How to Simplify Handling Short-Message Format Data in eDiscovery

Just a decade ago, short-message format data in eDiscovery was predominantly cell phone data that was –  as it still is today to an extent — a challenge to collect. The challenge has become easier with both in-person and remote collection options, but now we have new forms of short-message data showing up in eDiscovery like that from Microsoft Teams conversations, Slack messages, WhatsApp messages and more. These types of short-message data formats also require collection and processing just like cell phone data from a decade or more ago. What has not evolved as quickly is what you do with all this data after you have collected it, and how processes are applied to reduce the volume of data to save time and money on every case.

How Collection Has Changed

Custodians utilize their mobile device for personal purposes, so there is a lot of personal information on them like financial data, health data, family pictures, and more. Early on, custodians pushed back because collecting data involved physically taking the entire phone and collecting all the unfiltered data.

Some of the difficulties early on included inaccessible custodians. How do you collect data if the custodian lived in the mountains or somewhere else without reliable internet? There were also limitations on how many gigabytes could be collected. Today, remote collections using specialized technology like that from companies like Downstreem are the norm, no matter where custodians are located. The volume of gigabytes no longer matters, and modern technology — like their MobileStreem tool — allows for filtering data on site so that only relevant data is collected, and personal information is spared.

Modern Post-Collection Workflows

Most short-message format data today resides in the cloud, negating any access challenges of the past.  The newer challenge to eDiscovery as short-message format data has evolved is how to collect and keep all data associated with each custodian together, such as conversations, messages, pictures, videos, voicemails, call logs and attachments. Another challenge lies in determining from this massive volume of data what is relevant to the matter and how it might impact the case early on. In addition, more cases involve not just data from mobile devices but also from Microsoft Teams, Slack, Bloomberg Chat and more.

Collection processes vary, depending on how the platform operates, how the data originates and where it sits. For most platforms, however, attachments to messages reside in the cloud and must be identified and downloaded, then attached to the record as a child document so they come as a package in Relativity. Many workflows do not automate this step of downloading attachments, giving users an incomplete set of documents. When evaluating eDiscovery experts, ask whether their workflows automate this process. This unique point of differentiation can help better manage cases, control costs, and increase productivity.

Robust tools exist today that allow for ECA or analysis of data coming from mobile devices and short-message format platforms. These tools allow users to get a handle on the volume and types of data, sort through it to get the relevant information, and then export it to a review platform like Relativity. Users can sort data from multiple devices associated with an event, organize data like phone numbers, email addresses, Twitter handles, Snapchat names and more by custodian, and even apply facial recognition to organize all photos and videos by custodian. These tools allow for word clouds to determine important search terms from conversations and search by images like emojis. These ECA tools specifically designed for short-message format data give legal professionals valuable information early in their case, allowing them to make informed decisions about the matter.

Let us help you increase productivity when your next case involves short-message format data. Contact Gulfstream today.