e-discovery 2.0

Maybe this will show my age, but I’ve been around the electronic discovery business since the days when pricing was both simple and very expensive. Terabytes were at the mythical high-end of the spectrum and gigabytes of “e-docs” (not “ESI”) cost $3,000 – $4,000 to process. Understandably (and fortunately for most), pricing models have evolved, thanks in part to more educated consumers and initiatives such as Sedona’s RFP + Vendor Panel.

Leaving the WABAC machine and moving into present times, we’ve starting to see some variance from traditional pricing models that primarily focus on data “into” the processing machine. More and more companies (such as Kroll Ontrack) are moving to models that price on data “out” of the process. Since that’s a bit nebulous, an example might illustrate:

Traditionally, in a somewhat simplified fashion, an electronic discovery project would be priced by the amount of data in the initial corpus (say 100 gigabytes) and processing would be priced at $500 a gigabyte (for round numbers purposes). Leaving out the sometimes significant caveat that the 100 gigabytes would likely increase due to expansion of compressed files, this would mean that the bulk of the project expenses would be $50,000 ($500 x 100), plus relatively nominal costs for monthly hosting and user access rights.

At the end of the day, after elimination of system files, deduplication and application of search terms (reducing the initial corpus by say 70% collectively) there would be 30 gigabytes remaining for hosting and possible production, both of which are most often priced separately.

Given rampant commoditization there’s an arms race underway among certain service providers where they’re now changing the above model to give away initial processing as a loss leader – pricing only on the data that comes out the end of the processing/search step. In this approach the above workflow would largely stay the same, but the vendor would charge a higher rate for what ultimately is hosted on the back-end. If this back-end fee was $2,000 per resulting gigabyte and the same 30 gigabytes was seen out the back end, then the customer would pay $60,000 for the project. But, if the deduplication, searching, culling, etc. was more effective (at say 80%) then the resulting 20 gigabytes would only cost $40,000.

The question then, as Clint Eastwood would put it, is: “Do you feel lucky?” This pricing model forces attorneys and litigation support managers to guesstimate what culling, search, and de-duplication rates they’ll likely get on the data corpus. Guess right and they save the end client money, guess wrong and they’re way over budget.

The dynamics of this purchasing decision are a bit atypical because the buyer (usually counsel) doesn’t pay the bills, so the decision can often be more vexing than most. When a direct consumer gambles on pricing things will ideally balance out over time, with money being saved in some instances and some being overspent in others. But, when the buyer doesn’t pay the bills the motivation is less clear.

Thoughts run to Maslow’s hierarchy of needs to determine which pricing model is ultimately more compelling: (a) price certainty/adherence to budget, or (b) cost variability and the opportunity to save money. While it’s never good to understate the upside of saving money (Esteem), I think ultimately there’s a more fundamental need (Safety) to stay within budget and avoid the painful (sometimes client imperiling) call to discuss how a given e-discovery project has gone way over budget.

This calculation is made further vexing because it not only pits the purchasing party against unknown data culling/searching rates, but it also puts the vendor in an ethical bind where they make less money if they’re supremely effective at data reduction, whereas if they’re either intentionally or accidentally beneficiaries of relatively little data reduction then they stand to make a ton of upside.

It’s like you went to Vegas to gamble your kid’s college fund and on top of the already questionable house odds you knew that the dealer stood to profit by your losses. So, as for myself, no, I don’t feel lucky.

I was at the Sedona Conference Working Group’s Mid Year meeting last week where 80 or so electronic discovery practitioners and judges met to discuss hot topics in bucolic Denver, Colorado.  Without getting into the particulars of any discussion, several themes continue to stay on the front burner, including the progress of the cooperation proclamation and the relatively newer issue of proportionality (as highlighted recently by The American College of Trial Lawyers Task Force on Discovery).

Aside from those overarching themes I was struck by how polarizing the discussion was around one recent case in particular.  While many notable commentators have already made this the most talked about cases of the year, Phillip M. Adams & Assoc., LLC v. Dell, Inc., 2009 WL 910801 (D. Utah Mar. 30, 2009) continues to stimulate discussion.   Adams v. Dell is a patent infringement case where the plaintiff, alleged that one of the defendants (ASUS) destroyed critical pieces of evidence and should be sanctioned accordingly.

