Bill Overview
Title: National MEP Supply Chain Database Act of 2022
Description: National MEP Supply Chain Database Act of 202 This bill requires the National Institute of Standards and Technology to establish a database that provides a national overview of the networks of U.S. supply chains.
Sponsors: Sen. Menendez, Robert [D-NJ]
Target Audience
Population: People involved in or dependent on U.S. and interconnected global supply chains
Estimated Size: 150000000
- The database will focus on U.S. supply chains, which include manufacturers, suppliers, and distributors across various industries.
- Businesses that are part of these supply chains, particularly those collaborating with or impacted by U.S. manufacturing and distribution, will be included.
- This legislative move can influence any business linked to the supply chains in terms of operational efficiency and market reach.
- The enhancement of supply chain networks can potentially impact labor markets within manufacturing and distribution sectors.
Reasoning
- The new policy primarily impacts those involved in manufacturing, supply, distribution, and related sectors. Within these, the policy is likely to benefit businesses and workers by providing improved data for operational efficiency and connectivity.
- Given the large scope of the policy, encompassing up to 150 million Americans directly or indirectly related to the supply chain, the policy is designed to benefit a significant portion of the population, although the individual level of impact will vary greatly.
- In order to maintain the budget, the policy will implement the database incrementally, prioritizing key sectors initially, which may lead to varied impacts on different industries over time.
- The budget constraints suggest that while the policy aims to cover a wide range of supply chain stakeholders, its immediate benefits may more strongly benefit larger firms and institutions that are more directly connected to the use of such data.
- The distribution of effects is important; certain industries more reliant on real-time supply chain data could experience greater impacts on operational efficiencies, translating into potentially significant changes in wellbeing scores particularly over long-term planning horizons as efficiencies lead to improvements in job growth and stability.
Simulated Interviews
Production Manager (Detroit, MI)
Age: 34 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 12/20
Statement of Opinion:
- This database could help streamline our supplier communications and reduce bottlenecks.
- Better coordination might lead to fewer idle days in production.
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 | 7 |
| Year 20 | 7 | 7 |
Logistics Analyst (Los Angeles, CA)
Age: 45 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 10/20
Statement of Opinion:
- The database could provide valuable insights into optimizing routes and reducing shipment times.
- I'm hopeful that it will lead to cost savings which could be reinvested in the company.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 8 | 7 |
| Year 5 | 9 | 7 |
| Year 10 | 9 | 8 |
| Year 20 | 8 | 8 |
Small Business Owner (Raleigh, NC)
Age: 29 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 3.0 years
Commonness: 14/20
Statement of Opinion:
- I'm worried about whether this database will actually benefit small businesses like mine.
- Larger businesses might benefit more from the increased transparency.
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 | 6 | 5 |
| Year 20 | 5 | 5 |
Supply Chain Director (Houston, TX)
Age: 52 | Gender: male
Wellbeing Before Policy: 8
Duration of Impact: 20.0 years
Commonness: 6/20
Statement of Opinion:
- Access to a national overview would be a game changer for long-term strategic planning.
- Efficiencies gained could potentially reduce operational costs significantly.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 9 | 8 |
| Year 3 | 9 | 8 |
| Year 5 | 10 | 8 |
| Year 10 | 10 | 9 |
| Year 20 | 9 | 9 |
Research Scientist (Seattle, WA)
Age: 40 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 5.0 years
Commonness: 8/20
Statement of Opinion:
- Our work could benefit indirectly if the database helps ensure steadier and safer supply of medical supplies.
- The policy may not affect my personal job directly but contributes positively to public safety.
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 | 7 | 7 |
Software Developer (Chicago, IL)
Age: 28 | Gender: male
Wellbeing Before Policy: 8
Duration of Impact: 10.0 years
Commonness: 11/20
Statement of Opinion:
- Excited about the potential for developing new software solutions based on data from the database.
- Such initiatives drive innovation and can create new business opportunities.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 9 | 8 |
| Year 5 | 9 | 8 |
| Year 10 | 9 | 8 |
| Year 20 | 8 | 8 |
Retail Buyer (New York, NY)
Age: 37 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 15/20
Statement of Opinion:
- If this database improves visibility and reliability of U.S. supply chains, it could have a big impact on our import strategies.
- There's potential for improved coordination with suppliers.
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 | 7 | 6 |
| Year 20 | 6 | 6 |
Union Leader (Dayton, OH)
Age: 50 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 5.0 years
Commonness: 10/20
Statement of Opinion:
- I'm cautiously optimistic that this could protect jobs by stabilizing supply chains.
- However, transparency should not come at the cost of labor rights.
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 | 6 |
| Year 10 | 7 | 6 |
| Year 20 | 6 | 6 |
Freelance Consultant (San Francisco, CA)
Age: 26 | Gender: other
Wellbeing Before Policy: 6
Duration of Impact: 8.0 years
Commonness: 9/20
Statement of Opinion:
- This policy could be an excellent tool for advising clients on sustainability in their supply networks.
- There is a growing demand for transparency, and this could build trust with consumers.
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 | 8 | 7 |
| Year 20 | 7 | 7 |
Retired (Phoenix, AZ)
Age: 62 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 3.0 years
Commonness: 13/20
Statement of Opinion:
- This initiative is a positive step towards modernizing supply chains in the U.S.
- I am curious to see how it will affect smaller and medium-sized businesses.
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 |
Cost Estimates
Year 1: $105000000 (Low: $90000000, High: $120000000)
Year 2: $95000000 (Low: $85000000, High: $110000000)
Year 3: $95000000 (Low: $85000000, High: $110000000)
Year 5: $100000000 (Low: $90000000, High: $115000000)
Year 10: $110000000 (Low: $100000000, High: $120000000)
Year 100: $130000000 (Low: $110000000, High: $150000000)
Key Considerations
- Technological advancements and cybersecurity measures must be prioritized to protect sensitive supply chain data.
- Widespread collaboration across industries is crucial for comprehensive and accurate data collection.
- The potential economic benefits must be weighed against the considerable initial and ongoing costs.
- Encouragement of voluntary participation and potential regulation to ensure data completeness and reliability.