In ediscovery, most of the information collected during litigation involves email and other communication data (e.g. Slack and MS Teams). But the growing use of SaaS applications adds an additional element to the blanket term “collaboration data.”
These applications encompass many uses, including project management, ticketing services, content management, sales data, and more. And each of them usually contains a communications element using comments or built-in messaging channels. This dynamic functionality along with the easily adoptable nature of these applications creates a sprawl of complex sources of discoverable information across the enterprise data landscape.
How ubiquitous is SaaS sprawl? In a 2022 Hanzo blog, I cited a source that showed 99% of organizations were using one or more SaaS solutions at the end of 2021. And even more telling, according to the 2020 SaaS Trends Report, enterprises with employees ranging from 100-1000+, used on average 288 different applications within their organization. That study also cited a 60% app turnover rate, indicating a constant influx of new data sources continually introduced into an organization’s enterprise data stores.
Challenges with SaaS Data Collection for Ediscovery
When it comes to collecting electronic data for evidence during litigation, the Federal Rules of Evidence put great emphasis on accuracy. FRE Rule 1001 defines an admissible copy as being, “produced by methods possessing an accuracy which virtually eliminates the possibility of error.” And FRE Rule 1003 puts accuracy and precision above the need to collect an original: “When the only concern is with getting the words or other contents before the court with accuracy and precision, then a counterpart serves equally as well as the original if the counterpart is the product of a method which ensures accuracy and genuineness.”
With this priority on accuracy, you would think this would be reflected in data collection methods, but so far many companies are using basic data exports and screenshots in an attempt to capture the dynamic nature of these applications if they’re even bothering to preserve this data at all.
Examples of SaaS Application and Dynamic Data in Ediscovery Case Law
Sensory Path Inc. v. Fit & Fun Playscapes LLC (N.D. Miss. 2022)
This case is an example of using screenshots as evidence, rather than more modern collection methods for dynamic websites. In this case, screenshots were taken from the Internet Archive, a website that provides access to archived internet pages through its service known as the “Wayback Machine” and paired with an affidavit from a Records Request Process to authenticate them, as screenshots are not self-authenticated.
Antoinette Judy Famulare, Plaintiff v. Gannett Co, Inc (March 2022)
In this case, the plaintiff produced reports via screenshots of the Salesforce dashboard. The defendants could only produce Salesforce’s historical data exported to a Microsoft Excel spreadsheet, arguing that “it is not possible to give Plaintiff this actual information in the form of screenshots of the Salesforce Dashboard due to the dynamic nature of the platform.”
It’s this dynamic nature of the platform that is worth our attention here. Yes, the data from Salesforce was exported into a spreadsheet, but that spreadsheet doesn’t capture the SaaS platform’s interface in the same way, which often adds to the context, understanding, or at times additional data that may not have been a part of the export. And while screenshots can capture some of the visual nature of the data, they are static and must be authenticated by witness affidavit.
Ace Am. Ins. Co. v. First Call Envtl., LLC, (E.D.N.Y. Jan. 9, 2023)
This case highlights the growing instances of SaaS application data being requested for discovery. Here the defendant's employees were to fill out, review, and upload safety reports, meeting notes, employee concerns, and other descriptions of activities that were to take place on the job site to the defendant’s web-based SaaS application, Basecamp.
Basecamp is a project management application that includes a message board, to-do lists, document and file storage, chat messaging, calendars, and more.
When the defendant didn’t produce those documents, the judge ruled for an adverse inference sanction, stating, “Defendant’s company policy requires Documents to be uploaded—and presumably, preserved—on their online application, Basecamp… Defendant has offered no explanation as to why these documents were removed from Basecamp and cannot be located. Therefore, Defendant’s access and control over the Documents support its high responsibility in their non-production.”
Why Modern Collection Methods are Needed for SaaS Applications
As SaaS application data continues to be requested more and more during litigation, better collection tools will be needed. The status quo of using screenshots along with rudimentary exports is not scalable, nor does it provide the highest standard of accuracy required by the Federal Rules of Evidence. Likewise, as indicated by Ace Am. Ins. v. First Call, defensible preservation of SaaS application data is mandatory to avoid data spoliation sanctions.
This is why modern website and SaaS data ediscovery tools – which not only capture the text but also the interface as well as metadata – are needed. Not only do they provide the highest level of data preservation and collection for these new data sources, they also future-proof an enterprise’s ediscovery workflow by capturing the data flexibly as new data sources are added or removed from a company’s tech stack.
SaaS applications are here to stay, and they will continue to appear in case law during discovery. That’s why it’s important for large enterprises with vast amounts of data and multiple active matters to consider how that data will be preserved and collected before litigation, instead of waiting until a request to produce has been levied, and your legal team is left to figure things out on the fly.
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