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    Leading Trends in E-Discovery

    Dec 16, 2014

    Kroll Ontrack has issued its “2014 Ediscovery Trends: Industry Survey Results” identifying the top e-discovery trends in 2014. Predictive coding topped this year’s list as 47% of law firms and 37% of corporations reported using this technology last year. Almost three-quarters (73%) said they used it in document production for e-discovery, and almost half (47%) used it in early case assessment.

    Social media was another big trend in 2014. More than 50% percent of the participants were involved in a matter that involved social media data, reflecting corporations’ increased use of social media platforms to build relationships with their customers and market their products. It also presents numerous issues for e-discovery practitioners around privacy, discoverability, preservation, collection, and authentication of data, noted the report.

    Next on the list was BYOD (bring your own device), with 58% of respondents having matters involving data from personal devices. More than a quarter of those were involved in three or more such matters.

    The Internet of Things (IoT) is just beginning to show up on the e-discovery radar, the survey found. It’s expected that IoT will be a growing source of new litigation over the next several years, making now the time to prepare, concluded Kroll. Fortunately, 67% of the legal professionals surveyed have heard of IoT; 29% said they are already preparing for its impact on e-discovery.

    Security also proved to be a serious topic of consideration last year. The survey revealed that 38% of the respondents may be underestimating the importance of data security in e-discovery. These respondents indicated their organizations did not conduct internal discussions, make any changes to internal security infrastructure, or even hire a security consultant.

    So, what’s likely to be the next big trend in e-discovery? According to the survey respondents, look for a greater focus on information governance practices, improved use of analytics to deal with big data, and increased adoption of predictive coding.


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