The total amount of data generated as part of daily business operations was already on a massive upward swing as information technology developed over the last 20 years. This increase skyrocketed even more dramatically with the use of Big Data as part of business analytics and online transactions using customer information.
From the perspective of litigants engaged in the discovery, organizations anticipating potential litigation or organizations engaged in compliance reviews, this massive uptick in data presents two primary concerns: Cost and Due diligence. Analyzing large troves of data for compliance purposes or for litigation purposes can be a costly and potentially risky endeavor, particularly if the organization is unable to effectively manage its data holdings for the purposes of litigation or compliance.
One method to reduce costs and risk for organizations involves a process known as Early Data Assessment (EDA). EDA services can reduce compliance cost and make the process of data review even more effective by providing organizations the ability to identify critical and important documents. It also removes the need for irrelevant data, including running file extension analysis to triage data and eliminate junk and responsive content, keyword development and subsequent validation with false positive and false negative analysis, term restriction analysis through human and computer-assisted document review.
Aside from potential savings arising from risk reduction, the cost savings from EDA can be significant. One study, studying timesaving when employing computer-based predictive coding to review data holdings suggested that when compared to traditional document review, EDA saved about 80 percent in attorney review hours. Given the fact that reliable studies indicate that nearly 75% of e-discovery costs derive from attorney review time an assumption can be made that these methods can result in an overall reduction of compliance costs.
Litigants engaged in active or anticipating pending litigation or businesses conducting internal audits for compliance purposes must be prepared to conduct a thorough and accurate analysis of the data generated by day to day operations. The burden of meeting due diligence requirements for compliance review and for discovery can be particularly complex if the data review involves a number of different data sources and storage methods the problem of “data silos” or the fragmenting of data into distinct and separate silos. EDA can provide a safety net for organizations who under other methods of data review may fail to spot potential problem areas or may not be able to conduct a comprehensive review of all data due to complex data structure and storage.