Bill Overview
Title: Federal Human Capital Transparency Act
Description: This bill directs the Office of Personnel Management (OPM) to annually collect data relating to the federal workforce and post it on its website. Specifically, OPM must collect information on the total number of persons employed directly by each agency, the total number of prime contractor and subcontractor employees issued credentials allowing access to agency property or computer systems, the total number of employees of federal grant and cooperative agreement recipients who are issued such credentials, and a total count of the workforce of the agency.
Sponsors: Sen. Lankford, James [R-OK]
Target Audience
Population: Individuals employed directly or indirectly by the federal government (US)
Estimated Size: 5000000
- The bill affects individuals working directly for the federal government since their employment data will be collected and published.
- It includes prime contractor and subcontractor employees with access to federal agency properties or systems, thereby influencing them indirectly by having their data reported.
- Employees of federal grant and cooperative agreement recipients are also included in the data collection process as their numbers will be reported.
- The transparency and publication of this data could affect how these groups are perceived in terms of job security and employment statistics.
Reasoning
- The policy directly targets around 5 million individuals, including federal employees, contractors, and recipients of federal grants with credentials.
- The budget constraint suggests that while data will be collected and published, individual awareness or direct experience of this publication may vary.
- Since the policy focuses on transparency, it might not have a direct monetary or day-to-day job impact on these individuals' lives, but it might influence perceptions of job security or stability through visibility of employment numbers.
- A range of commonness scores will reflect how typical these experiences and impacts are among the target group.
Simulated Interviews
federal employee (Washington, D.C.)
Age: 35 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 5.0 years
Commonness: 15/20
Statement of Opinion:
- I think this policy is useful for understanding government employment trends.
- It may help in improving transparency, but I'm concerned about privacy.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 7 | 7 |
| Year 3 | 7 | 7 |
| Year 5 | 7 | 7 |
| Year 10 | 7 | 6 |
| Year 20 | 6 | 5 |
subcontractor employee (Texas)
Age: 28 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 2.0 years
Commonness: 10/20
Statement of Opinion:
- This policy doesn't seem to affect my job directly, but I'm curious how our subcontracting numbers being public will affect contracts.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 6 | 6 |
| Year 3 | 6 | 6 |
| Year 5 | 6 | 5 |
| Year 10 | 5 | 5 |
| Year 20 | 5 | 4 |
federal grant recipient employee (California)
Age: 42 | Gender: female
Wellbeing Before Policy: 8
Duration of Impact: 3.0 years
Commonness: 12/20
Statement of Opinion:
- Publishing employment data is neutral to me, but could affect the university's position and future grants.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 8 | 8 |
| Year 5 | 8 | 7 |
| Year 10 | 7 | 6 |
| Year 20 | 6 | 5 |
prime contractor (New York)
Age: 50 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 10.0 years
Commonness: 8/20
Statement of Opinion:
- I welcome the transparency, but this might pressure us to retain or optimize workforce more visibly.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 5 |
| Year 2 | 6 | 5 |
| Year 3 | 6 | 5 |
| Year 5 | 6 | 5 |
| Year 10 | 5 | 4 |
| Year 20 | 5 | 4 |
federal contractor (Nevada)
Age: 29 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 4.0 years
Commonness: 11/20
Statement of Opinion:
- I hope transparency brings more opportunities for contractors like us.
- Data being public might affect competitiveness.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 6 | 5 |
| Year 20 | 5 | 4 |
federal employee (Virginia)
Age: 39 | Gender: male
Wellbeing Before Policy: 8
Duration of Impact: 0.0 years
Commonness: 18/20
Statement of Opinion:
- It won't impact my role much, but it adds an extra layer of accountability for agencies.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 8 | 8 |
| Year 5 | 8 | 7 |
| Year 10 | 8 | 7 |
| Year 20 | 7 | 6 |
government contractor (Georgia)
Age: 55 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 5.0 years
Commonness: 13/20
Statement of Opinion:
- It's good for clients to be aware of our workforce size, could bolster trust in federal contracts.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 7 | 7 |
| Year 3 | 7 | 7 |
| Year 5 | 7 | 6 |
| Year 10 | 7 | 6 |
| Year 20 | 6 | 5 |
federal grant recipient employee (Maryland)
Age: 31 | Gender: other
Wellbeing Before Policy: 6
Duration of Impact: 6.0 years
Commonness: 9/20
Statement of Opinion:
- The data being out there makes me wonder about changes in grant allotment based on workforce numbers.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 6 | 6 |
| Year 3 | 6 | 5 |
| Year 5 | 6 | 5 |
| Year 10 | 5 | 5 |
| Year 20 | 5 | 4 |
federal employee (Arizona)
Age: 44 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 3.0 years
Commonness: 14/20
Statement of Opinion:
- It might improve the competitiveness of contractor bids, which could affect project execution timelines.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 7 | 7 |
| Year 3 | 7 | 7 |
| Year 5 | 7 | 7 |
| Year 10 | 7 | 6 |
| Year 20 | 7 | 6 |
government contractor (Colorado)
Age: 60 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 7.0 years
Commonness: 12/20
Statement of Opinion:
- I find the increase in public data useful for aligning our own transparency models.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 5 |
| Year 2 | 5 | 5 |
| Year 3 | 5 | 4 |
| Year 5 | 5 | 4 |
| Year 10 | 5 | 4 |
| Year 20 | 4 | 3 |
Cost Estimates
Year 1: $15000000 (Low: $12000000, High: $18000000)
Year 2: $12000000 (Low: $10000000, High: $14000000)
Year 3: $12000000 (Low: $10000000, High: $14000000)
Year 5: $12000000 (Low: $10000000, High: $14000000)
Year 10: $12000000 (Low: $10000000, High: $14000000)
Year 100: $12000000 (Low: $10000000, High: $14000000)
Key Considerations
- The bill introduces additional administrative workload for the Office of Personnel Management, potentially requiring more staff or reallocation of existing resources.
- Maintaining data privacy and security will be crucial given the sensitivity of employment data in federal operations.
- Initial costs for system setup could be higher due to technology infrastructure development requirements.