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.

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