The underlying facts and timelines are fairly complex, but in summary the dispute centered around the alleged infringement of several patents developed to resolve defects in floppy disks during in the late 80’s.  What makes this decision so vexing is that it starts out as a preservation case, but quickly confuses that concept with data retention and information management practices/policies.

So, starting with the preservation angle…  Both sides fortunately agreed about the definition for the duty to preserve evidence, which in the 10^th circuit begins when a party “knows or should know [it] is relevant to imminent or ongoing litigation.”  The triggering of the preservation duty was not surprisingly much more complicated and ASUS (the responding party) claimed that its duty to preserve wasn’t triggered until early 2005, when they received a letter warning it of potential litigation because of the alleged patent infringement.  But, the Magistrate held that “counsel’s letter is not the inviolable benchmark” and the duty to preserve was triggered much earlier (in the 1999-2000 time frame) because similar litigation was rampant in the industry, highlighted by a late 1999 suit where Toshiba paid billions of dollars in a class action settlement related to similar floppy disk issues.

Leaving the murky preservation issue by the wayside for a bit, the Magistrate then moved into ASUS’ claims that FRCP 37(e) provided a safe harbor for its alleged destruction.

“ASUS claims it can find a safe harbor against sanctions because of the recently adopted rule that sanctions may not be generally imposed for ‘failing to provide electronically stored information lost’ if a party can show the loss was ‘a result of the routine, good-faith operation of an electronic information system.’”

Nice try, but strike two for ASUS…

“ASUS provided an extensive declaration from an experienced consultant in e-discovery. While he stated the reasons for and history of ASUS’ ‘distributed information architecture,’ he did not state any opinion as to the reasonableness or good-faith in the system’s operation. And while he says ‘ASUSTeK’s data architecture relies predominantly on storage on individual user’s workstations,’ his 31-page declaration does not show he is familiar with the precise practices pointed out in the declarations of employees. Those employees’ declarations describe the practice of ASUS’ email system to overwrite old data regardless of its significance; ASUS’ reliance on employees for all email and data archiving; and the process of replacement of computers, which also relies on employees to transfer data from their old to their new computers. Neither the expert nor ASUS speak of archiving ‘policies;’ they speak of archiving ‘practices.’

The court’s distinction between “policies” and “practices” seems like a convenient (perhaps “Deus ex machina”) way to discount ASUS’ data retention activities and prevent the use of the FRCP 37(e) safe harbor.  Since in most instances, “bona fide, consistent and reasonable” document retention “policies” have been found to be presumptively valid by everyone ranging from Sedona (Guideline 3) to Carlucci v. Piper Aircraft Corp. and Arthur Andersen LLP v. United States, 125 S.Ct. 2129 (2005).  It’s not clear how he draws the important “practices” distinction and why said practices are exponentially different from presumptively valid “policies.”

It’s precisely this line of thinking that confuses the alleged failure of the duty to preserve (discussed at the outset of the opinion) with the duty to retain information.  The court seems to think it’s an “unreasonable” practice to have custodians responsible for compliance with data retention and this deficiency made the safe harbor unavailable.

“ASUS has explained that it has no centralized storage of electronic documents, email or otherwise, and relies on individual employees to archive email (which will be deleted if left on the server) and electronic documents (which reside only on individual workstations).”

Not only is this custodian-based retention practice, in and of itself, reasonable; it’s probably the most common form of data retention practices seen at corporations today.  While a number of vendors have promised intelligent retention systems that work without any significant human intervention, for the most part those solutions are still in their infancy.  Additionally, there are significant technical challenges to have an application manage *all* ESI (Electronically Stored Information) that exist for a given custodian (including desktop files, instant messaging, text messaging, social media, etc.) As such, most companies must inherently rely upon their custodians to both retain and preserve data pursuant to company policies.  The court not only seems to miss this point, but also attempts to impose an obligation that corporations must prevent the “loss of data” above and beyond specific preservation obligations.

