Data Mining & Analytics

Traditional document review for relevancy and privilege has proven to be less accurate, more burdensome and costly as the size of ESI continues to grow. The use of data analytics and conceptualization is revolutionizing the discovery process by significantly streamlining and, in many instances, bypassing costly, linear document review methods. DOAR has proven that when used correctly, analytics can ensure a more thorough review of your data as well as the opposition's and give you a distinct strategic advantage by providing early insight into the document population, speeding up the production process and ultimately avoiding unnecessary costs.

Irrelevancy Identification

DOAR has successfully utilized data analytics to quickly identify irrelevant documents and remove them from the review stream thereby significantly speeding up the overall effort. Domain name isolation and classification allows for further refinement in both exclusion and inclusion of document groups.

Content Categorization

Contextual relationships offer a different view into the document population and present patterns that may exist across the data set so you can start to see what relevance really represents early on. It will also group similar information together based on pre-determined content or some other statistical relevance which in turn lets you speed up the decision making process. Moreover, the application of this type of methodology lets you maintain consistency across the entire document review process and avoid discrepancies in the subjective coding of similar documents across different reviewers.

Privilege Determination

The use of analytics to find potentially privileged documents helps to ensure that the appropriate safeguards have been put into place by casting a wider net to identify those documents based on content and not just email address or the typical privileged language.

Production Analysis

DOAR's application of these techniques not only allows attorneys to review documents that need to be produced faster, it also offers a distinct advantage at gaining insight into the production that you are receiving. For example, you can use documents that are most relevant to the case in your possession to quickly isolate other similar documents received from opposing counsel and determine to what extent they are in compliance with the document request.

Analytics Based Review

There are many circumstances that allow a party to completely bypass the manual document review process when utilizing data analytics. Several factors go into making this decision, one pair of which being the type of data that is available and the level of reliability that goes along with it. For example, while the use of analytics across scanned documents with OCR is far superior to standard keyword searching, the percentage of inaccuracies associated with the OCR process can sometimes throw off the analysis. On the other hand, certain types of native electronic data can be put through the conceptual categorization, issue coding and privilege segregation process with a high degree of accuracy and consistency and be put straight through to production without additional manual review. This methodology considerably lowers the cost of discovery, allowing corporations to perform much of the review in house while letting outside counsel focus on more substantive issues sooner.