As Cimplifi discusses, the rise of messaging platforms has ushered in a new era of conversational ESI, making defining a “conversation” important.

In their post titled (wait for it!) Taming Modern Data Challenges: Defining a “Conversation” (available here), Cimplifi discusses how as long as there has been a discipline called “eDiscovery”, there has been conversational data. Historically, that has been most common in emails that reflect conversations between multiple parties. However, unlike email, modern chat and messaging tools result in ESI that is fluid, fragmented, and contextual. These platforms are designed for real-time, informal collaboration.

This conversational data reflects how business gets done today – decisions are often made “on the fly”, questions are asked and answered in rapid succession, and actions are coordinated across distributed teams. From a discovery standpoint, this data can be highly relevant, but it often defies the traditional assumptions and workflows built around document-centric discovery.

There are several ways conversational ESI stands apart from its more conventional counterparts. Here’s one of them:

Volume and Redundancy: High-frequency, low-substance messages (e.g., “OK”, “Got it”, or even a “thumbs-up” emoji) create noise in review. Conversely, meaningful decisions may occur in fleeting exchanges that might be easily overlooked if review is forced into a document paradigm, based on arbitrary time-based “chunks” like 24 hours per “document”.

So, what are the other ways in which conversational ESI is different? What are multi-channel conversations? And what discovery strategies should you apply to conversational data? Find out here, it’s just one click! The conversation is just getting started! 😉

So, what do you think? How is your organization taming modern data challenges in eDiscovery? Please share any comments you might have or if you’d like to know more about a particular topic.

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