Webinar Recap: Get the Most Out of Your Slack Early Case Assessment



One of the keys to managing the cost of ediscovery—and litigation more broadly—is effective early case assessment (ECA). When you can quickly and accurately predict the future of a case, you’re more likely to, as Kenny Rogers would say, know when to hold ’em and know when to fold ’em.

Often, data within the collaboration platform Slack offers a fast way to gain insight into a potential case. But Slack data poses several challenges, especially during ECA. That was the topic of a webinar Hanzo presented recently, “Get the Most Out of Your Slack Early Case Assessment.” Here’s what we talked about. 

Why Slack Data Is Useful for Early Case Assessment

The goal of ECA is to quickly and inexpensively assess the risk that a potential matter poses.ECA lets you efficiently gauge what is at stake in terms of the time, money, or reputational damage it could cost to defend or prosecute an issue. Legal teams need to identify the key players rapidly in a dispute, the data sources they’ve used, and the timeframes that are relevant to the underlying facts. Next, they need to survey those data sources to gain a sense of the veracity of any claims or defenses. Once they’ve identified and analyzed potentially relevant information, they must preserve information if litigation ensues. Finally, they need to turn their insights into action, whether that’s settling a matter, rebutting an assertion, or digging in for a fight. 

Collaboration platforms such as Slack have already changed the way businesses communicate and share information. Because Slack messages have replaced so many internal conversations that used to occur over email, they’re a logical place to start with investigations and ECA. But just because Slack data is helpful in ECA doesn’t mean it’s easy to get to—at least not with conventional approaches. 

The Challenges of Using Slack Data in Early Case Assessment

The first challenge around Slack data is its volume. Users send more than 1.5 billion Slack messages per month, many of which are so short as to be meaningless without the context of their surrounding messages. And that content isn’t static, like an email—users can add new threads or expand threads at any time and, if their settings allow it, even edit and delete messages. Slack data is complex, too, with emojis, GIFs, file attachments, and hundreds of integrations uploading data to the platform. 

Unfortunately, Slack’s internal search engine is less robust than traditional ediscovery tools when identifying relevant messages. That makes it hard to locate all of the messages associated with a custodian, pinpoint relevant conversations, or discern the context of messages that contain keywords. Finally, Slack exports data in an unwieldy, frankly unfriendly JSON format that your team can’t readily load into ediscovery review platforms.

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