According to the recent “E-discovery Business Confidence Survey” from ComplexDiscovery, the increasing number of new communication channels in use by modern organizations is the largest issue impacting e-discovery business performance.

Recent cases illustrate the point:

• NFL player Mychal Kendricks pleads guilty and faces a potential 25 year imprisonment after insider trading scheme uncovered over a series of text messages and Instagram posts;
• In Lee v. Trees, Inc., an Oregon Magistrate Judge granted terminating sanctions where plaintiff was found to have manufactured text messages to support wrongful termination claims;
• In GoPro, Inc. v. 360Heros, Inc., a California Judge granted partial terminating sanctions after defendant was found to have forged evidence contained in two Skype conversations;
• In Commonwealth v. Mangel, the Superior Court of Pennsylvania disallowed into evidence a social media post presented by the prosecution as a simple screen shot;
• In Forman v. Henkin, the Court of Appeals of New York reinstated a ruling requiring the plaintiff to turn over private Facebook photos before and after an injury, arguing that “even private materials may be subject to discovery if they are relevant”;
• In Gould v. Farmers Insurance Exchange, a Missouri District Judge compelled two non-party Farmers Insurance agents to comply with subpoenas and produce text messages sent to potential customers, rejecting the argument that this would violate their Fifth Amendment rights;
• In People v. Price, a New York State Court of Appeals made it clear that there is no strict rule or formula that must be met in order to have social media communications authenticated in order to be admitted into evidence.

The growing use of social media, mobile applications and text messages, as well as new collaborative creates a variety of new challenges to e-discovery, including:

• How can you match custodians to all of their content sources?
  • Short answer: Data mapping needs to be re-shaped as ‘identity mapping’
• What methods are available to collect and preserve these content sources?
  • Short answer: Every new content source is unique, requiring its own method of collection
• How can legal teams review rich, dynamic collaborative content?
  • Short answer: Review needs to respect native context and metadata
• How can metadata and conversational context be delivered for production?
  • Short answer: e-discovery throughput needs to be redefined

The Next Generation of E-Discovery

In short, firms need be thinking now about how they can update their e-discovery processes and technology, acknowledging that the shift away from email and documents is nothing short of a redefinition of the basic unit of work. The task is no longer about finding a needle in a haystack, it’s about finding multiple unique needles in multiple unique haystacks.

Firms can address the changes created by the volume and variety of communications and collaborative channels and applications organizations employ for both internal and external communications. Here are some common components:

• Governance: ensuring your policies are updated to define acceptable and prohibited business uses for each network, as well as to define the role for e-discovery professionals in the evaluation of new communications tools
• Identification: ensuring that identities can be proactively mapped between custodians and content sources
• Preservation: defining preservation methods to be used for non-IT and non-custodian-controlled content sources, including social media and mobile applications
• Collection: Outlining of the methods to be employed to collect from each content source, whether it be dependent on the native content source provider, 3rd party technologies or forensic services, or internal IT staff
• Review:  assessing current review technologies to address unique content modalities from each new network, including voice, video, whiteboards, join/leave/modify events, emojis, and other non-text information
• Analysis: similar to above, assessing whether existing analytics or predictive coding technologies can process new content sources, or if reviewed data can exported to third party applications at required throughput