e-discovery 2.0

We’ve devoted a number of posts to the topic of ECA, ranging from a quest to define the acronym, all the way to the cost savings benefits of the ECA approach.  And, while there seems to be relative unanimity around the beneficial aspects of ECA, there still seem to be a number of myths and misconceptions.  So, ala the Mythbusters, we’ll run these myths through the gauntlet to see which survive scrutiny.

Myth #1: ECA Is Only Valuable if Performed “Early”

Certainly, ECA is best leveraged and will be most valuable when performed at the outset of litigation.  As has been stated before, it has value on two primary fronts, the first being the ability to scope electronic discovery (both in terms of cost and timelines).  The next is the more traditional value proposition where ECA is used to get an understanding of the case facts to enable the strategic decision making process.

As such, there are scenarios where an ECA methodology would still generate value even if performed “later” in the mater.  For instance, with bifurcated, class action litigation initial discovery about the class may occur months before discovery on the merits.  In this instance using a later ECA approach would still make sense since discovery about the case facts may not have been possible earlier on.  Similarly, “late” ECA may still hold value when new parties or claims are added to an existing lawsuit, or when there’s a substantial change in case direction, data, or custodians.

Myth #2: ECA Is Only Performed With Technology

Sure, enterprise grade ECA products  are an important part of the mix, but the products won’t perform an ECA by themselves.  There’s just too much subjective decision making involved in the assessment process.   Therefore, the right people are critically important — not only in terms of experience performing this analytical work, but also in their ability to capably testify about the underlying decision making process.  It’s also important to be able to follow a repeatable and defensible processes to show that the “recipe” used was aligned with industry best practices and wasn’t ginned up for a particular engagement.

Myth #3: ECA Only Works With Large ESI Volumes

Yes, ECA methodologies makes a lot of sense for large, bet-the-company matters because even modest savings when processing, analyzing and reviewing terabytes will easily approach six to seven figures.  However, smaller matters will still benefit from better budgetary insights that facilitate informed matter management.  And, in a way there’s almost more benefit from being able to quickly evaluate (fight/settle) smaller suits since the transactional costs are so high relative to the amount in controversy.  In both scenarios it’s important to view objective case data to prepare for meet & confer conferences.

Myth #4: Clients Don’t Want To Pay for ECAs

Many end clients (corporate counsel typically) have a similar litigation mindset:  i.e., the desire to avoid costs for as long as possible.  While avoiding early costs makes some sense on its face, the fact is that spending a small amount of money early on (for budgetary and case assessment purposes) will in most instances reduce the overall litigation budget.  It’s the classic, “you can pay me now, or pay me later” situation.

Counsel must understand that while some costs are incurred early in the process the benefits are crystal clear: i.e., determining customized case strategies early in the matter to decide whether to fight or settle.  Similarly, corporate clients must recognize that the benefits outweigh the costs and require their litigation counsel to include this process in every significant matter.

This illustration highlights how an initial ECA investment actually pays for itself over the life of the litigation.

Myth #5: ECAs Begin when the Complaint is Filed

Many newbie ECA practitioners may think that the timing for an ECA approach would start when the complaint is filed.  And, while this isn’t patently ridiculous, I think the better approach is to begin the clock at the time litigation becomes “reasonably likely” — versus later dates such as when the complaint is filed or when discovery is propounded.  This trigger is also the same for trigger preservation obligations and a host of interrelated activities such as ESI “identification,” which makes the matter kick-off more synchronized.

For more information about ECA, watch a recording of our recent webinar — E-Discovery MythBusters: Debunking Common Myths About Early Case Assessment.

It’s not just in New Jersey that corruption is in the news. It feels like everywhere you go, the authorities are investigating white collar crime and thus have an increasing need for electronic discovery technology.

Earlier this month, as those of you who follow my Twitter feed will know, I was visiting customers and partners in Germany. In virtually every meeting, data privacy and corruption investigations were top of mind, and with good reason. Following the Siemens case last year, German investigators have become much more active and it was easy for my hosts to list example after example of recent cases. There was the Deutsche Bahn case of management spying on its own employees, in violation of German privacy laws; the Deutsche Bank case of management spying on its own board; and, the Deutsche Telecom case of management phone tapping employees to find leaks. There were stories of price collusion among cable car companies in the Alps, and corruption investigations into the activities of German companies in Eastern Europe.

