Leveraging Structured Data as a Competitive Advantage Leads to Class Decertification

Facts at a Glance

California wage and hour class action involving over 11,000 truck drivers

Collection and analysis of over 13 TB of data and 75 billion records from 9 different systems
Successful class decertification ruling six weeks before trial, saving company millions

CHALLENGE

Assist a client with a class action regarding unfair compensation practices.

Our client, a national long-hauling trucking company, was facing a major California wage and hour class action brought forth by its drivers alleging unfair compensation practices including lack of meal and rest breaks.

iDS was tasked with:

Providing consulting services to assess the validity of plaintiffs’ unfair wage and hour allegations
Drafting an expert report and relation declarations in support of our findings and conclusions
Delivering numerous rounds of data productions based on court and plaintiff requests

Solution

iDS was engaged to retrieve data to back up claims of non-work activity.

iDS was chosen based on our relationship with the client and our deep experience in assisting other clients with similar issues. A project plan was drawn up to include:

Understanding plaintiffs’ claims and identifying the relevant data sources, including onboard computers, payroll records, driver logs, and compensation plans
Collecting over 13 TB of data spanning 6,800 tables and 75 billion records from 9 different systems
Ingesting this data into the xIOT® platform, allowing our team to efficiently analyze, enrich, and visualize fact patterns across disparate data sources

Result

iDS demonstrated variations in compensation plans, leading to a class decertification ruling.

Our data driven analysis successfully demonstrated wide variations in class members compensation plans, ultimately leading to a class decertification ruling just six weeks before trial. In addition, we delivered 12 rounds of data productions, ultimately comprising over 900 million records across 1,500 files.