At this point, the fact that Slack data is a common source of ESI in litigations and internal investigations should come as no surprise.
With more than 12 million daily active users, each of them sticking around for about 9 hours per day, Slack has largely replaced email as the main communication channel in organizations of all sizes. In fact, most companies report a 50 to 80% reduction in email usage when Slack is in place.
And yet, most legal professionals seem to have missed the news.
A recent industry report issued by eDiscovery Today shows that only about 26% of legal professionals use data from collaboration tools in their cases. When asked to produce Slack data, many legal teams still refuse, arguing that such data would be too burdensome to produce and not proportional to the needs of the case.
While the “undue burden” argument might still work sometimes—like in Laub v. Horbaczewski, No. CV 17-6210-JAK (KSx) (C.D. Cal. Nov. 17, 2020), where the court found Slack data duplicative—recent cases show that courts are starting to realize that discovery of Slack data is not only possible, but generally also proportional.
There’s more. Courts are even starting to consider review and production of Slack data as “generally comparable to requiring search and production of emails.”
Discovery of Slack Data is Often Proportional (and Courts Know It)
The previous quote is extracted from Magistrate Judge Alexander F. MacKinnon’s ruling in the Central District of California around the defendants’ motion to compel production of Slack data in Benebone LLC v. Pet Qwerks, Inc., No. 8:20-cv-00850-AB-AFMx (C.D. Cal. Feb. 18, 2021).
In this case regarding claims of patent infringement, trade dress infringement, and unfair competition, a proportionality dispute arose between the parties when the plaintiff refused to produce Slack data under the “undue burden” argument.
During the meet and confer process ordered by the Magistrate Judge, the plaintiff backed their proportionality objection with an estimated cost of $110,000 to $255,000 to extract, process, and review the 30,000 messages contained in their Slack account. This estimate was based on an attorney review rate of $400 per hour, or $8.50 per Slack message.
If those numbers make you balk, you're not alone. Savvy practitioners (and judges) are increasingly aware that Slack eDiscovery does not have to be difficult or expensive when the right tools are used.
And that’s why the defendants in Benebone knew they could easily counter the proportionality argument. They were able to prove that managing Slack messages could seamlessly be done by using available software.
“Requiring review and production of Slack messages... is generally comparable to requiring search and production of emails” - Benebone LLC v. Pet Qwerks, Inc.
They submitted a cost estimate of $22,000 for the plaintiff to find and produce its responsive Slack messages, based on a quote from a vendor that offered specialized software and contract review attorneys at a rate of $40 per hour.
Judge MacKinnon was convinced and her ruling should be an example to all courts facing needless objections to Slack eDiscovery.
In granting the defendants’ motion to compel production of Slack communications, Judge MacKinnon stated that “requiring review and production of Slack messages by Benebone is generally comparable to requiring search and production of emails and is not unduly burdensome or disproportional to the needs of this case – if the requests and searches are appropriately limited and focused.”
A similar case occurred in 2017 when New York-based litigator David Slarskey was able to compel production of Slack data that was indispensable to his case.
After refusal from opposing counsel to produce Slack communications on the basis of proportionality, Slarskey brought to court Logikcull’s guide to Slack discovery to support his request. By demonstrating that there was software capable of handling Slack data, he forced opposing counsel to produce it—and this data ended up proving essential to obtaining a favorable settlement.
Slack eDiscovery Tools: The Key to Winning the Proportionality Argument
Courts are changing their views on Slack discovery. Most likely, the notion that discovery of ESI from Slack is disproportional will start to be rejected as a general rule.
Especially, if technology is involved.
You may have already realized that the common element between the Benebone and Slarskey cases was the availability of eDiscovery software that could easily handle Slack data.
In Benebone, a $22,000 quote from their eDiscovery vendor and a description of specialized software tools to manage Slack’s ESI were enough for the judge to grant the motion to compel production of Slack data.
In fact, Judge MacKinnon stated that “. . . third-party tools have been developed over the past several years for collecting and reviewing Slack messages and that review and production of Slack messages has become comparable to email document production through use of these tools.”
When compared to the $110,000 to $255,000 plaintiff’s estimate to extract, process, and review their Slack messages, the $22,000 quote presented by the defendant seemed proportional to the needs of the case.
However, this amount could have been even lower—and, consequently, the chances of getting the motion approved much higher.
Using a self-service cloud-based eDiscovery solution like Logikcull would have eliminated the need for vendors and would have brought the overall cost of discovery down by about 30%. All thanks to advanced filtering and searching capabilities that would have reduced the number of documents needing manual review.
This is aligned with David Slarskey’s approach in his case where he even compelled the opposing party to use Logikcull to analyze the data themselves—with no third parties involved. In doing so, Slarskey actually turned Slack data into an opportunity. Not only did he find evidence that led to a favorable settlement, but he also established himself as an innovator.
“We showed the clerk that an effective tool exists and opposing counsel ended up producing the data using Logikcull.” - David Slarskey, Partner, Slarskey LLC
Get Ready for the Upcoming Wave of Slack eDiscovery
Let’s get it out of the way: There’s simply no escape from Slack data.
So, if your workflows are not adapted to support Slack discovery yet, this is the best time to remedy that. As Slarskey puts it: “You’re really doing a disservice to your clients if you’re limiting yourself to emails.”
If you’re not too familiar with Slack’s dynamics, idiosyncrasies, and preservation options, this should be your first step in order to set the right Slack retention and information governance policies or understand your client’s. This includes an understanding of Slack’s pricing plans since each of them has different preservation and exporting capabilities (like accessing Slack’s discovery API) that might affect whether you can successfully preserve and collect Slack data in the event of eDiscovery or a legal hold involving Slack.
Next, you need to find the best way to process and review your Slack data. For starters, when you export data directly from Slack it shows as virtually unreadable JSON code.
This is how a single Slack message looks:
You certainly can't review any file in this format. And you can’t just toss it into any discovery software since most of the available tools are not designed to handle Slack data.
However, with a simple cloud-based solution like Logikcull, you can handle Slack data so that it can be rendered and reviewed as easily as any other document type—and at a much lower cost than most tools and vendors out there.
In Logikcull, managing Slack data is as easy as upload, search, download. Slack’s ESI is searchable and easy to understand as Logikcull creates a display similar to Slack’s user interface.
From there, most of the same discovery best practices that apply to any other document review can be used on Slack data. You can create custom tags, test and refine search terms, run bulk keyword searches or batch documents for your team to review. But most importantly, you’re able to manage Slack data along with any other doc type relevant to your case and keep everything in one secure place.
We can only expect Judge MacKinnon’s comparison of Slack data with emails to become the norm, but you can actually make it work in your favor when you’re equipped with the right tools to manage Slack discovery.
Stay ahead of the game and let Logikcull turn Slack data from a burden into an opportunity by making Slack discovery a simple, fast, and cost-effective process. See Logikcull in action.