“ASUS’ practices invite the abuse of rights of others, because the practices tend toward loss of data. The practices place operations-level employees in the position of deciding what information is relevant to the enterprise and its data retention needs. ASUS alone bears responsibility for the absence of evidence it would be expected to possess. While Adams has not shown ASUS mounted a destructive effort aimed at evidence affecting Adams or at evidence of ASUS’ wrongful use of intellectual property, it is clear that ASUS’ lack of a retention policy and irresponsible data retention practices are responsible for the loss of significant data.”

Although the exact rationale was unclear, the court held that ASUS violated their duty to preserve and that the loss of evidence could not be excused as a “routine, good faith operation of electronic information systems.” While the court ruled that sanctions were appropriate, it reserved final sanctions pending the close of discovery.   Depending on what those ultimate sanctions look like, it seems pretty likely that this decision will be subject to appellate review.  Until then, it’s probably too soon to treat this questionable holding as gospel.  Wary corporations however should continue to bolster the “reasonableness” of their information management/retention/destruction policies and practices so that in hindsight a court won’t be able to take away the FRCP 37(e) safe harbor by casting those “practices” as being unreasonable.

In today’s economy, controlling electronic discovery costs has taken on a new urgency.  Because the financials of many companies have deteriorated so quickly, there is great interest in finding methods to reduce any costs in the short-term.  As  a result, anyone in a company’s IT or legal department that comes up with a plan to substantially reduce their company’s electronic discovery costs in the short-term is likely to become a hero in their company.  So, what’s the best way to reduce electronic discovery costs quickly?

A natural first step is to decide where to focus.  Which electronic discovery activities are the most costly today?  Which have the greatest room for cost reductions?  The EDRM model serves as a good guide for answering such questions by breaking electronic discovery activities into Information Management, Identification, Collection, Preservation, Processing, Analysis, Review, Production and Presentation.  One thing I have noticed when interacting with enterprises is that the IT and legal departments tend to focus on different stages within electronic discovery based on their perspective.  IT managers naturally concentrate on the information management, identification, collection and preservation activities because these are the activities in which they are most involved.  Similarly, legal managers naturally look to preservation, processing, production and review.

Given these different perspectives, it’s important to take an objective approach to calculating electronic discovery costs.  Doing so is not that easy.  Costs can vary significantly depending on each company, the nature of the case, nature of the data, which vendors/technologies that are used and a variety of other factors.  Costs also come in many different forms: direct hard dollar costs, such as spending on legal and electronic discovery fees delivered by third parties; indirect hard dollar costs, such as time spent by company employees; and soft dollar costs, such as increased risk that could lead to adverse judgments and sanctions.  Finally, electronic discovery costs are often buried across both legal operating budgets and IT budgets making it hard to separate these costs from the costs of other activities.

Undertaking an internal analysis to understand your company’s electronic discovery costs is a valuable activity if you want to better control these costs.  However, while costs do vary between companies, most companies will find that the same activities contribute the most direct hard dollar costs and that these are the costs that are easiest to control in the short-term.  To demonstrate this, let’s walk through a generic cost analysis of a typical case.  Fortunately, we don’t have to start from scratch in doing this.  Leonard Deutchman, an author of several excellent electronic discovery articles, has already done most of the work in a May 2007 article, “Get Ready for the Rules Changes, Part VIII“.  In this article, Mr. Deutchman walks the reader through a hypothetical litigation between an Investor and a Venture Capital firm.  He describes the typical electronic discovery activities and calculates the direct hard dollar costs for these activities including:

• Collection: Mr. Deutchman calculates that it costs $10k to collect 400GB from 8 hard drives and the data of 8 custodians on file and email servers using an outside vendor (doing it in-house can be less expensive).  Note that this excludes any collection from back-up tapes, which can be more costly.
• Culling & Processing: it costs $4k to reduce the 400GB to 90GB by removing non-relevant file types prior to processing.  Processing 90GB costs $90k at $1000/GB.  De-duplication and the application of search terms reduce the data to 25GB.
• Production: it costs $4k to produce the 4GB of data that is deemed responsive and not privileged to produce to the other side.

