It is certainly true that any policy that enforces the deletion of documents that might otherwise be discoverable should reduce electronic discovery costs.  Thus, document retention policies, just like enforced mailbox size limits, can absolutely help reduce e-discovery costs.  However, implementing a retention policy is not easy.  A recent article in the New York Law Journal by Adam Rosman is very insightful in this regard when he says, “the rub is implementation.”   Mr. Rosman outlines a conversation between a hypothetical company’s Associate General Counsel and the CTO that demonstrates that the major challenge with retention policies is not designing one.  Rather, the challenge is implementing a policy that effectively balances the needs for litigation readiness and e-discovery, regulatory compliance and knowledge management and can be cost-effectively enforced throughout a company’s IT organization and user community.  Given this, it’s not surprising that a 2006 study by Nextpage and CXO research found that “while two-thirds of the companies surveyed have a document retention policy in effect, almost half of them don’t actively enforce it” and why 39% of respondents cited implementing a standard policy and 34% percent said user compliance were major weaknesses in implementing retention policies.

Because of these implementation challenges, retention policies are not a quick way to reduce your e-discovery costs.  They are also not going to reduce enough data to solve an organization’s e-discovery cost “problem.”  First, due to the implementation challenges, retention policies are not going to delete all the electronically stored information (ESI) they should.  Second, HIPAA, Sarbanes-Oaxley (SOX) and FINRA regulations require that many documents must be retained for several years.  Finally, business users will demand many exceptions: emails, loose files, collaboration content, financial records, contracts, etc. that they want to save beyond the retention period for important business reasons.  As a result, even companies with retention policies are going to have a substantial and growing amount of discoverable ESI and the electronic discovery costs that go with that.

Document retention policies thus are a bit like taking vitamins.  They are likely going to help reduce the amount of time you are sick - although you’ll probably find some “studies” that say they do help and some that don’t.  But when you get sick, they aren’t going to make you better.  For that, you need a remedy that directly targets the specific problem.  Similarly, document retention policies, and you can say the same thing about all information management solutions to e-discovery, will help reduce e-discovery costs, but they won’t solve the e-discovery cost problem.  Specific e-discovery solutions are necessary to do that.  We’ll discuss many of these specific e-discovery solutions in the next set of posts in this series.

One year later, the 2009 report bears this out. In contrast to last year, there have been significant changes for many players, most notably Autonomy which has broken into the “Leaders” category. What’s driven these changes in the vendor landscape? Primarily, the increasing importance of e-discovery. To quote, Gartner’s report (p. 4):

Leading products offer more than just search and packaging, but also provide tools for review and case management. Discovery tools are fast becoming a requirement to play in the enterprise part of the market.

This emphasis on e-discovery has clearly helped Autonomy, which “targets the high end of the enterprise market that is looking to manage complex information management and discovery requirements.” (p.8). It bundles the ZANTAZ archive with Aungate Investigator, Aungate Legal Hold, and Introspect, to create million-dollar-plus software packages that can take over 6 months to deploy. The growing importance of e-discovery has also helped Symantec, which has had a two-pronged strategy. First, improve its own Discovery Accelerator (DA) module that enables users to get data out of Enterprise Vault. For example, the latest release of DA finally allows users to do a search within a search, something that many Symantec customers have been requesting for years. Second, provide an API for DA so that other vendors can integrate with it. A handful of vendors have built adapters to the DA API, although I’m not aware of any customers that are using the integrated solution.

On the other side of the coin, the lack of e-discovery functionality has clearly hurt other large vendors, like EMC, HP, IBM, and Quest, all of whom have fallen back within the lower-left “Niche Player” quadrant. In EMC’s case, there is clearly a plan to address this in the form of SourceOne and its recent partnerships with leading e-discovery software providers through the EMC Select Program. But the others have yet to articulate a strategy and are roundly criticized by Gartner for providing limited search and discovery capabilities.

Perhaps the most encouraging thing to take away from this year’s report is that the market is still evolving. The basis of competition has changed from basic mailbox management and archiving of different file types, to support for business-facing applications such as legal discovery. These “application opportunities” have opened the window for a fresh wave of innovation in the archiving industry, and any archiving vendor which capitalizes on them can still dramatically improve its competitive position.

It may be hard to believe, but there was time in the very recent past where the iconic EDRM model did not yet exist. No multicolored boxes, no arrows, no sloping volume and relevance lines — nothing. Coming up with a standard way of talking about electronic discovery was the first problem that the group set about solving, and I think it would be hard to argue with the fact that they came up with the gold standard: a simple, clear, concise model that, at least so far, is standing the test of time as a way of thinking about the flow of the e-discovery process.

With each passing year, the group has started to address a broader set of problems, all with a practical bent.  Currently, there are eight:

This year’s annual EDRM conference took place back in May. After years of meeting in the same chilly and wind-swept location in downtown St. Paul, Minnesota, George and Tom had the brilliant idea of spicing up the meeting a bit by moving it to a more exotic locale: Bora Bora! Plans were set in motion, but quickly the overwhelming feedback came back from EDRM members: E-discovery is so fascinating, so heart-warming, that adding Bora Bora to the mix would simply be too much for the vast majority of the participants to bear. So St. Paul it was!

