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What's in a name? Quite a bit, it turns out.

Consolidation of the many ways an individual can be identified using advanced name normalization techniques provides multiple benefits in discovery.

In discovery, a key aspect of understanding your data is ascertaining to what extent key players involved with the case show up in the data, and specifically, which communications and documents they can be tied to. Whether you are working on early case assessment, fact discovery, or privilege review, clarifying who exactly is party to specific communications or documents is core to the mission.

Yet, in many cases, this core activity is frustrated by the existence of various name variations, aliases, and titles for any single individual. At the start of the review, anticipating and manually configuring all the possible permutations for any given individual’s name, email address, or title is a speculative, painstaking, and error-prone process. Even at the end of the review, the work of consolidating and standardizing name references can be excruciating drudgery as anybody who has had to prepare a privilege log can attest to.

Luckily, name normalization tools provide an automated way to simplify and scale the tedious process of consolidating and standardizing name references for a large number of individuals while also increasing the comprehensiveness and accuracy of the information you store and leverage for each of the key players you are researching. Once integrated into your review platform, name normalization provides a way to supercharge key downstream workflows including keyword analysis, strategic searching, email thread review, witness preparation, privilege review, and production gap analysis.

Name normalization tools work by isolating and consolidating information found in the headers and signatures of email communications and other documents. Name normalization is designed to scan, identify, and associate the full set of name variants, aliases, email addresses for any individual referenced in the data set. For example, header and signature mentions like Karen Jones, Karen Sparck Jones, K Jones, KS Jones, Dr. Jones, kjones@company.com, may all link to the same person. A name normalization algorithm will recognize these similarities and group them to a unique individual’s entry which can then be edited and invoked for downstream querying, searching, reviewing, and reporting. Additionally, once an individual has been identified and logged by the system, they can be linked to a larger role-based profile such as Chief Scientist, Executive, or Internal Counsel, allowing you to easily run aggregate level searches and reports on different types of key players.

Getting your key player name references in order is especially helpful when your aim is to understand who is communicating with whom about underlying facts. Name normalization tools  help you get to the key email threads that matter, and then help you efficiently navigate through each particular thread to understand who is linked to each message. Through the process, you will be able to confirm your hypotheses about who is involved with which particular issues, discover other people of interest you were previously unaware of, and subsequently develop a strategy for leveraging key people and the documents they are linked to for deposition preparation.

For more information on the benefits of name normalization in eDiscovery, click here.

 

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