Extract from Ryon Lane’s article “Today’s Biggest eDiscovery Challenge? The Wide Variety of Non-email Data Sources”
Does it seem like eDiscovery is more complicated and demanding than ever? There are many challenges in conducting eDiscovery today – the ever-expanding volume of data in organizations, the challenges of hiring experienced personnel who understand eDiscovery workflows and best practices, and protecting Personally Identifiable Information (PII) and other sensitive data. In addition to these challenges, eDiscovery goals still must be achieved within budgetary constraints in a turbulent economy.
By far one of the most urgent and far-reaching eDiscovery challenges organizations face today is the increasing variety of data types subject to discovery. In this post we’ll discuss why this is (arguably) the biggest eDiscovery challenge today, various types of data repositories subject to discovery and data collection, and what you should look for in a technology solution to fulfill not just your eDiscovery needs, but also your Archival and Compliance needs as well.
Increasing Types of Data are the Biggest eDiscovery Challenge Today
That’s a bold statement, right? But don’t take my word for it – it’s market sentiment as well as the feedback of many of you readers. The results of the most recent quarterly eDiscovery Business Confidence Survey published by ComplexDiscovery count “Increasing Types of Data” as the single most pressing issue respondents felt will most impact the business of eDiscovery over the next six months (of a choice of six options). Selected by almost 37% of respondents, “Increasing Types of Data” almost doubled the next-highest choice (“Budgetary Constraints” at 19.72%).
Was that a quarterly anomaly? Not at all. According to analysis of the survey results by eDiscovery Today, this quarter’s results were the 7th time in eight fiscal quarters “Increasing Types of Data” was at (or tied for) the top issue of concern. That’s a bullish trend indicating just how challenging keeping pace with increasing data types has become.
