DOL Wage & Hour Enforcement Scraper

Overview

This Actor extracts Department of Labor (DOL) Wage & Hour Division (WHD) enforcement case data from the official WHISARD (Wage and Hour Investigative Support and Reporting Database). Access 300,000+ wage & hour violations, employer compliance records, back wages recoveries, and penalty assessments across all U.S. states and industries.

Perfect for:

• PE/VC due diligence teams evaluating employer compliance risks
• ESG (Environmental, Social, Governance) researchers studying labor practices
• Compliance consultants monitoring industry-specific violations
• Legal teams tracking regulatory enforcement trends
• HR professionals benchmarking company compliance against peers
• Policy researchers analyzing wage theft patterns by state/industry

Key Features

• 300,000+ Enforcement Cases: Complete historical WHISARD database
• Multi-Filter Search: State, employer name, industry, violation type, monetary recovery, date range
• Rich Data Fields: Violation details, back wages, penalties, employee counts, status, prosecution outcomes
• High-Value B2B Data: Single case record worth $100-500 to compliance/PE teams
• Fresh Data: Updated as DOL publishes new enforcement actions
• No Auth Required: Access public WHISARD data without credentials
• Bulk Download Capable: Export 100,000+ records in single run

Sample Data Fields

Each enforcement record includes:

Field	Example	Business Value
Case ID	WHD-2024-001234	Unique case identifier
Employer	ABC Manufacturing Corp	Compliance risk assessment
Violation Date	2024-03-15	Timeline of enforcement
Violation Type	Minimum Wage, Overtime	Category-specific risk
Employees Affected	47	Scope of violation
Back Wages	$145,000	Financial impact & recovery
Penalties	$32,500	Enforcement severity
Total Recovery	$177,500	Total monetary outcome
Status	Resolved	Case lifecycle
Investigation Type	Complaint Investigation	Enforcement source
State	TX	Geographic filtering
Industry	Hospitality	Sector-specific risk

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How to Use This Actor

Step 1: Open the Actor in Apify Console

Navigate to this Actor in the Apify Store and click Try for Free or Activate.

Step 2: Configure Search Filters (Optional)

The input form supports the following filter options:

State Filter

• Enter a two-letter state abbreviation (e.g., TX, CA, NY, FL)
• Leave empty to search all 50 states
• Default: All states

Employer Name Filter

• Enter a full or partial company name (e.g., McDonald's, Walmart, Amazon)
• Supports case-insensitive partial matching
• Leave empty to search all employers
• Default: All employers

Industry Filter

• Enter an industry description (e.g., Hospitality, Healthcare, Agriculture) or NAICS code (e.g., 72 for accommodation & food service)
• Supports partial matching
• Leave empty to search all industries
• Default: All industries

Minimum Back Wages Filter

• Enter a dollar amount (e.g., 10000, 50000, 100000)
• Returns only cases with back wages at or above this threshold
• Useful for identifying high-severity violations
• Default: 0 (no minimum)

Date Range Filters

• Violation Date From: Enter as YYYY-MM-DD (e.g., 2023-01-01)
• Violation Date To: Enter as YYYY-MM-DD (e.g., 2024-12-31)
• Leave empty for no date boundary
• Default: All dates

Max Results

• Enter the number of records you want to retrieve (1 to 300,000)
• Higher limits cost more Apify compute credits
• Start small (100-500) to test your filters
• Default: 100

Step 3: Run the Actor

Click Start to begin. The Actor will:

1. Validate your filter inputs
2. Query the DOL WHISARD database via Socrata API
3. Download and structure all matching records
4. Save results to the default dataset

Typical run times:

• 100 records: ~30 seconds
• 1,000 records: ~2 minutes
• 10,000 records: ~10-15 minutes
• 50,000+ records: 30+ minutes (depends on Apify compute plan)

Step 4: Download Results

Once the run completes, click the Dataset tab to:

• View results in table format
• Download as CSV for Excel/Sheets
• Download as JSON for database import
• Export to other tools via Apify integrations (Google Sheets, Slack, email, webhook, etc.)

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Example Use Cases

Case 1: PE Due Diligence on Target Company

Task: You're evaluating a hospitality company (1,200 locations) for acquisition. You need to assess wage & hour compliance risk.

Inputs:

• State: (leave empty for all)
• Employer: Restaurant Group Name
• Industry: 72 (Accommodation & Food Service)
• Min Back Wages: 50000 (focus on material violations)
• Date From: 2022-01-01 (last 2 years)
• Max Results: 1000

Output: All wage violations affecting the company since 2022. You can now:

• Calculate total compliance costs (back wages + penalties)
• Identify geographic hotspots (states with most violations)
• Assess trend (improving or worsening?)
• Factor remediation costs into valuation

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Case 2: ESG Scorecard - Industry Benchmarking

Task: Your ESG team is building a labor compliance scorecard for your SaaS portfolio companies. Benchmark tech service providers against industry average.

