After thread and duplicate management tools, the final major tools and techniques available for pursuing the three goals of ECA are advanced analytic tools, powered by semantic indexing and other advanced mathematical analyses, including: concept searching, concept clustering, categorization, TAR 1.0 and 2.0 workflows, and new AI tools.
Any modern document review platform provides case teams with a powerful set of tools for investigating their collected ESI in pursuit of the three goals, like a series of overlapping lenses you can use to bring your quarry into sharp focus. After sampling tools and searching and filtering tools, the next major types of tools available for pursuing the three goals of ECA are tools for handling email threading and for handling duplicates and near-duplicates.
Any modern document review platform provides case teams with a powerful set of tools for investigating their collected ESI in pursuit of the three goals, like a series of overlapping lenses you can use to bring your quarry into sharp focus. The next major type of tools and techniques available is search and filtering, including keyword and phrase searching, Boolean searching, fuzzy searching, conceptual searching, and more.
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Practitioners have a wide array of tools and techniques at their disposal to work towards each of these goals during the ECA phase of an eDiscovery project. The specific bells and whistles of those features vary, but the core functions almost always include: searching tools, email threading tools, duplicate handling tools, conceptual analysis tools, and random sampling tools.
The fog of war is apt shorthand for the state of uncertainty that exists early in a new legal matter. Whether you are gearing up for litigation, an agency enforcement action, or an investigation, you are faced with potential conflict and liability shrouded in a fog of uncertainty. Early case assessment (ECA), fundamentally, is the process of trying to clear as much of that fog as possible.
In addition to the core activities of expansion, extraction, normalization, indexing, and objective culling that we have already discussed, there can be a variety of additional steps required during processing to prepare the materials for subsequent early case assessment, review, and production activities, including: creating custom fields, TIFF images, and load files; and performing some form of quality control validation.
Processing also includes several types of objective culling that are used to reduce the amount of material that must be worked with throughout the subsequent phases of a discovery project, saving both time and money. The objective culling options commonly employed during processing are de-NISTing, deduplication, and content filtering.
Almost every processing effort encounters at least a few exceptions during processing that cannot be handled without some manual intervention (if they can be handled at all). Additionally, certain source types are special cases that routinely require custom work to process. The handling of these exceptions and special cases can affect both project costs and the completeness of your data set.
Broadly speaking, there are four main activities that take place during processing: expansion, extraction and normalization, indexing, and objective culling. In this Part, we will discuss the first three of these activities, review how decisions made during them can affect later discovery activities, and touch on some of the tools commonly used to complete them.
ESI processing for discovery is one of the areas in which legal practitioners need some level of technology competence to fulfill their duty. Although it is often given short shrift compared to the steps that come before it (preservation and collection) and after it (assessment, review, and production), effective processing is critical to the success of those downstream steps and includes a variety of important decisions to make.