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Collaboration tools like Slack have revolutionized the way we work, helping teams be more productive than ever before. In early 2020, as widespread remote work took hold, Slack’s concurrent users jumped from 10m to 12.5m in a matter of weeks.
As more and more day-to-day work happens in Slack, more and more business information is generated and stored in the platform. Think: dynamic Slack channels and messages, threaded conversations, files and gifs, standard emoji reactions including ones you can create yourself, not to mention, the ability to edit and delete messages. The net effect is a meteoric rise in unstructured data (a.k.a. data that exists outside of clearly defined and searchable formats). Yet, no matter how hard to reach, this data is integral to how we work, and therefore, highly relevant to corporate litigation and investigations.
Thanks to the interactivity of new tools like Slack, the way that we communicate has evolved. The way we conduct discovery must evolve, too. In fact, 25% of industry respondents in a recent eDiscovery Today survey said that discovery of collaboration app data is the biggest area organizations need to address in 2021. Let’s take a closer look at some novel Slack eDiscovery challenges and how to tackle them.
For a growing number of companies, Slack is where the majority of work happens. At the time of writing, Onna’s 137 active Slack users have collectively sent 147,994 messages in the last 30 days alone. For a ~150 person company, that’s a significant amount of data. You can only imagine how many messages are exchanged in a company of thousands of employees — never mind the threads, links, and JPG, PDF, GIF, ZIP, etc., files that go along with them.
When you’re working with massive, multi-faceted datasets like this, the most expensive part of eDiscovery is often the review phase. A surefire way to keep review costs down is to avoid collecting irrelevant data in the first place.
Sync and archive specific workplace data in a search-ready, real-time data repository to avoid reactive, unwieldy collections. By choosing what Slack data to collect and preserve at the outset, you can avoid unnecessary processing and review costs later on.
You can have all the right information at your disposal, but if it’s incomprehensible and lacking context, it won’t get you very far. If you’ve come across the notorious JSON file in your Slack eDiscovery journey (see below), you know what we’re talking about.
When you request a corporate Slack export, the above is what you’ll end up with. All the information is buried in an indecipherable language. It’s difficult for even the most diligent legal teams to make sense of with time on the table — let alone in a hurry. Without the right tool in place, identifying what’s relevant for a case is time-consuming, expensive, and raises risk of error.
Slack exports that give you a full, contextual view for early case assessment. The right eDiscovery solution will pull and process data in its original format, giving you conversations as they actually happened, with edits and/or deletions indicated.
From intellectual property to trade secret disputes, whether or not a party was privy to certain company information is often relevant in litigation. When it comes to cloud-based communication like Slack, however; how do you prove someone was “in the room” if they didn’t send any messages?
To solve this particularly thorny challenge, you need a tool with the ability to identify all Slack channel members, whether or not they actively participated in any conversations. This is a must-have feature to look for in a Slack eDiscovery solution, as it ensures complete, accurate, and defensible discovery.
A big part of Slack’s user-friendliness is the amount of customization available to users. From color schemes and notification settings to reminders and integrations, individuals can make the application work exactly as they want it to. Slack also gives users the ability to both delete and edit messages after sending, which can make things tricky when it comes to preservation.
Effective preservation for Slack legal holds that also stays in line with your company’s standard retention periods. This means your Slack eDiscovery solution retains custodian data even if the source data is deleted or removed. You’ll also want to be able see edits and deletions when previewing Slack data during early case assessment. Another really useful feature for preservation is ID-mapping capabilities — so that you can identify the same individual across multiple Slack instances or sources even when name/credentials may differ.
The big takeaway here is that traditional eDiscovery tools haven’t caught up to the sophisticated, complex nature of Slack data. If you’ve encountered, or expect to encounter, any of the above challenges, fear not — our platform was built to solve them all. Every solution given here is a feature of Onna’s Slack eDiscovery solution. By doing all of the above and more, we dramatically cut the time and cost of collecting, processing and reviewing data. Our intelligent indexing and machine learning processing paired with precise search capabilities, filtering and tagging, can help you quickly find and export only the data you need.
Our most diligent customers also archive data from Slack and other apps through our platform’s auto-sync and archive function, meaning they have real-time repositories of data. Whether you need to produce ESI for litigation, internal investigations, government retention mandates, audits and more, you can access what you need at a moment’s notice.
As a cloud-conscious solution, the challenges we’ve discussed are not all unique to Slack. We’re continually working on new features to enhance the accuracy, completeness and efficiency of managing cloud-based eDiscovery, so businesses can continue to benefit from best-of-breed tools and their legal departments can sleep a little better at night.
If you’d like to learn more about our Slack eDiscovery solution or how we work to bring key information from all of your apps together, reach out to us here.