Extract from Jim Gill’s article “Trends for Collaboration Data Ediscovery in 2023”
It’s that time of year again when people are pulling out their crystal balls and doing their best to predict the future of what we’ll see in the ediscovery industry in 2023. I mean who doesn’t want to know what to look out for down the road? So in that spirit, here are some things Hanzo has been paying attention to as we move into a new year.
Data Sources Outside the Norm
New data sources should probably make the list every year, but the shift that is taking place now is slightly different than we’ve seen in the past. New messaging platforms like Slack and Teams have been the talk of the town when it comes to new data over the past few years, and while there are still many ediscovery challenges around that type of data, they are no longer the new kids on the block and have become a fairly regular part of the ediscovery workflow.
What has emerged as a new challenge is collecting data from other SaaS collaboration applications like Jira, Confluence, Asana, and Salesforce. Reports have shown that an average enterprise might be using up to 200 different SaaS applications at one time. And with a 60% yearly churn rate, the number of applications that are being adopted and then replaced by something new creates challenges when it comes to understanding your organization’s data landscape.
But more than that is the challenge of collecting data and metadata from these sources. There is often an export function of some sort, but it doesn’t capture the interface which itself often holds data and context to understanding data. Screenshots have been used to supplement these raw data exports, but they don’t always effectively fit the rules for best evidence.