New Cases on Hot Discovery Trends: Collaboration Tools, Categorical Privilege Logs, and IoT Evidence

Among hot topics in discovery practice, some of the most noteworthy include collaboration tools, privilege logging workflows, and the proliferation of new data sources through the Internet of Things (IoT). With courts having issued few decisions on these topics, three recent cases addressing these issues are particularly significant.[1] The first is Charter Communications Operating v. Optymyze, which focused on the discovery of relevant chat messages from the defendant’s Microsoft Teams platform.[2] The second is Maxus Energy Corp. v. YPF in which a Delaware bankruptcy court ordered produced thousands of communications previously withheld as privileged and which were reflected on a categorical privilege log.[3] The final case is State v. Burch, in which the Wisconsin Supreme Court considered both the nature and admissibility of Fitbit data and other non-traditional ESI.[4]

Charter Communications v. Optymyze

In Charter Communications, plaintiff requested production of relevant chat messages that defendant’s employees exchanged on Microsoft Teams. In response, defendant turned over the relevant messages, but its production segregated each message into an individual document, separate and apart from any other messages the users exchanged. The result was that defendant produced 87,000 individualized and separate messages as emails that often memorialized just a few words or lines of text. Plaintiff then demanded that defendant produce the Teams messages in native format so plaintiff could reconstitute the messages into conversations. After defendant declined to do so, plaintiff moved for relief and the court granted plaintiff’s motion, ordering defendant to produce the Teams messages in native format.

Maxus Energy v. YPF

In Maxus, the bankruptcy court ordered the parties (pursuant to their agreement) to use categorical privilege logging, in which documents were identified according to category descriptions rather than individual ones for each document. Pursuant to that order, the defendant parent company—which was involved in an adversary proceeding initiated by a trust for the parent’s subsidiary—withheld on privilege nearly 5,700 documents (among other items) which the parent and the subsidiary previously shared and identified them in three discrete categories on a privilege log. In response, the trust argued those categories described documents that were not actually privileged. The court agreed and ordered them produced in discovery. In a final effort to stave off production of those materials, the parent and its co-defendants argued they should first be permitted to conduct a document-by-document review and individually log documents before turning them over to the trust.

In rejecting this argument, the court reasoned that defendants had long since waived their rights on this issue by reaching an agreement with the trust—and obtaining the court’s approval—to instead use a categorical privilege log. While categorical logs may obviate the extensive costs and delays associated with document-by-document logs, the court noted that such logs also have drawbacks, such as the possibility of having to produce en masse documents previously designated as privileged.

State v. Burch

In Burch, the Wisconsin Supreme Court considered the nature and admissibility of Fitbit data from the victim’s boyfriend (Detrie) in connection with the defendant’s argument that he was not responsible for the victim’s homicide. While the defendant argued that Detrie committed the murder in question, both law enforcement and the court dismissed defendant’s assertion that Detrie was the assailant based on evidence from his Fitbit. In contrast, evidence from another non-traditional data source—geolocation data from defendant’s “Google Dashboard”—strongly suggested he was responsible for the crime.

In particular, the court observed that Detrie had a Fitbit Flex, which it described as “a wrist-worn device that continuously tracks the wearer’s steps and interfaces with the wearer’s phone or computer.” During the timeframe when the homicide transpired, Detrie’s Fitbit confirmed that he took only 12 steps. In contrast, Google Dashboard information the police obtained from Google (based on defendant’s email address) established that defendant’s Samsung smartphone was at the following locations: “[The] bar [the victim] visited the night of her death, a location near [her] residence, the place where [her] body was found, and the [freeway] on-ramp where [her] discarded clothing was discovered.”

Ultimately, the court affirmed a lower court finding that the State, as the movant, only needed to satisfy a sufficiency standard to authenticate evidence from Detrie’s Fitbit. In addition, the court held that the State did not need to introduce expert testimony to establish the reliability of the Fitbit evidence, which exculpated the victim’s boyfriend from involvement in her homicide.

Conclusion

The above referenced decisions exemplify various practice points including the need to produce enterprise chats in a reasonably usable format, understanding the benefits and possible drawbacks of categorical privilege logs, and the growing importance of non-traditional forms of ESI. They also underscore the need to stay current on evolving practices and technologies, along with the cases addressing them.