Inputs:

• State: (leave empty)
• Employer: (leave empty)
• Industry: 81 (Administrative & Support Services) OR 62 (Health Care & Social Assistance)
• Min Back Wages: 0 (count all violations, not just large ones)
• Date From: 2023-01-01
• Max Results: 5000

Output: Industry-wide violation data. You can now:

• Calculate violation rate per state
• Identify common violation types in the sector
• Benchmark your portfolio company's record against peers
• Create ESG disclosure metrics

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Case 3: State Labor Board Comparison

Task: Your nonprofit is researching which states have the most aggressive wage enforcement. Build a map of state enforcement intensity.

Inputs:

• Run one query per state with Max Results = 5000
• Aggregate results by state

Output: Enforcement statistics by state. You can now:

• Rank states by total violations, back wages recovered, penalties assessed
• Analyze labor protection effectiveness
• Create policy recommendation charts

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Data Fields Reference

Case Identification

• caseId: Unique case identifier (e.g., "WHD-2024-001234")
• violationDate: Date violation was identified or investigated

Employer Information

• employerName: Legal name of employer
• address, city, state, zipCode: Employer physical location
• county: County of violation
• businessType: Type of business (corp, LLC, sole proprietor, etc.)

Violation Details

• violationType: Classification of violation (Minimum Wage, Overtime, FLSA, etc.)
• violationDescription: Detailed description of violation
• numberOfEmployeesAffected: Count of affected employees
• industry: Industry description
• naicsCode: North American Industry Classification System code

Financial Impact

• backWages: Amount of back pay owed to employees
• penalties: Civil penalties/fines assessed
• compensatory: Compensatory damages awarded
• totalMonetaryRecovery: Sum of all monetary outcomes

Enforcement Status & Outcomes

• status: Current status (Resolved, Pending, Settled, etc.)
• investigationType: Type of investigation (Complaint, Wage MD, etc.)
• resolutionDate: Date case was resolved
• prosecutionCode: Code indicating if criminal prosecution occurred
• prosecutionResult: Result of criminal prosecution (if applicable)

Administrative Fields

• recordCreatedDate: Date record was added to WHISARD
• remarks: Additional notes or comments
• dnDebarred: Whether employer was debarred from federal contracts
• namedEspionage: Flag for retaliation/espionage allegations

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Pricing & Cost Estimates

This Actor uses a per-result pricing model plus Apify compute costs.

Actor Start Event

• Fixed cost per run: $0.00005 (negligible)
• Applies once, regardless of results

Per-Result Pricing

• $0.002 per enforcement record returned
• Example: 1,000 records = $2.00 in Actor costs

Apify Compute Costs

• Runs on Apify's free compute tier for most searches
• 100 records: 0.5 compute units ($0.03)
• 1,000 records: 3 compute units ($0.15)
• 10,000 records: 25 compute units ($1.25)
• 100,000 records: 200+ compute units ($10+)

Total Cost Example

Fetching 5,000 DOL enforcement records:

• Actor cost: 5,000 × $0.002 = $10.00
• Compute cost: ~15 units = $0.75
• Total: ~$10.75

Pro tip: Start with small runs (100-500 records) to test your filters before running 10,000+.

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Input/Output Examples

Example Input (JSON)

{
  "state": "CA",
  "employer": "ABC Manufacturing",
  "industry": "31",
  "minBackWages": 10000,
  "dateFrom": "2023-01-01",
  "dateTo": "2024-12-31",
  "maxResults": 100
}

Example Output (First 2 Records)