Mr. Deutchman doesn’t identify direct hard dollar costs for Information Management, Identification or Preservation.  These activities are typically not associated with direct hard dollar costs on a per matter basis.  Rather, they involve indirect hard dollar costs such as employee time and software licenses.  Mr. Deutchman also does not provide an estimate for the costs of review.  However, since review does contribute significant direct hard dollar costs for every matter, this gap needs to be filled in order to get a complete sense of the direct hard dollar costs.  The two big buckets of cost in review are: attorney review costs and review software costs.  In Mr. Deutchman’s hypothetical litigation one might imagine the following scenario for these costs:

• 25GB translates into 195,000 documents using the low end of the documents per GB email (9,000/GB) and documents per GB files (7,000/GB). Industry survey data that is available from EDRM.  This example assumes that 40% of the 25 GBs is email.
• The attorneys reviewing the data charge $75/hour and make 100 document decisions per hour.  This translates to approximately $146,000.
• The hosted review service costs $50/GB/month and, in this case, let’s assume we host it for 6 paid months.  This costs $7,500.

If we tabulate these costs and calculate the direct hard dollar cost shares for each stage, the clear take-away is that Processing and Review costs comprise the vast majority of direct hard dollar costs.  Collection and Production direct hard dollar costs are significantly smaller in comparison.

Now, it’s possible to come up with many arguments for why Mr. Deutchman or my estimates could be high including different assumptions for attorney hourly review costs, higher document decision rates, cheaper vendor pricing, etc.  Similarly, it’s possible to come up with many arguments for why the estimates could be low including the need to perform multiple review passes, slower document decision rates, more expensive vendor charges, etc.  In addition, each company will have their own unique circumstances that will change this picture.  However, this generic analysis strongly suggests that more customized analyses would come to the same conclusion: if you want to reduce electronic discovery costs quickly, then you need to focus on processing and review costs.  One can also imagine that even if you were to use some form of activity-based costing to allocate indirect hard dollar costs on a per matter basis, it would likely not change the importance of Processing and Review costs.

What does this mean for IT and legal managers in Corporations?  These kinds of analyses make it pretty clear that, even though they are more involved in the Information Management, Identification, and Collection phase of electronic discovery, IT managers need to focus more on helping the legal team optimize Processing and Review activities.  You are not going to get the biggest bang for your buck in the short-term by trying to reduce costs in Information Management, Identification, Preservation, and Collection.  Similarly, legal managers need to work more closely with IT in order to focus on how to reduce processing and review costs.

So, the obvious question coming out of such an analysis is what’s the best way to reduce Processing and Review costs?  We’ll discuss this issue in a future post.

In the meantime, tell me what you think by participating in our first e-discovery 2.0 poll.  See the sidebar here: Which Phase of Electronic Discovery Do You Think is the Most Costly?

If you have been to LegalTech before, you know that – by the end of the day – you could use a nice stiff drink to recover. So why not do it with some company? We (Aaref, Dean, Kurt, and Will) will be at the Bridges Bar at the Hilton at 7pm, and we are happy to buy drinks for the first 50 E-Discovery 2.0 readers who join us (we will have a big E-Discovery 2.0 sign on our table, so feel free to just stop by and introduce yourself). It’s a great way to meet us, suggest ideas for what we should cover on the blog, and get warmed up before going to the B-Discovery event later that evening.

Come early though. We mentioned the idea to Brandon, who runs the E-Discovery 2.0 group on LinkedIn, and he invited his group to arrive shortly after, so the seats (and the drinks!) may go fast.

It’s a new year in legal technology, and the visions of sugarplums dancing in our heads quickly give way to visions of LegalTech 2009. After all, who can help but dream about another opportunity to brave the icy streets of New York City in February? Fond memories of attempting to wolf down a stale croissant and cold cup of coffee while jostling for an uptown cab outside the New York Hilton can set even the most jaded litigation support manager’s heart aflutter.

