise Search/Information Access
❯Records Management ❯Email Management ❯Information Governance ❯Legal Hold
❯Document Life Cycle Management ❯Storage/Archive
Bonus Distribution: LegalTech New York
E-Discovery
March 2013
Reservations: 12/14 Materials: 1/4 Mail Date: 2/22
ECM: Cloud, Mobile, On-Premise
April 2013
Reservations: 1/11 Materials: 2/1 Mail Date: 3/21
• Classification• Taxonomies• Categorization•
❯Unstructured Content Management
❯Text Mining/Analytics/Semantics ❯Content Management Systems ❯Autocategorization
❯XML/Authoring
❯Internal/External Search Strategies ❯Unstructured/Structured Content Integration
Bonus Distribution: Enterprise Search Summit; Gartner Customer 360 Summit; FOSE; MER
Intelligent Search in the Age of Big Data
• ECM• EDMS• DRM/KM• BYOD •❯Web Content Management
❯Document/Image/Forms Management ❯Digital Asset Management
❯Cloud and Mobile Applications ❯Regulatory Compliance ❯Case Management ❯Records Management
Bonus Distribution: AIIM; Gartner BI Summit
Enhancing SharePoint
July 2013
Reservations: 4/12 Materials: 5/3 Mail Date: 7/3
Knowledge Management for Customer Support
August 2013
Reservations: 4/19 Materials: 5/10 Mail Date: 7/3
• EDMS• CRM• ECM•
❯Web Content Management
❯Collaboration
❯Business Process Management ❯Information Governance
❯Blogs, Wikis, Forums ❯Enterprise Search ❯Storage
Bonus Distribution: CRM Evolution
Content Management with SharePoint
October 2013 Reservations: 7/12 Materials: 8/2 Mail Date: 9/20
Knowledge Management
November 2013 Reservations: 8/9 Materials: 8/30 Mail Date: 10/22Cloud Strategies and Solutions
December 2013
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• CRM •WCM •Social •Partner Collaboration •
❯Authoring ❯Site Design ❯Mobile Access ❯Web Analytics ❯Social Business ❯Knowledge-Centered Support ❯Cloud/Hosted/On-premise/Hybrid
❯Digital Asset Management
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Customer Experience in a Multi-Channel World
BPM and Case Management
May 2013
Reservations: 2/8 Materials: 3/1 Mail Date: 4/22
• RM •Storage •Social Nets •ECM•
❯Cloud Storage ❯Search ❯Office 365 Migration ❯Records Management ❯Collaboration ❯Portals ❯Security
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• Enterprise 2.0• Web 2.0• Collaboration•
❯Customer and Partner Relationship Management ❯Mobile and Cloud Applications
❯Sentiment/Customer Intelligence ❯Customer Experience
❯SharePoint ❯Expertise Location
❯Human Resource Management
Bonus Distribution: Enterprise 2.0
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September 2013
Reservations: 6/14 Materials: 7/5 Mail Date: 8/21
• Email Management •E-Records• Risk Management•
❯E-Discovery
❯Information Governance ❯Document Lifecycle Management ❯Retention Management/Archive ❯Legal Hold
❯Security
❯Business Continuity
Bonus Distribution: ARMA
Information Governance and RIM
• SaaS • IaaS • Storage • APIs•
❯Web Services ❯Multi-tenant ❯Security ❯Information Governance ❯Infrastructure/Platforms ❯Open Source ❯WebOS ❯Mobile
Bonus Distribution: Dreamforce
• BPM• Workflow• CM/DM •
❯Business Process Management ❯Content Management and Integration ❯Adaptive Case Management ❯Collaboration
❯Cloud-Provided Services ❯Contracting
❯Business Process Outsourcing
Bonus Distribution: Gartner BPM Summit
• KCS v5•KPIs • Analytics•
❯Knowledgebases ❯Contact Center
❯Customer Relationship Management ❯Help Desk
❯Service Management ❯Knowledge Management ❯Incident Management
❯Web Experience Management
Bonus Distribution: CRM Evolution
• EDMS• ECM• BI/CI• E-Learning •
❯Content Management ❯Document Management ❯Enterprise Search ❯Classification/Taxonomy ❯Collaboration ❯Expertise Location ❯Project Management/Modeling ❯Business Performance Analysis
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Kathryn Rogals Paul Rosenlund Andy Moore
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For more information on the companies who contributed to
this white paper, visit their websites or contact them directly:
AccessData
588 West 400 South, Suite 350 Lindon UT 84042 PH: 801.377.5410 FAX: 801.765.4370 Contact: [email protected] Web: accessdata.com Accusoft 4001 N. Riverside Drive Tampa FL 33603 PH: 800.875.7009 or 813.875.7575 FAX: 813.875.7705 Contact: [email protected] Web: www.accusoft.com
Catalyst Repository Systems
1860 Blake Street, 7th Floor Denver CO 80202
PH: 303.824.0900 or 877.557.4273 FAX: 303.293.9073
Web: www.catalystsecure.com
Content Analyst Company, LLC
11720 Sunrise Valley Drive, Suite 400 Reston VA 20191 PH: 888.349.9442 or 703.391.8700 FAX: 703.391.1644 Contact: [email protected] Web: www.contentanalyst.com kCura
231 South LaSalle Street, 8th Floor Chicago IL 60604
PH: 312.263.1177 FAX: 312.263.4351
Contact: [email protected] Web: www.kcura.com
