Ediscovery 101 For Collaboration: Why is collaboration data so hard to manage in ediscovery?

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As the world embraces a more collaborative way of working and uses new applications like Slack to communicate with one another, there is a corollary impact on other areas of the business such as why legal is challenged to manage Slack data for ediscovery.


WHY IS COLLABORATION DATA SO HARD TO MANAGE IN DISCOVERY?

Ediscovery-101-For-Collaboration-Article7--SOCIAL-CARDS

Why is Slack data in ediscovery a big deal anyway? What makes it so hard to manage?

To understand the challenge of collaboration data in ediscovery, it helps to understand the origin and structure of discovery. As you know from our earlier posts, discovery started out with paper files. While the incorporation of email gave rise to what we call ediscovery, many of the principles around discovery were unchanged. After all, email is simply an electronic version of the letter, which is a form of communication that’s been around for centuries. 

CHALLENGE 1 - SLACK IS NOT PAPER

The first problem with Slack is that there’s no paper-based corollary for it; it’s an entirely new method of communication. With the exception of direct messages, conversations on Slack aren’t sent “to” a single person; they’re posted in a channel for anyone who belongs to that channel to see. If a custodian—remember, this is the person who has information you need to know about a potential court case—belongs to that channel, they may have seen that information, even if it wasn’t “directed” to them. The novelty of Slack’s structure also means that standard ediscovery tools—which were designed to deal with things that looked like paper—have no idea what to do with the complexity of Slack data.

CHALLENGE 2 - DISCOVERY REQUIRES CONTEXT

The second problem hinges on how discovery works. The purpose of discovery isn’t just to save information for use in a court case—it’s to actually use that information in the eventual case. In other words, you need to be able to read over or review the information, provide it to your opponent, and maybe even present it to a judge or jury for their consideration in deciding your case. 

Reviewability becomes a huge issue due, in part, to the sheer volume of Slack. Organizations can easily generate millions of lines of conversation or millions of direct messages in a single day, most of which have zero relevance to any current or potential litigation. Many of those posts will have abbreviations, emojis, or shorthand responses, if not all three. Sure, you can search Slack to look for particular words that relate to a pending court case, but Slack is usually so casual and fast that it’s riddled with misspellings, incomplete thoughts, and multiple simultaneous conversations. Discovery lawyers may have to sift through hundreds of lines within a channel to figure out whether something is relevant and exactly what it means. All of that surrounding context is necessary and important to figure out what was, and what wasn’t, said.

CHALLENGE 3 - SLACK DATA IS RICH, UNSTRUCTURED, AND COMPLEX

But wait, there’s more! Slack also incorporates different file types—users can attach documents, spreadsheets, images, videos, and so on—and integrates with other apps. If, for example, your Slack instance is integrated with your project management software or time-tracking or expense software, your Slack channels may include notifications about what’s happened in those other programs. Any and all of that information might be relevant and discoverable to a court case, which means you need a way to capture it and produce it to an opponent.

What litigants need is a way to get data out of Slack and into a discovery tool that can figure out how to separate the wheat—the useful messages—from the chaff—everything else.

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