Bill Overview
Title: Strengthening Support for American Manufacturing Act
Description: This bill requires the Department of Commerce to contract the National Academy of Public Administration to study and report on Commerce's manufacturing programs. The study must (1) include the statutory authority for the programs, and (2) assess proposals to consolidate the programs.
Sponsors: Sen. Peters, Gary C. [D-MI]
Target Audience
Population: People employed in global manufacturing industries
Estimated Size: 12800000
- Manufacturing directly involves people working in industries that produce goods.
- The bill calls for a study and report; immediate direct effects might be limited to policy makers, researchers, and industry leaders.
- In the longer term, any changes to manufacturing programs could affect workers in the manufacturing sector on a global scale.
- Manufacturing is a global activity, but the bill focuses on American manufacturing programs, so indirect effects on foreign trade partners may be considered.
Reasoning
- The policy primarily affects those involved in the manufacturing sector in the US, estimated at about 12.8 million people.
- Immediate effects of the policy might be limited as it is focused on a study and report by the Department of Commerce.
- Any changes following the study, such as consolidation of programs, might have both positive and negative effects on people employed in manufacturing.
- We should consider a range of stakeholders, including factory workers, policy analysts, industry leaders, and those indirectly linked to manufacturing like supply chain and logistics personnel.
- Given the limited budget, major direct impacts likely won't be felt immediately, but potential policy changes could lead to significant shifts over a decade.
- Policy changes could lead to job losses or gains depending on the efficiency of consolidated programs.
Simulated Interviews
Auto Factory Worker (Detroit, MI)
Age: 35 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 10.0 years
Commonness: 12/20
Statement of Opinion:
- I hope this policy can strengthen our industry rather than disrupt it.
- The last manufacturing shift left many of us uncertain about job security.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 5 |
| Year 2 | 5 | 5 |
| Year 3 | 6 | 5 |
| Year 5 | 6 | 5 |
| Year 10 | 7 | 5 |
| Year 20 | 8 | 5 |
Textile Industry Manager (Raleigh, NC)
Age: 42 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 20.0 years
Commonness: 8/20
Statement of Opinion:
- I'm interested in how this policy might improve efficiency in manufacturing programs.
- Consolidation could mean more streamlined processes or unintended disruptions.
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 | 8 | 6 |
Steelworker (Pittsburgh, PA)
Age: 28 | Gender: male
Wellbeing Before Policy: 4
Duration of Impact: 10.0 years
Commonness: 10/20
Statement of Opinion:
- We need more support, not just another study.
- Real jobs could be on the line depending on how this policy is implemented.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 4 | 4 |
| Year 2 | 5 | 4 |
| Year 3 | 5 | 4 |
| Year 5 | 6 | 4 |
| Year 10 | 7 | 4 |
| Year 20 | 7 | 4 |
Policy Analyst (Houston, TX)
Age: 50 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 5.0 years
Commonness: 5/20
Statement of Opinion:
- This is a crucial step in understanding and improving our manufacturing capabilities.
- The study can provide insights that lead to better policy decisions.
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 |
Electronics Manufacturer Owner (Seattle, WA)
Age: 60 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 7/20
Statement of Opinion:
- This might help us compete better, but only if the government implements the right improvements after the study.
- Consolidation could help or hurt depending on execution.
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 | 7 | 6 |
| Year 10 | 7 | 6 |
| Year 20 | 6 | 6 |
Supply Chain Coordinator (Chicago, IL)
Age: 33 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 5.0 years
Commonness: 10/20
Statement of Opinion:
- Greater efficiency in programs could really help mitigate some logistics challenges we face.
- The impact on the ground might be indirect but meaningful.
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 | 6 | 5 |
| Year 20 | 6 | 5 |
Union Representative (Boston, MA)
Age: 55 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 8.0 years
Commonness: 4/20
Statement of Opinion:
- This policy needs to prioritize worker input in any recommendations.
- Studies are good, but only if they result in tangible benefits for workers.
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 | 8 | 6 |
| Year 20 | 7 | 6 |
Software Engineer (San Jose, CA)
Age: 29 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 20.0 years
Commonness: 15/20
Statement of Opinion:
- I'm interested in how this might steer technology integration in manufacturing.
- The outcomes could open new opportunities for software development.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 7 | 7 |
| Year 3 | 8 | 7 |
| Year 5 | 8 | 7 |
| Year 10 | 8 | 7 |
| Year 20 | 8 | 7 |
Environmental Advocate (Atlanta, GA)
Age: 38 | Gender: other
Wellbeing Before Policy: 5
Duration of Impact: 0.0 years
Commonness: 3/20
Statement of Opinion:
- It's essential that any program changes also consider environmental impacts.
- This study might open avenues for cleaner manufacturing practices.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 5 |
| Year 2 | 5 | 5 |
| Year 3 | 5 | 5 |
| Year 5 | 5 | 5 |
| Year 10 | 5 | 5 |
| Year 20 | 5 | 5 |
Logistics Manager (Charlotte, NC)
Age: 45 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 6/20
Statement of Opinion:
- If the study results in better-coordinated programs, that could boost our efficiency.
- Any disruptions could drive costs up if not managed carefully.
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 | 6 |
| Year 10 | 6 | 6 |
| Year 20 | 6 | 6 |
Cost Estimates
Year 1: $3000000 (Low: $2000000, High: $4000000)
Year 2: $3000000 (Low: $2000000, High: $4000000)
Year 3: $3000000 (Low: $2000000, High: $4000000)
Year 5: $3000000 (Low: $2000000, High: $4000000)
Year 10: $3000000 (Low: $2000000, High: $4000000)
Year 100: $3000000 (Low: $2000000, High: $4000000)
Key Considerations
- The effectiveness of the study depends on the quality of data and the analysis conducted by the National Academy of Public Administration.
- Implementation of the study recommendations could be slow and politically challenging.
- Short-term financial costs are modest, but strategic long-term impacts could be significant.