A similar focus on anti-corruption exists closer to home. I have written before about the increase in FCPA investigations and that’s been reflected in recent headlines. As the Wall Street Journal reports, Sun and Shell have recently come under the microscope, according to their public filings. And Frederic Bourke, a founder of the accessories firm Dooney & Bourke, was recently found guilty of conspiracy to violate the Foreign Corrupt Practices Act, which may result in jail time.

All indications are that the U.S. Department of Justice and its counterparts overseas are just warming up. It’s not a good time for white collar crime, wherever you are in the world.

There are legions of Arnold Schwarzenegger quotes, including the famous “I’ll be back” from The Terminator.  Well, true to this sentiment, The Governator finally coughed up his hairball and made good on the promises to push through California’s long overdue alignment with the electronic discovery changes made by the FRCP on 12/1/2006.

Citing mysterious budgetary concerns (which still elude me), The Governator initially vetoed Assembly Bill No. 5.  But as of July 1^st, California’s new electronic discovery provisions were finally made law.  Interestingly enough, California (which tends to more progressive than most) was way behind the times in terms of adopting the new framework of the FRCP…

“The California Discovery Act hadn’t really been revised or amended since the mid-1980s,” said Patrick O’Donnell, the supervising attorney for the Judicial Council’s Office of the General Counsel who led efforts to write the state’s e-discovery law. “This is really a major step to address the changes in the world of electronic data since then. … This gives a lot more clarity and certainty in how the issue will be focused on.”

Instead of the alleged budgetary concerns it appeared that California had (and still has) bigger fish to fry and needed some extra cycles to get lawmakers, attorneys, Silicon Valley leaders and court administrators all on the same page.

The new California provisions pretty closely mirror the FRCP language with a few minor exceptions, called out by Joshua M. Briones and Anahit Tagvoryan in their recent article…

• Minor tweaks to the Rule 37 language around the safe harbor provisions broadening slightly (beyond “loss”) the California language to also preclude sanctions where ESI is “lost, damaged, altered, or overwritten.”
• No corresponding meet & confer provisions in the California statute similar to the Rule 16 and 26 sections in the FRCP.
• Inaccessibility provisions of FRCP 26(b)(2)(B) changed slightly to require producing party to file a protective order for ESI it believes is not reasonably accessible due to “undue burden or expense.”

While a long time in the offing, these provisions (despite the minor tweaks) should be a refreshing change for California practitioners who’ve been waiting too long for the other shoe to drop.  Now, case law can start to develop, which will continue the honing-in process…

In my last post, I started a discussion on the myths surrounding concept search.  The first myth I dispelled was the “concept search is concept search” myth.  The myth is that there is an agreed upon definition of concept search.  In actuality, when people in e-discovery use the term concept search, they don’t always mean the same thing.  Frequently they are not actually talking about concept search technology at all and are actually talking about concept or content categorization technology, which is very different.  The second myth that needs dispelling is that concept search is better than keyword search.

The thinking behind this myth goes something like this:

Keyword search has a lot of problems.  It is prone to being over-inclusive, i.e., finding some non-relevant documents, and under-inclusive, i.e., not finding some relevant documents.  Concept search technologies are new and interesting and using these technologies you can find documents that keyword search can’t find.  Therefore, concept search must be better than keyword search.

Let’s examine this thinking.  The first two statements are accurate.  Keyword search is not perfect and can produce over- and under-inclusive results.  And concept search and content categorization technologies can both help identify documents that keyword search technologies might not find.  However, the conclusion that concept search is better than keyword search is not valid and doesn’t follow from these two statements.  Why?

In order to answer this question, we first need to go back to the difference between concept search and content categorization. Because these are different technologies, we really need to separately compare concept search versus keyword search and content categorization versus keyword search.  Let’s start with content categorization and keyword search.

The issue with this comparison is that keyword search and content categorization do different things.  Keyword search can be used in many ways in e-discovery.  The two most common are: (1) analysis or case assessment: finding the hot documents and understanding the matter by determining who knew what, when, how and why, etc., and (2) culling: removing non-responsive documents and/or identifying potentially privileged documents in order to reduce a large, starting set of documents to a smaller set before review.

Content categorization, on the other hand, has historically been used within the review phase of e-discovery.  Categorization can help reviewers to better understand the documents they are reviewing and thus potentially increase the speed of review.  Practitioners with whom I have worked also find that categorization can be useful during analysis by helping to understand a matter and identify potentially important keywords.