The weather and the Manhattan traffic may remain the same, but, as we’re all painfully aware, this year’s show takes place in the context of a dramatic global recession that is having a huge impact on the legal industry’s use of technology, particularly electronic discovery. It’s in challenging times that innovation often thrives the most, so this year’s LegalTech may actually yield a surprising number of new ideas and technologies.

Innovation aside, this year’s LegalTech will likely have a bit of a different “look and feel” from last year:

Some things, of course, never change. Fortunately, the team at Incisive Media has been working overtime to put together a stellar lineup of practitioners, legal experts, and judges to provide insight into some of the key issues of legal technology. While electronic discovery is top-of-mind for many, there’s a lot of more than that on tap. Key sessions include:

• Patrick Oot, Director of Electronic Discovery and senior litigation Counsel at Verizon will lead the first-ever LegalTech Town Hall meeting, to be featured on YouTube. The Town Hall will be an interactive discussion where participants will be able to submit questions in real-time to a panel of experts for immediate feedback and insight on the topics that are of top concern.
• John W. Woods, a partner at Hunton and Williams, will deliver a keynote on “How eDiscovery is Changing the Relationship Between Law Firms and their Corporate Clients”. Clearly there’s a sea change going on here, which seems to be being accelerating by the economy, and it will be very interesting to hear what John has to say.
• Finally, LegalTech would not be complete without a contribution from a leading light of the bench. And this year, none other than United States Magistrate Judge John M. Facciola of Peskoff v. Faber and United States v. O’Keefe will be presiding. Ralph Losey said he’s “just about my favorite judge of all time” and it’s sure to be a fantastic session to get up to speed on the cutting edge of electronic discovery law.

The fantastic speaker lineup, of course, just scratches the surface. LegalTech is also an incredible networking opportunity to meet with fellow practitioners and vendors. However, it can be a little overwhelming, particularly to first-time attendees. So, we thought we’d close with a video that Monica Bay put together last year that provides a quick “how-to” guide for making the most of your time at LegalTech.

As a final note, I’ll be attending the E-Discovery 2.0 LinkedIn Happy Hour before B-Discovery’s LegalTech event.  It’s at the Hilton’s Bridges Bar from 8:00 – 9:00pm on Monday February 2^nd.  Come by and say hello.  If you are not a member of the E-Discovery 2.0 LinkedIn group, sign up here.  See you at the show!

HP announced today that it has signed an agreement with Clearwell to resell the Clearwell E-Discovery Platform. The two companies have been partners for some time and have many joint customers such as Constellation Energy, Del Monte, and Universal Music. But, under this new agreement, thousands of HP sales people will now be compensated for selling Clearwell, giving them a powerful incentive to introduce their customer base to Clearwell’s e-discovery solution.

To my knowledge, this is the first time that a major archiving vendor has agreed to resell a partner’s e-discovery solution, and it raises a couple of interesting questions: why did HP do this deal? And, what does it mean for HP customers?

Ask anyone who tracks the email archiving market, and they will tell you that e-discovery is a major driver of archive purchases. As Gartner’s Carolyn DiCenzo observes: “Legal discovery is being mentioned by almost every client evaluating an e-mail archiving solution.” That’s because whenever a company has litigation, regulatory inquiries or internal investigations, IT is required to provide relevant electronic information to legal or information security. Far better to have it in one repository than spread out on user desktops, email servers, and file shares. So, CIOs are partnering with General Counsels to deploy email archives, much as they did – in years gone by – with the VP of Sales to implement CRM systems.

The problem is that, when you look at archives as e-discovery solutions, they only solve 50% of the pain. In EDRM terms, archives are a very effective solution for collection and preservation, but awful for processing, analysis, and review. They provide a bulletproof way to capture and preserve every message, but do not make it easy to perform early case analyses and cull down data to the very small set of documents relevant to the case at hand.

