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Putting Context into Discovery of Messages

Published September 2, 2021

Written by Doug Austin, Editor of eDiscovery Today

The session at ILTACON 2021 last week that I moderated was titled Better Together? E-discovery with Teams and Other Collaboration Platforms and we discussed discovery considerations associated with collaboration apps like Slack, Teams and Zoom. We also discussed a few cases tied to the topic, including Sandoz, Inc. v. United Therapeutics Corp., which was on the production of text messages.

Why did we discuss a case involving text messages in an educational session about discovery of collaboration platforms? I’ll explain.

Contextual Text Messages

In the Sandoz case, the defendant sought an order compelling one plaintiff (RareGen) to produce contextual text messages according to the same rules adhered to by the defendant and another plaintiff (Sandoz) and consistent with the Special Master’s March 2021 Order (before that order, those parties had not produced them either). The Special Master rejected plaintiff RareGen’s timeliness objection regarding the motion to compel and ordered them to produce contextual text messages. It’s a simple case ruling.

But what are contextual text messages and why were the parties in the case disputing production of them in discovery? Contextual text messages are messages that are part of a conversation that don’t hit on search terms for relevance but are still needed to fully understand the conversation between the parties. Because each message is stored individually, you can’t get the full understanding of the conversation that took place without including those contextual messages.

For example, this case dealt with an exclusive deal to distribute a cardiovascular drug, certainly the name of that drug would be one logical search term to apply to text messages. So, hypothetically, if an employee of one of the parties asked another employee “Hey, did you discuss potential distribution of {drug name} with Fred?” and that employee responded with “Yes, he said he is interested”, that second message would be a contextual message – it wouldn’t be retrieved by the search term, but could still be very important to the case.

Defining Context and Why This Isn’t an Issue for Emails

Of course, the question then becomes which messages are considered contextual? To some degree, that can be open to interpretation, but if those messages were proceeded with a question about “How was your weekend?” and a response of “It was great, we went to the beach”, those messages probably wouldn’t be considered contextual. However, because defining context can be so subjective, you may have to define what constitutes a conversation within those messages.

Often, parties agree to produce any day’s messages with relevant content, but they may also agree to produce the entire history of a conversation between parties if the discussion lasts several days.

For emails, we never have to worry about this issue because each email is a snapshot of the conversation up to that point – search terms that hit on any part of the conversation will retrieve the entire conversation (whether all of it is contextual or not). The issue with email is deduplication, not context.

But it Does Apply to Collaboration App Messages

However, messages in collaboration apps are individually stored just like text messages; hence, the contextual issue applies to them as well. Just like with text messages, you need to apply context to collaboration app messages to fully understand the conversation.

So, that’s why we discussed that case in an ILTACON session about collaboration app discovery!

Conclusion

If you expect discovery of text messages from mobile devices and/or collaboration app data and chat messages, it’s important to establish an understanding up front with opposing counsel how those contextual messages will be handled, which may entail defining what a “conversation” is for discovery purposes regarding those messages. Otherwise, you may be leaving important evidence behind or be forced to engage in motion practice to get that evidence (like this case).

Speaking of the session, I want to thank the panelists I worked with for a great session with lots of great insights – Damon Goduto with Lineal Services, Rose Jones with King & Spalding LLP, Jack Thompson with Sanofi and Martin Tully with Redgrave LLC – as well as Gordon Moffat of Pillsbury Law for doing a great job coordinating the session for us!

Learn more about collecting data in Teams and other collaboration platforms.

And for more educational topics from me related to eDiscovery, cybersecurity and data privacy, feel free to follow my blog, eDiscovery Today!