Policy Impact Analysis - 117/S/5090

Bill Overview

Title: Cargo Preference Reporting Act

Description: This bill requires the U.S. Maritime Administration to make public and submit to Congress a report regarding cargo preference data on an annual basis.

Sponsors: Sen. Fischer, Deb [R-NE]

Target Audience

Population: People in global shipping and logistics industries

Estimated Size: 6500000

Reasoning

Simulated Interviews

Ship Captain (New Jersey, USA)

Age: 45 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 5.0 years

Commonness: 8/20

Statement of Opinion:

  • This policy could lead to greater transparency within the industry, which is a good thing.
  • Regular reporting may highlight inefficiencies we face and could result in improvements.

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 8 7
Year 10 8 7
Year 20 8 7

Logistics Manager (Texas, USA)

Age: 58 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 3.0 years

Commonness: 10/20

Statement of Opinion:

  • Increased reporting could complicate compliance but also lead to more systematic improvements.
  • As a manager, I welcome data that can refine our operations.

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 7 6
Year 10 7 6
Year 20 7 6

Government Employee (Florida, USA)

Age: 39 | Gender: male

Wellbeing Before Policy: 8

Duration of Impact: 10.0 years

Commonness: 5/20

Statement of Opinion:

  • This will increase workload initially, but the long-term benefits of transparent reporting justify the effort.
  • It could set the stage for more effective maritime policies.

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 9 8
Year 10 9 8
Year 20 9 8

Shipping Company Employee (California, USA)

Age: 27 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 2.0 years

Commonness: 15/20

Statement of Opinion:

  • This policy directly impacts my job, increasing transparency demands.
  • I hope this leads to better operational standards industry-wide.

Wellbeing Over Time (With vs Without Policy)

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

Shipping Company Manager (Virginia, USA)

Age: 48 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 5.0 years

Commonness: 7/20

Statement of Opinion:

  • Any transparency helps long-term policy goals, even if it's challenging initially.
  • Hopeful for streamlined procedures in the future changing ambiguity into precision.

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 8 6

Maritime Lawyer (Seattle, USA)

Age: 33 | Gender: female

Wellbeing Before Policy: 9

Duration of Impact: 8.0 years

Commonness: 3/20

Statement of Opinion:

  • This could drive policy reforms which are overdue in many respects.
  • Increased clarity in shipping data can resolve disputes more efficiently.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 9 9
Year 2 9 9
Year 3 9 9
Year 5 9 9
Year 10 10 9
Year 20 10 9

Retired Maritime Worker (New York, USA)

Age: 62 | Gender: male

Wellbeing Before Policy: 5

Duration of Impact: 4.0 years

Commonness: 12/20

Statement of Opinion:

  • Transparency has always been lacking, more transparency can only be helpful.
  • I'm skeptical of how swiftly changes will happen though.

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 6 5

International Trade Consultant (Georgia, USA)

Age: 50 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 3.0 years

Commonness: 9/20

Statement of Opinion:

  • This adds clarity that can facilitate smoother trade operations.
  • Informed policies are the best policies, this step could lead to such.

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 8 7
Year 10 9 7
Year 20 9 7

Mariner (California, USA)

Age: 29 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 2.0 years

Commonness: 6/20

Statement of Opinion:

  • Anything that helps increase operational transparency is desirable.
  • It might not change my day-to-day work immediately but can affect future guidelines.

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 7 6

Logistics Coordinator (Louisiana, USA)

Age: 46 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 5.0 years

Commonness: 4/20

Statement of Opinion:

  • This data should help refine where we dispatch goods most efficiently.
  • If shared properly, this information could guide strategic planning and resource allocation.

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 8 7
Year 10 8 7
Year 20 8 7

Cost Estimates

Year 1: $2500000 (Low: $2000000, High: $3000000)

Year 2: $2550000 (Low: $2050000, High: $3050000)

Year 3: $2600000 (Low: $2100000, High: $3100000)

Year 5: $2700000 (Low: $2200000, High: $3200000)

Year 10: $3000000 (Low: $2500000, High: $3500000)

Year 100: $5000000 (Low: $4500000, High: $5500000)

Key Considerations