That’s why enterprise customers find it so compelling to pair up an archive, such as HP’s Integrated Archive Platform, with an e-discovery solution, such as the Clearwell E-Discovery Platform. So to summarize, HP is doing this deal because it’s the best way to provide HP customers with an end-to-end solution for e-discovery. The two products integrate out-of-the-box, have been proven to work together at several large enterprises, and can be purchased from a single supplier (HP). That’s a much easier, lower risk decision for many enterprises than purchasing separate point solutions and cobbling them together.

Very few companies have as much mindshare with corporate CIOs as HP. It can only be good news for the e-discovery market as a whole to have one the largest technology companies in the world out there educating its customers on the value of lowering the costs and risks of e-discovery.

Perhaps the single greatest component of e-discovery costs is review, meaning the pain-staking process whereby teams of attorneys evaluate information to determine its relevance to the case at hand. Why has review become so expensive? A recent Sedona Working Group Paper explains:

In 1990, a typical gigabyte of storage cost about $20,000; today it costs less than $1 dollar. As a result, more individuals and companies are generating, receiving and storing more data, which means more information must be gathered, considered, reviewed and produced in litigation. But, with billable rates for junior associates at many law firms now starting at over $200 per hour, the cost to review just one gigabyte of data can easily exceed $30,000.

That’s quite a difference: $1 to store a gigabyte of data vs. $30,000 to review it; and it has driven corporate legal departments and law firms to embrace e-discovery review platforms. These review platforms, which can be either packaged software or a hosted service, typically emphasize one of two main benefits:

• “Review Faster”: Traditional review platforms increase attorney productivity by increasing the number of documents they can review each hour. For example, the name “Attenex” derives from the claim that it will help attorneys review documents “at 10x” the speed that they could do otherwise. These products help to a point, but – no matter how good the software – there is a limited number of documents that the human brain can digest in a day, so, even with them, review remains very expensive;
• “Review Less”: More recent e-discovery solutions have focused on having attorneys review fewer documents by culling down data prior to review. This can massively reduce review costs, since 80%+ of documents can be eliminated without being read, but it does raise one serious question: how can you be sure that responsive documents do not inadvertently get culled?

The technical term for this issue is “elusion”, meaning: out of all the material judged as not responsive, how many are in fact responsive (i.e., how many false-negatives does your culling methodology produce)? It is virtually impossible to answer that question definitively without a human reviewing the entire dataset to assess relevance which, of course, defeats the point of culling in the first place. So the accepted practice is to use statistical sampling theory, whereby you test a sample that gives you a certain confidence level about the total population. For example, to get a margin of error of 2-sigma with 95% confidence level, you need to randomly select and process one-in-400 documents. How easy is this to do? Actually, it’s pretty straight forward. Any good e-discovery solution should let you create a separate folder containing a subset of non-responsive documents for human review as a quick check on the effectiveness of culling. You can determine the size of your sample according to what confidence level you want to have.

This is an area that Sedona and others have considered in great depth, and there are many excellent papers on the subject by people far more knowledgeable than me. To pick just a few, Herbert Roitblatt has written extensively about sampling in e-discovery and elusion; and, Daticon’s paper may be a few years old, but is well worth reading to understand the origins of the “review less” movement.

Practically speaking, as someone who has seen both approaches in action, I think that “review faster” is helpful, but if you want to massively reduce your e-discovery costs, then the big win is “review less” – even with sampling to mitigate concerns about elusion.

I have written before about the irony of technology companies failing to use technology to improve their own businesses. As with any rule, there is an exception – and in e-discovery, that exception is Cisco.

This will not be a surprise to anyone familiar with Cisco, since the company has a reputation for innovation that extends well beyond networking. In the 1990s, it was quick to embrace the internet, becoming a poster child for how the web can help streamline a company’s operations. Its M&A group has probably done more to power M&A in the tech sector than anyone else, since it was Cisco which disproved the old adage that technology acquisitions do not work.

So it is with e-discovery in general, and E-Discovery 2.0 in particular. The team at Cisco – Neal, Pallab, Mark, Joel and others – are among the most thoughtful, sophisticated corporate legal departments that you will find. They support the large team of inside/outside counsels who represent the interests of Cisco’s global business, and they do it in a way that saves the company money. I have seen them do more with less than companies a fraction of their size. Neal has been talking about the phenomenon that is E-Discovery 2.0 long before me; in fact, he’s one of the people who have educated me on the topic.

