Data culling may not be the flashiest of topics but it's an essential component to a defensible and efficient e-discovery process. One of the major challenges in e-discovery is that in most cases organizations simply don't know what electronically stored information (ESI) they have, let alone what they will ultimately need. It's common for legal teams to cast a wide preservation net to ensure potentially responsive ESI doesn't get deleted. However, costs begin to soar in the collection, processing and review stages if data sets aren't significantly purged of irrelevant material. Much has been made of the debilitating costs of e-discovery. In reality, for many organizations the bulk of those costs are the result of unnecessary attorney review of ESI.
Like many elements of e-discovery, there is no common blueprint for a defensible culling process and the jurisprudence on the subject is not especially helpful—judges are far more concerned with results than with methods. As a practical matter, each e-discovery project is different and requires its own process. For example, when a lawsuit has been filed, defense counsel can review the fact pattern cited in the complaint for keywords to begin identifying responsive ESI. Conversely, when litigation is merely anticipated, triggering the duty to preserve, counsel has to guess which ESI might be implicated and consequently will tend to collect a substantial amount of it. As a result, it's a good idea for legal teams to develop a basic culling strategy that establishes an effective and repeatable, yet flexible, methodology that can be clearly articulated to a judge or opposing party.
Traditionally, keyword searching was the foundation of most culling approaches. While keyword search is still a useful practice, there are other methods that can be employed prior to keyword and other, more advanced search techniques to narrow the ESI funnel earlier in the overall discovery lifecycle. Following are some useful and relatively simple culling methods that organizations should consider as part of their larger strategies:
Date Range: It may be the simplest of all culling methods yet many organizations are still reluctant to give thoughtful consideration to data range when determining ESI relevance. It's important to establish date parameters with opposing counsel that not only establishes a date range for relevant ESI but also specifies how that range will be applied (create date rather last modified date, etc.)
File Type: To properly cull down large data volumes it is important to look at what file types are germane to the specific matter. For instance, a patent infringement case might be highly dependent on design blueprints and dense engineering documents. In these cases, it may be acceptable to discard files in video formats since they are unlikely to contain relevant information. An HR matter might depend almost entirely on email and other communications, allowing legal teams to filter out all other file types.
Subject Matter Expertise: By definition, culling is the process of removing ESI that is of no relevance to the case. While lawyers may be overseeing the discovery project, they often require input from those with knowledge of the subject matter to determine what types of ESI that are potentially relevant, and it is essential to engage them early in the matter. For example, a lead engineer involved in a particular project may explain that a whole set of documents thought to be relevant to the case by company lawyers are in fact related to a similar, yet separate, project. Also, departments within large organizations may use different terminology to describe the same thing, or the same terminology to describe different things. Without going directly to the source, it's next to impossible for lawyers to identify these inconsistencies.
Electronic Search: Once data sets have been narrowed down through the methods listed above, the final step of the culling process is to conduct electronic searches that scan the documents for relevant terms and related concepts. There are host of available technologies on the market that rely on various search methodologies, from basic keyword searching to advanced computer algorithms, that incorporate keywords, synonyms, concepts, etc. Even though these processes are driven by technology, judges still require parties to give careful consideration to how they are ultimately executed. Electronic searching is not intended to be a rote e-discovery process akin to flipping an on/off switch. As mentioned earlier, each e-discovery project is different and that should be reflected in the electronic search techniques that are employed.
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