Review is not the most expensive part of e-discovery
The mission to reduce document review costs for your firm or your firm’s clients is an ever-present charge. Most attorneys equate legal document review with a painfully high price tag, and many assume that there is no viable alternative. However, as a deeper look into all the elements of the EDRM (Electronic Discovery Reference Model) that compound your discovery costs should reveal: It doesn’t have to be so expensive. How much of your “document review/document production” costs stem from hours devoted to work that is not actual document review?
From the outset, inefficiencies haunt the entire doc review process. From identification to collection, to processing and ESI (electronically stored information) production protocols (or lack thereof), time and money hemorrhage sources abound. We’ve even seen cases where clients spend more time and money negotiating searches and production protocols than on reviewing actual documents. This is just one example of a costly oversight that we see all the time, and it often goes unnoticed or noticed-but-ignored.
This is hardly the fault of the attorneys managing reviews. Until very recently, law schools taught them how to study, interpret, and argue the law—not how to develop ESI production protocols, how to choose search terms, how to negotiate on behalf of a client regarding those search terms, or how to reduce document review costs. As a result, many attorneys think that going back and forth a dozen times to argue about search terms is par for the course and that the time and money spent doing so is unavoidable.
There are several areas surrounding e-discovery workflow and legal document review where we see companies and law firms sticking to old, inefficient and expensive methods that, now more than ever, make it near-impossible to reduce e-discovery and review costs. Most of the time, these methods and the inefficiencies therein end up increasing a firm’s total tab instead.
Four common inefficiency traps
1-Stop overspending on search term negotiations
Historically, the negotiation of search terms between opposing parties has been an important part of e-discovery, but with modern technologies and workflows, the cost of that process now quickly—and often vastly—outweighs any savings. In the old world, reducing the number of documents through aggressive search term negotiations translated into lowering both hosting costs and the number of hours attorneys spent (and billed) for review. When technology took over much of the review process, that suddenly changed.
Simply put, the return on investment of those negotiations doesn’t reduce document review cost as much as it once could. Rather, it’s more cost-effective, and often more accurate, to let the machine learning systems crank through a larger set of documents than for you to spend more time, money and effort on all-too-often ineffective search term negotiations.
In a recent matter, a client’s counsel spent two months negotiating terms with the opposing counsel. Their process resulted in eight different search term iterations, with each cycle taking up both attorney and technician time, but in the end only decreasing the count by about 2% overall. Now that it’s more possible than ever before to reduce document review cost, it’s clear that this practice is overdue for change.
Opposing parties should agree to some basic search terms and first run them through analytics without getting bogged down in minor details. Even if you’re already loading a million documents, it’s wisest to go ahead and load a million and a half and spend less time arguing terms. The benefit of advanced analytics these days is that it can quickly weed out non-responsive files for a fraction of the cost, so you can reduce document review costs exponentially more, even when you factor in hosting and analytics costs.
2-Avoid unnecessary discovery timeline compression
A related concept is the ancillary effect that weeks or months of search term negotiations have on the overall discovery timeline and total costs. In the example above, our review attorney team couldn’t begin their review until the search terms were finalized, which took weeks longer than scheduled. So instead of having the expected six weeks to complete the review phase, the team only had 2 weeks, requiring them and outside counsel to rush the job and work overtime and weekends, all of which increased costs even more. In the end, the 2 months spent arguing over search terms not only racked up large attorney fees on the front end, but it also led to a document review process that was more expensive, unnecessarily rushed and downright chaotic.
Agreeing on more basic search terms may mean pulling in more irrelevant files in the beginning, but a review team powered by analytics and machine learning will not necessarily have to look at all the files, as the platform sets aside non-responsive documents automatically. This way, you don’t run the risk of delaying—or rushing—the review process. Ultimately, the most precious asset these days is time, and any attempt to reduce document review cost should be made with that in mind.
3-Eliminate excessive issue coding
Issue codes are labels used to categorize documents in a way that makes it easier for the legal team to organize documents and quickly find them later in the case. Too often, though, counsel will request 30, 40, or more codes on a single matter, of course with the best of intentions that those codes will help organize depositions, fact outlines and the like. While it’s certainly an option to use that many tags, we’ve found that anything more than 8-10 tags often just slows the pace of review and escalates costs unnecessarily, with very little return value.
Indeed, where clients have insisted on such a large number of issue codes, we’ve later seen those codes combined, reduced or simply never referenced again. Now that the analytical tools (TAR and otherwise) are available and becoming increasingly sophisticated, most review tools are more effective than issue coding ever was. While this may seem like a minor issue, if a reviewer has to make 30 or 40 tagging decisions per document instead of 8-10, your chance to reduce document review cost becomes slim to none. To the contrary, most likely this will increase your review cost—again with very little in return.
4-Eliminate junk attachments
Efficiently and intelligently handling document “families” (groups of related files that contain parent and child documents, such as an email and its attachments) can have a significant impact on your hosting, review and production costs. Consider an email with an attached spreadsheet that also has a company logo in the sender’s signature, as well as social media icons with links to each platform. Technically speaking, those logos and icons are attachments, but they shouldn’t be treated as such for e-discovery purposes. In this simple example, it’s the difference between a parent with a single attachment or a parent with half a dozen attachments. It’s easy to see how that can quickly bloat your database with useless files that simply complicate the workflows and inflate rather than reduce document review cost.
Most modern data processing systems can exclude such irrelevant logos, icons and the like from ever being included in the data promoted to review. Even if your processing platform cannot do that, it’s fairly simple to search for and eliminate those files once loaded into a review platform. Either way, it should be simple even for opposing parties to agree that such files are irrelevant and should be eliminated in bulk as early in the process as is feasible.
Today, the integration of analytics, updated technologies and proper workflows, especially when combined with an experienced review team, enables accurate and effective review of even terabytes of data in a relatively short amount of time, and at a lower cost than ever before. To achieve ideal results, it’s important to establish a trustworthy partnership between the client, counsel and e-discovery team. The legal team should be educated on the possibilities and availability of advanced analytics, and the e-discovery vendor should be able to provide expert advice on running efficient, cost-conscious document review that ensures accuracy, quality and defensibility. Recognizing these common inefficiency traps is the first step to combatting them, and taking the restorative steps we’ve outlined here will empower your organization to reduce document review costs while delivering results case after case.