Companies like Cisco, Charles Schwab, Qwest, and Wells Fargo, are “canaries in the coalmine”. That’s why, when one of them says something, people listen.

We love investing in technologies and business models that are able to shrink existing markets. If your company can take $5 of revenue from a competitor for every $1 you earn – let’s talk! – First Round Capital

At first glance, this statement may not make much sense, but I think it is actually quite profound. The idea becomes clearer when you think of it from the perspective of a customer. To paraphrase: if you can save a customer $5 by charging them $1, you have a great business. Yes, you will shrink the market, but you will blow your competition out of the water. Consider some examples:

• A small business hungry for leads pays about $1.40 for each call (or unqualified lead) it gets from placing an advertisement in the Yellow Pages, and it has to pay for the ad up front. Compare that to an average cost of 40c per click (or unqualified lead) on Google AdWords – and the 40c is only paid if someone clicks;
• When I took a 2 day trip to Guyana in March, it cost my wife 87c a minute to call my hotel using AT&T. Compare that to 28.6c a minute she could pay for the exact same call using Jajah;
• It must cost over $50 (I’m guessing) to place a personal ad in a newspaper. Compare that to a zero cost for the same ad on Craig’s List. And based on my experience, Craig’s List is more effective (I know someone who met their fiancée on Craig’s List, but have yet to meet anyone for whom a newspaper worked out);
• Many companies doing e-discovery gather data based on custodians, date ranges, and keywords and send it out to service providers like Applied Discovery or Kroll at $2,000 per GB – and then wait weeks for the results. Compare that to paying $200 per GB for a (E-Discovery 2.0) product that enables you to analyze the data in-house – and gives you the results in hours.

All this begs an obvious question: how can someone offer customers the same (or, in many cases, more) value at a fraction of the cost of existing players? That’s where new technology or business models come in. Google and Craig’s List do not spend money on printing and distributing huge volumes of paper; Jajah avoids connection fees and other costs by leveraging VoIP; and, E-Discovery 2.0 products leverage the latest innovations in search, open source, web and storage technologies.

It is ironic that the technology industry is so obsessed by growth, given that its greatest achievement is often shrinking a market.

The other day, I came across the fascinating statistic that over 50% of products returned every year to stores across America have absolutely nothing wrong with them. Apparently, consumers used them for an average of 20 minutes and then gave up, because they were too complicated.

At this point, most customers of traditional enterprise software could be forgiven for thinking: “I wish I could do that.” Enterprise applications are notoriously feature-laden, complicated to use, and difficult to install. They make their users feel stupid, by presenting them with complex pictures that look like amoeba or toolbars with 150 different options. Why does enterprise software seek to punish its customers in this way?

Partly, because customers ask for it. Whether they are buying a dishwasher or an accounting application, people habitually over-estimate their ability to figure out how a complicated product works and, as a result, pay more for features that they never use. Partly, it’s because enterprise software is designed by engineers who think everyone is as technically proficient as they are, and by marketing people who view every additional feature as a new selling point.

By contrast, Web 2.0 applications such as FaceBook, Flickr, StumbleUpon, or Meebo are incredibly easy use. Even an idiot who has never seen these applications before can use them without an instruction manual or a training course. You could say that’s because they are trivially simple applications. But I think it’s primarily because, if they were not so easy to use, people would simply click away and try something else – i.e., they would die.

That to me is the real lesson that Web 2.0 apps can teach enterprise software: make something that is easy to use, easy for someone to install, and easy for them to evaluate. Get people addicted to your application because it’s so good (the average FaceBook user spends 4+ hours a day on the site). No doubt, this is harder to do with enterprise applications because they are inherently more complex. But figure out a way to hide the complexity, packaging all the functionality users need into a design that’s easy to use. This is a key characteristic of e-discovery software applications; it’s the genius of salesforce.com’s CRM application and Apple’s iPod; and, it needs to be a core skill of any company creating enterprise applications today.