The Simplified
E-⁠Discovery Case Law Library
A collection of simple, easy to understand analyses and resources on e-⁠discovery case law.
Case shelved under Proportionality

What Constitutes an Undue Burden in E-Discovery

Meredith et. al. v. United Collection Bureau, Inc.
N.D. Ohio April 13, 2017
Why This Case is Important

If evidence is proven to be relevant and necessary for litigation, then parties may be compelled to take extensive measures to produce requested data.

Overview:

In this class action suit, the Plaintiff claimed that the Defendant, a debt collector, used autodialed, prerecorded calls using third party skip-trace services, which resulted in numerous wrong number calls to cell phones, which is a violation of the Telephone Consumer Protection Act. According to the complaint, the Defendant has a practice of placing calls to cell phones regarding the collection of a debt without the prior consent of the called parties.

In an earlier discovery dispute, the court ruled on the Plaintiff’s motion to compel, which raised numerous shortcomings in the Defendant’s responses to discovery request. However, the Plaintiff sought extremely detailed information about calls made by the Defendant, which would require them to do a manual review of more than 278,000 accounts.

Ruling:
  • Manual Review Unduly Burdensome: The court rejected the plaintiff’s motion to compel, because it was unduly burdensome to conduct a manual review of the large volume of data.
  • Technology Solution Requested: As an alternative, the plaintiff requested that the defendant write a computer program to find responsive data. The Defendant refused, and subsequently the plaintiff filed a motion to compel specified data.
  • Data Relevant for Litigation: The court granted the plaintiff’s motion based on their justification that the requested data was relevant and necessary for litigation.
Download Case Law PDF

Download the PDF version of Meredith et. al. v. United Collection Burau, Inc. case analysis here.

relevant resource
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Preserving/Collecting New Data Types: An E-Discovery Recipe
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