This was Clearwell’s third EDRM conference, and location aside, it’s been fascinating to see how it has changed over the last few years. Here are several notable trends from this year’s kickoff:

• More participation from end-users: There was a definite increase in the number of end-user/consumer participants (that is, those not from the vendor community), particularly from law firms. This could be taken as further evidence that e-discovery is indeed moving in-house.
• Increased enthusiasm to take on new challenges: One of the great things about EDRM is its willingness to try to tackle new areas that aren’t being directly addressed by some of the other (fantastic) organizations out there like Sedona. This was in evidence several years ago, when Clearwell was fortunate to get involved in the early stages of the EDRM XML project, which has proven to be a huge time, cost, and risk reducer for many in the industry by providing a common standard that can be used to move data within the e-discovery process. It was in evidence last year when Clearwell’s CTO was able to help launch a new effort around Search that is seeking to develop standards and best practices in an increasingly complex and contentious area. And, finally, it was in evidence this year with the launch of the Information Management project, a cutting-edge group that is exploring how to solve the challenges that e-discovery poses for information management - certainly a complex area in need of thought leadership.

• Improved collaboration: One thing that has amazed us from day one is how collaborative EDRM is, and continues to become. There are a lot of e-discovery vendors involved who, outside of the confines of the St. Paul Hotel, aggressively compete in the marketplace. However, George and Tom have been able to create an environment at EDRM where competitive spirits are set aside and ideas can be cultivated which provide huge value across the e-discovery landscape (both vendor and consumer).

One final note: If you’re an e-discovery practitioner in a law firm or corporate setting, I’d encourage you to get connected, either informally (through the EDRM web site) or formally (by signing up for one or more of the projects). While end-user involvement continues to grow, there is definitely still a need for more non-vendor involvement. It is critical in ensuring real and relevant problems get solved, and to pushing the state of the art in e-discovery forward. Please join us!

Corporations have the following options for reducing e-discovery costs. Some of these approaches are aimed at changing the overall way e-discovery is performed. And some of these are aimed at improving the results of a particular step within a typical e-discovery process. None of the options are mutually exclusive.

• Retain less data through information management: one of the methods that corporations can undertake to reduce e-discovery costs even before e-discovery has begun is to adopt a data or document retention policy. Such a policy can, for example, stipulate that the corporation deletes all documents not required for specific business, legal or compliance reasons after a fixed period of time, such as 90 days. As a result, a properly implemented document retention policy has the potential to significantly reduce the amount of data that is identified and collected during electronic discovery.

• Better assess your case and your discovery issues: another approach to reducing the overall costs of litigation including discovery is to perform an early case assessment. Pioneered by Dupont and others, the objective of this approach is to understand all the key case facts within a short period of time so that the litigation team can make better decisions quicker. Because costs always rise over time, quicker resolution of litigation reduces costs. While early case assessment was originally an overall approach to litigation, there is now an equivalent in electronic discovery. The goal is to identify all the potentially discoverable data, but only collect, process, and analyze a prioritized portion of this data in order to inform an understanding of the case AND calculate an estimate of the ultimate potential e-discovery costs.

• Bring e-discovery in-house: another holistic method for reducing electronic discovery costs is to manage all or a portion of the e-discovery process in some or all matters inside the Enterprise as opposed to outsourcing it to law firms or litigation service providers. While bringing e-discovery in-house has other benefits, such as improved security and control, the principal benefit is to convert variable service costs, typically priced on a per Gigabyte basis, into fixed software costs thus producing a return on the investment to manage e-discovery in-house.

• Preserve and collect less data: in addition to holistic approaches, e-discovery costs can be reduced at each step in the e-discovery process. One way to reduce e-discovery costs would be to preserve and collect less data. Reducing the amount of preserved and collected data not only reduces the cost of each of these steps but also reduces the cost of each downstream step. There are pros and cons to this approach which I will discuss in a later post.

• Process less data: more data is frequently preserved and collected than needs to be processed for analysis and review. This excess data can be filtered out prior to processing thus reducing processing and all other downstream costs. The techniques used to do this are often referred to as pre-filtering, pre-processing or early data analysis.

• Process differently and review native: historically, most electronic data was converted to an image format, such as TIFF, prior to review. This process is computationally intensive and expensive. In recent years, e-discovery practitioners have been processing and reviewing more documents in a native or near-native format and avoiding the cost of converting documents to an image format until later in the process.

• Review less data: data can also be reduced after processing and prior to review and production. Much has been written in the e-discovery community about this process, often called “cull-down,” and the different search and analysis techniques that can be used as part of this process, such as keyword search, concept search, de-duplication, and others. The fewer documents requiring processing and review, which as we have seen is a substantial portion of the overall costs, the lower the overall costs.

• Review data faster: in addition to reducing less data, the electronic discovery community has pioneered new methods of reviewing data faster including data clustering, near de-duplication, and other more automated review techniques. The faster documents are reviewed, the lower the attorney review costs.

While all of these approaches have the potential to reduce the costs of electronic discovery, some are going to be more effective than others. Each approach can be implemented using a multitude of techniques or practices and each of these techniques has their pros and cons. For example, some techniques may have a greater risk of raising defensibility issues from the court or opposing side than others. Other practices may be less expensive initially, but, over the course of a changing and iterative e-discovery, may prove to be more costly overall. In a series of future posts, we’ll review the different practices used as part of these approaches and analyze the pros and cons of each to understand which may be the most effective for your organization.

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.