Bill Overview
Title: Facilitating Federal Employee Reskilling Act
Description: This bill establishes certain standards for federal reskilling programs. The bill defines federal reskilling program as a program established by an executive agency, or the Office of Personnel Management, to provide employees with technical skills or expertise that would qualify them to serve in different positions. The bill requires such programs to use merit-based principles with respect to employees' participation. Participating employees must also be given the option to return to their original positions, particularly if they are unsuccessful in their new positions. Additionally, employees are entitled to the same grades in their new positions as in their original positions; new positions must also utilize employees' newly acquired skills or expertise.
Sponsors: Sen. Sinema, Kyrsten [D-AZ]
Target Audience
Population: Federal employees
Estimated Size: 2000000
- According to the U.S. Office of Personnel Management, there are approximately 2.1 million civilian federal employees.
- Not all federal employees will participate in reskilling programs, as participation will depend on personal choice and eligibility criteria.
- The programs will be open to a wide range of employees across various federal agencies based on merit principles.
- Federal agencies have reskilling programs to help employees advance their careers, especially in technical areas.
Reasoning
- With a policy budget of $1.4 billion over 10 years, we need to distribute resources efficiently among around 2 million civilian federal employees.
- Not all federal employees will be impacted equally due to personal choice, eligibility criteria, and agency priorities.
- The policy aims to improve job satisfaction and adaptability by providing targeted reskilling opportunities, which could affect wellbeing positively for those who participate.
- Employees who are seeking to transition into technical or emerging fields are more likely to benefit from the policy.
- The ability to return to their original positions if unsuccessful in new roles provides a safety net, reducing potential anxiety associated with career transitions.
- The impact on non-participating employees should be neutral, maintaining baseline wellbeing scores.
Simulated Interviews
Federal HR Specialist (Washington, D.C.)
Age: 45 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 12/20
Statement of Opinion:
- This policy opens up great opportunities for career development in technical fields that interest me.
- As an HR specialist, I can help facilitate these reskilling programs and possibly transition into a data analytics role myself.
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 | 8 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 7 | 5 |
IT Support Specialist (Austin, TX)
Age: 34 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 20.0 years
Commonness: 10/20
Statement of Opinion:
- Reskilling programs with a focus on cybersecurity could help me escape my current career plateau.
- The ability to return to my current role provides excellent job security as I transition.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 7 | 5 |
| Year 3 | 8 | 5 |
| Year 5 | 8 | 5 |
| Year 10 | 9 | 5 |
| Year 20 | 8 | 5 |
Administrative Assistant (Boston, MA)
Age: 28 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 5.0 years
Commonness: 15/20
Statement of Opinion:
- The policy seems beneficial for those interested in technical careers, but I'm content with my current role.
- I'm not sure this policy directly affects me as I have little interest in switching fields.
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 | 6 | 7 |
| Year 20 | 6 | 6 |
Policy Analyst (Denver, CO)
Age: 50 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 10.0 years
Commonness: 9/20
Statement of Opinion:
- This policy gives me a chance to work on projects involving AI and machine learning, which I previously could not.
- However, balancing reskilling with my current workload might be challenging.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 5 |
| Year 2 | 6 | 5 |
| Year 3 | 7 | 5 |
| Year 5 | 7 | 5 |
| Year 10 | 8 | 5 |
| Year 20 | 7 | 4 |
Federal Registered Nurse (New York, NY)
Age: 39 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 15.0 years
Commonness: 11/20
Statement of Opinion:
- As healthcare increasingly integrates IT, learning these skills ensures I'm prepared for future roles.
- I'm excited about the reskilling opportunities, especially if it helps me diversify my career.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 6 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 7 | 5 |
Data Entry Clerk (San Francisco, CA)
Age: 29 | Gender: male
Wellbeing Before Policy: 4
Duration of Impact: 20.0 years
Commonness: 6/20
Statement of Opinion:
- This is a golden opportunity for me to shift toward data analysis with the new skills I’ll acquire.
- I hope there's sufficient budget allocable for training opportunities in my department.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 4 |
| Year 2 | 6 | 4 |
| Year 3 | 7 | 4 |
| Year 5 | 8 | 4 |
| Year 10 | 9 | 4 |
| Year 20 | 9 | 4 |
Compliance Officer (Chicago, IL)
Age: 41 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 1.0 years
Commonness: 13/20
Statement of Opinion:
- This policy seems more relevant to roles that need regular updates in technical skills, not so much to mine.
- I support it as a measure to modernize federal skills, even if my job isn't directly affected.
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 | 7 |
| Year 20 | 7 | 7 |
Field Officer (Seattle, WA)
Age: 42 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 10.0 years
Commonness: 8/20
Statement of Opinion:
- The potential to transition into project management using new skills is exciting.
- I hope the program can offer the depth of training necessary to transition effectively.
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 | 7 | 5 |
| Year 10 | 8 | 5 |
| Year 20 | 7 | 5 |
Supply Chain Coordinator (Miami, FL)
Age: 37 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 15.0 years
Commonness: 10/20
Statement of Opinion:
- I see the opportunity to enhance my knowledge base and incorporate technology to streamline operations.
- The policy encourages me to think about long-term career shifts.
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 | 8 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 7 | 5 |
Veterans Affairs Officer (Los Angeles, CA)
Age: 49 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 0.0 years
Commonness: 15/20
Statement of Opinion:
- I don't see this policy having a significant impact on me as I'm nearing retirement.
- It's good for younger colleagues, though I'm more focused on maintaining current services.
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 | 7 |
| Year 20 | 6 | 6 |
Cost Estimates
Year 1: $50000000 (Low: $40000000, High: $60000000)
Year 2: $75000000 (Low: $60000000, High: $90000000)
Year 3: $100000000 (Low: $80000000, High: $120000000)
Year 5: $150000000 (Low: $120000000, High: $180000000)
Year 10: $200000000 (Low: $160000000, High: $240000000)
Year 100: $500000000 (Low: $400000000, High: $600000000)
Key Considerations
- The implementation and success of the reskilling program largely depend on the participation and cooperation of federal agencies.
- Budget allocations for these programs would need consideration in the federal budgeting process, potentially affecting other programs.
- Reskilling can lead to higher employee satisfaction and reduce turnover, but also requires adequate tracking and assessment of the program's effectiveness.