[
  {
    "caseId": "WHD-2024-001823",
    "violationDate": "2024-03-15",
    "year": 2024,
    "employerName": "ABC Manufacturing Corp",
    "address": "123 Industrial Blvd",
    "city": "Los Angeles",
    "state": "CA",
    "zipCode": "90001",
    "county": "Los Angeles",
    "industry": "Computer & Electronic Products Manufacturing",
    "naicsCode": "3341",
    "businessType": "Private Corporation",
    "violationType": "Minimum Wage, Overtime",
    "violationDescription": "Failure to pay minimum wage and overtime compensation",
    "numberOfEmployeesAffected": 47,
    "backWages": 145000,
    "penalties": 32500,
    "compensatory": 15000,
    "totalMonetaryRecovery": 192500,
    "status": "Resolved",
    "investigationType": "Wage & Hour Investigation",
    "resolutionDate": "2024-06-20",
    "namedEspionage": false,
    "dnDebarred": true,
    "remarks": "Settlement reached; employer implemented new timekeeping system",
    "prosecutionCode": null,
    "prosecutionResult": null,
    "recordCreatedDate": "2024-03-20"
  },
  {
    "caseId": "WHD-2024-001824",
    "violationDate": "2024-02-28",
    "year": 2024,
    "employerName": "XYZ Hospitality Group",
    "address": "456 Main St",
    "city": "San Francisco",
    "state": "CA",
    "zipCode": "94102",
    "county": "San Francisco",
    "industry": "Accommodation & Food Service",
    "naicsCode": "72",
    "businessType": "Private Corporation",
    "violationType": "Tip Credit Misappropriation",
    "violationDescription": "Illegal deduction of tips from employee wages",
    "numberOfEmployeesAffected": 23,
    "backWages": 67500,
    "penalties": 18000,
    "compensatory": null,
    "totalMonetaryRecovery": 85500,
    "status": "Settled",
    "investigationType": "Complaint Investigation",
    "resolutionDate": "2024-05-10",
    "namedEspionage": false,
    "dnDebarred": false,
    "remarks": "Trained management on tip laws; created new policy",
    "prosecutionCode": null,
    "prosecutionResult": null,
    "recordCreatedDate": "2024-03-05"
  }
]

---

Troubleshooting

"No results found"

• Verify filter parameters are spelled correctly
• Try broadening filters (remove state, employer, or industry)
• Check that your date range actually contains data
• Increase maxResults to see if data exists upstream

"API returned status 429: Rate Limited"

• The Actor will automatically retry with exponential backoff
• If error persists, try fetching fewer results in smaller batches
• Wait 5-10 minutes before retrying

"Request failed / timeout"

• DOL's API may be temporarily unavailable
• Try running again in a few minutes
• Contact Apify support if issue persists

Results seem outdated

• WHISARD is updated regularly but may have a 1-2 week lag
• The most recent violations appear under "New cases" separately
• Check recordCreatedDate to see when entries were added

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Related Actors & Data Sources

Looking for related labor/compliance data?

• OSHA Violations Scraper — Occupational Safety & Health Administration enforcement (workplace injuries, fatalities)
• EEO-1 Employer Statistics — Equal Employment Opportunity Commission diversity data
• WARN Act Notices — Mass layoffs and plant closures (60-day advance notices)
• State Labor Board Directories — Individual state labor agency data (varies by state)
• Employment Standards Database — Minimum wage and overtime rules by state

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Legal Disclaimer & Data Usage

This Actor extracts publicly available data from the U.S. Department of Labor WHISARD database. All data is:

• Published by a U.S. government agency
• Free to access and distribute
• Not subject to copyright restrictions (public domain)
• Acceptable for commercial use

Your responsibilities when using this data:

1. Accuracy: DOL data is as accurate as source records. Verify critical information independently.
2. Context: Individual violations don't necessarily reflect current employer practices or legal liability.
3. Privacy: While WHISARD is public, be mindful of sensitive business information when sharing results.
4. Compliance: When using data for employment decisions (hiring, contracting), ensure compliance with Fair Credit Reporting Act (FCRA) and local employment laws.
5. Attribution: While not legally required, crediting DOL WHISARD as the source is appreciated.

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FAQ

Q: How often is this data updated? A: WHISARD reflects new enforcement actions as DOL publishes them, typically within 1-2 weeks of case closure. The Actor queries live data.

Q: Can I filter by specific violation type? A: The current version filters by industry and monetary amounts. Violation type filtering is available via the violationType field in exported results.

Q: What's the oldest record available? A: WHISARD contains historical enforcement data dating back decades. Start date varies by record type.

Q: Can I download all 300,000+ records at once? A: Yes, but it will cost significant Apify credits and take 30+ minutes. Recommended: Download in batches by state or year range.

Q: Is this data confidential? A: No. WHISARD is public record. However, some sensitive employee information may be redacted in certain cases.

Q: Can I use this for hiring/employment decisions? A: Yes, but ensure compliance with Fair Credit Reporting Act (FCRA) and state employment laws. DOL violations reflect employer compliance, not employee qualifications.

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Support & Feedback

Issues or questions?

• Check the Apify Community Forum
• Review the DOL WHISARD documentation: https://www.dol.gov/agencies/whd/data
• Contact Apify support: support@apify.com

Suggestions for improvements?

• Email: seatsignal@apify.com
• We welcome feedback on additional filters, fields, or use cases

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Version History

v0.1 (Initial Release)

• WHISARD database extraction
• State, employer, industry, date range, and monetary filters
• 25+ data fields per record
• Support for up to 300,000 records per run