However, content categorization has not been used as part of culling.  First, culling needs to be transparent.  You need to be able to get agreement with or at least explain to the opposing side and the court exactly how you have culled the data set.  If you cull based on categories of documents that have been generated by a proprietary, black-box algorithm, it’s going to be difficult to gain agreement on or explain your culling methodology.  This is why the typical method of culling is still to use keyword search and either agree on the set of search terms with the opposing side or to use e-discovery search best practices to perform keyword searches on your own.

Second, content categorization has its own issues when it comes to being over- and under-inclusive.  There is no guarantee that your group of documents that have been categorized as being related to, for example, a company’s hiring policies include all of the documents in your matter related to hiring policies or that they do not include some documents that may not really be related to hiring policies.  Content categorization, like keyword search and virtually every information retrieval technology, is not perfect.

So what about concept search technology?  Surely, concept search technology is better than old, boring keyword search.  Well, actually it’s not that clear-cut.  The problem with concept search technology is that while it might find more relevant documents than plain keyword search, it will also likely find more false positives.  Imagine searching for documents containing “terminate” in an employment matter and your concept search technology automatically searching for “fire”, “dismiss”, etc. as well.  You’ll find more documents related to the termination of employees, but you’ll also find a lot more non-relevant documents concerning house fires, the fire department, etc.

So concept search can help address the under-inclusive problem with keyword search, (though it won’t solve it) and can be helpful during analysis.  But it can often increase the over-inclusive problem.  In addition, today’s concept search technologies share the transparency problem with concept categorization.  These technologies have largely been designed as “black boxes”, which as I have discussed in the past, makes sense for Enterprise search but not for e-discovery search, and, as a result, could also be potentially difficult to explain and defend.   For these reasons, concept search technology isn’t used very much in e-discovery today.  In order for its use to become widespread, it will need to become more transparent.  But that’s a topic for another day.

The bottom line here is that despite all the hype, concept search and content categorization technologies do not solve all the challenges of e-discovery search.  Both of these technologies can be very useful and the technology behind them is always improving.  However, as most of the experienced practitioners I work with already know, these technologies are generally better thought of as supplements to keyword search, not replacements.  The important question is not whether to use one technology over the other but which technology is best suited to your objectives and how best to use all the available technologies to achieve the desired goal.

Assuming that you can buy each company for the same price, which would you acquire?

Company A has been in business 3 years, has 25 customers, no brand to speak of, and did about $5 million in revenue in the prior year; or,

Company B has been in business 7 years, has over 100 customers, a strong brand in its market, and is doing $25 million in annual revenue?

“No brainer,” you say, “obviously, Company B.” So it is that FTI looks to have got a great deal buying Attenex (Company B) today for $88 million, whereas Seagate looks like it grossly overpaid for Metalincs (Company A) which it bought for $82 million in December 2007. But things are not always as they appear, and there are good reasons why litigation support software company Attenex has sold for a paltry 3.5x revenue, a multiple well below the 16x commanded by Metalincs or even the 5x revenue that Iron Mountain paid for Stratify.

Three forces reduced Attenex’s acquisition price. The first is that FTI accounted for a large proportion of Attenex’s revenue. That gave FTI leverage over Attenex since it could say, “sell to us for $88 million, or we will take our business elsewhere, your revenue will plummet, and the value of your business will be greatly reduced.” This power that FTI had over Attenex made it the only logical acquirer, so there could be no pressure from other bidders to raise the purchase price.

The second force depressing Attenex’s valuation is that its revenue will likely decline post acquisition as Attenex’s partners (who compete with FTI) switch from Attenex to other solutions. Software investors value growth above all else – and are willing to pay up for it. For example, Bladelogic, an unprofitable software company, went public last year at a $500 million valuation with less trailing revenue than Attenex. But it did $62 million in revenue the following year (Bladelogic sold to BMC Software for $800 million in April 2008). Attenex, by contrast, will see declining revenue in the next 12 months.

Finally, acquirers worried that, since Attenex’s revenue comes almost entirely from its hosted offering via service providers, its revenue was more volatile than enterprise-oriented e-discovery software companies. This is due to the fact that customers (typically, law firms) purchase Attenex-powered services on a case-by-case basis and can switch away at any time. Enterprises, in contrast, purchase long-term software contracts that will not vary based on short-term changes in case volume.

Once these factors are taken into account, the price and the multiple start to look a lot better. Attenex’s founders, who are some of the pioneers of the e-discovery industry, get some well-earned liquidity; the venture investors make a decent return; and, employees get to join a professionally-run company that compensates its people well. My congratulations to the Attenex team, and to FTI which has negotiated a great deal.

Of course, all this says nothing about the deal’s impact on the broader e-discovery market. That will be the subject of my next post.