US Layoffs — June 1997

The US labor market showed signs of rising strain as employers reported 10 WARN Act notices in June 1997, displacing an estimated 3,423 workers — signaling an acceleration from May. Filings came from 1 states and territories, with an average of 342 workers per notice.

10
Total Notices
3,423
Workers Affected
1
States Reporting
342
Avg per Notice
0
Closures

Top States by Workers Affected

StateNoticesWorkers
Ohio103,423

Ohio led the nation with 3,423 workers affected across 10 notices .

Industry Breakdown

IndustryNoticesWorkers
Manufacturing11,564
Healthcare194
Retail154

The Manufacturing sector topped the list of affected industries with 1,564 workers across 1 notice. Notably, Healthcare reported 94 workers.

Layoff Type Analysis

Layoff type data was not available for filings this month.

Largest Layoffs

CompanyLocationWorkersType
Ford-Lorain Assembly PlantLorain, Ohio1,564
Revco Corporate OfficeTwinsburg, Ohio1,000
Everready BatteryFremont, Ohio250
Strambaugh-ThompsonBoardman, Ohio179
Monarch Machine Tool CompanySidney, Ohio98
Aetna/US HealthcareMaumee, Ohio94
Miller-Holzwarth, IncSalem, Ohio65
Electra SoundParma, Ohio60
Futuro, IncMilford, Ohio59
Value City Dept. StoreSpringfield, Ohio54

The most significant filing came from Ford-Lorain Assembly Plant in Lorain, Ohio, reporting 1,564 affected workers. Revco Corporate Office followed with 1,000 workers.

Trend & Outlook

After a dip last month, layoff activity has ticked back up.

The numbers illustrate mounting pressure on the the nation labor market, with activity running above both recent and year-ago benchmarks. The Manufacturing sector warrants close attention heading into the next period.

This report covers all WARN Act filings with notice dates in June 1997. The Worker Adjustment and Retraining Notification Act requires employers with 100+ employees to provide 60-day advance notice of mass layoffs and plant closings. Data is sourced from official state filings and updated daily by WARN Firehose. Download the full dataset or explore state-by-state data.

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