eDiscovery Daily Blog

• July 16, 2024

In the ever-evolving world of eDiscovery, the types of data we collect, process, and review have expanded far beyond traditional documents. With the proliferation of short messages, geolocation data, social media posts, financial transactions, and structured databases, traditional document-centric approaches are proving inadequate. This shift necessitates a reevaluation of how we handle data throughout the Electronic Discovery Reference Model (EDRM) to avoid the pitfalls of linear review workflows that are both expensive and tedious.

Embracing Native Review Applications

In the early days of eDiscovery, converting spreadsheets to .TIF or .PDF formats made them difficult to review, as they obscured formulas and data analysis capabilities. Over time, review applications evolved to support native spreadsheet formats, improving efficiency and accuracy. This same approach is now critical for “modern data” such as JSON files from Slack or Facebook, time-keeping systems, financial data, and geolocation information. Processing and parsing this data for ingestion into document review platforms can retain context, facilitate cross-platform communication analysis, and significantly reduce review costs.

Challenges with Document Conversion

Converting modern communications data into documents poses significant challenges. For example, screenshots of text messages or chat conversations, while common, can be cumbersome and costly at scale. Such conversions often strip away context and lead to fragmented reviews, where each message is examined in isolation. This method is not only inefficient but also prone to missing crucial aspects of communication patterns.

Consider a scenario where a custodian starts a conversation via email, switches to Slack, continues with text messaging, and concludes with a phone call. In a traditional document review platform, piecing together this conversation’s context is difficult. By contrast, a native review application can present these communications chronologically, providing a seamless and comprehensive review experience.

Streamlining Review Workflows

Modern review platforms allow for more efficient tagging and categorization of messages within threaded conversations. Relevant, non-relevant, confidential, and privileged messages can be easily identified and isolated, reducing the need to convert the entire corpus of data into documents. This approach not only accelerates the review process but also minimizes costs and enhances accuracy.

Leveraging Advanced Technologies

As Erin Perczak, Co-Founder of Perin Discovery, notes, the inclusion of chat communications in discovery requests has become the norm. This shift underscores the need for tools capable of integrating modern communications with standard discovery formats. Advanced eDiscovery platforms can now handle a diverse array of data types, from emails and loose files to chat communications and beyond.

Expanding the Evidence Spectrum

With the right technology, eDiscovery teams can layer additional data types—such as geolocation, social media activity, user activities, and financial transactions—into their reviews. This capability enables a comprehensive narrative that weaves together various data points into a coherent timeline. For instance, consider an investigation involving an employee suspected of stealing data: text messages discussing the theft, geolocation data showing movements, and financial transactions indicating illicit activity can all be combined to tell a compelling story.

Telling the Whole Story

In cases requiring the collection and production of more than just corporate documents and emails, incorporating modern communications is crucial. Business-related conversations now frequently span multiple platforms, from email to chat applications like Microsoft Teams or Slack, and even text messages. Building a fluid timeline of these conversations enhances case strategy and provides a fuller understanding of the evidence.

Conclusion

Modern data types are reshaping eDiscovery workflows, demanding innovative approaches to data analysis and review. By adopting native review applications and leveraging advanced technologies, legal teams can efficiently handle the complexities of

modern communications, reduce costs, and improve the accuracy and comprehensiveness of their reviews. Embracing these changes is essential for staying ahead in the dynamic landscape of eDiscovery.

You can also download our complimentary guide to learn how to benefit from eDiscovery technology to accelerate finding key evidence in texts and chat data.

Find out more about how CloudNine can help you tackle newer data forms with our cloud-based eDiscovery solution, CloudNine Review, and set a time to meet with us.