Policy Impact Analysis - 117/S/5028

Bill Overview

Title: Prioritizing Evidence for Workforce Development Act

Description: This bill requires state workforce development plans to describe how the state will prioritize funding evidence-based programs that demonstrate positive outcomes for their target populations.

Sponsors: Sen. Braun, Mike [R-IN]

Target Audience

Population: Individuals participating in workforce development programs

Estimated Size: 15000000

Reasoning

Simulated Interviews

Unemployed (Rural Ohio)

Age: 34 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 5.0 years

Commonness: 8/20

Statement of Opinion:

  • I'm hoping this program can improve my job prospects, but I am skeptical given past experiences with similar programs.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 5
Year 2 7 5
Year 3 7 5
Year 5 8 5
Year 10 8 4
Year 20 7 3

Retail Worker (Urban California)

Age: 28 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 3.0 years

Commonness: 10/20

Statement of Opinion:

  • This could be a great opportunity to get some support in shifting careers. I hope it's not just another box-checking exercise.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 8 6
Year 3 8 5
Year 5 8 5
Year 10 7 4
Year 20 6 4

Manufacturing Technician (Suburban Texas)

Age: 45 | Gender: other

Wellbeing Before Policy: 6

Duration of Impact: 2.0 years

Commonness: 6/20

Statement of Opinion:

  • I'd like to see these changes make a difference in my career. Programs have been hit or miss in the past.

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 5
Year 10 6 5
Year 20 6 4

Entry-level IT Support (New York City)

Age: 22 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 4.0 years

Commonness: 12/20

Statement of Opinion:

  • I need real, tangible results from these programs, not just 'fluff' support. It could help a lot if done right.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 7 6
Year 3 8 5
Year 5 8 5
Year 10 7 4
Year 20 6 3

Construction Laborer (Atlanta, Georgia)

Age: 52 | Gender: male

Wellbeing Before Policy: 4

Duration of Impact: 5.0 years

Commonness: 8/20

Statement of Opinion:

  • Access to these programs could potentially change things for me, but I've been let down before.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 4
Year 2 6 4
Year 3 6 4
Year 5 7 3
Year 10 7 3
Year 20 6 2

Administrative Assistant (Chicago, Illinois)

Age: 39 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 6.0 years

Commonness: 7/20

Statement of Opinion:

  • These updates might help diversify my skills. I hope they offer real support and guidance.

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 9 4
Year 10 8 4
Year 20 7 3

Truck Driver (Phoenix, Arizona)

Age: 41 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 3.0 years

Commonness: 9/20

Statement of Opinion:

  • I would like these programs to offer more specific, practical training. It must connect directly with job opportunities.

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 5
Year 10 6 5
Year 20 6 4

Part-time Retail Associate (Detroit, Michigan)

Age: 30 | Gender: female

Wellbeing Before Policy: 4

Duration of Impact: 5.0 years

Commonness: 11/20

Statement of Opinion:

  • I need these programs to actually connect me with jobs, not just prepare me theoretically.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 4
Year 2 6 4
Year 3 7 5
Year 5 8 5
Year 10 8 4
Year 20 7 3

Warehouse Supervisor (Seattle, Washington)

Age: 58 | Gender: male

Wellbeing Before Policy: 5

Duration of Impact: 2.0 years

Commonness: 5/20

Statement of Opinion:

  • The updates might help me maintain employability, but I'm not the main target.

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 4
Year 10 5 4
Year 20 5 3

Homemaker (Rural West Virginia)

Age: 33 | Gender: female

Wellbeing Before Policy: 4

Duration of Impact: 5.0 years

Commonness: 4/20

Statement of Opinion:

  • Access to reliable job programs could help me find a stable job. It’s crucial to have support in rural areas.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 4
Year 2 6 4
Year 3 6 4
Year 5 7 3
Year 10 7 3
Year 20 6 2

Cost Estimates

Year 1: $25000000 (Low: $20000000, High: $30000000)

Year 2: $25000000 (Low: $20000000, High: $30000000)

Year 3: $25000000 (Low: $20000000, High: $30000000)

Year 5: $25000000 (Low: $20000000, High: $30000000)

Year 10: $25000000 (Low: $20000000, High: $30000000)

Year 100: $25000000 (Low: $20000000, High: $30000000)

Key Considerations