Policy Impact Analysis - 117/S/3650

Bill Overview

Title: PLUM Act of 2022

Description: of 2022 This bill replaces the congressional publication entitled United States Government Policy and Supporting Positions , commonly known as the PLUM Book , with an online public directory. The PLUM Book contains personnel information for federal civil service leadership and support positions in the legislative and executive branches that may be subject to noncompetitive appointment, including heads of agencies and policy executives. The book is used to identify presidentially appointed positions and is published every four years (after each presidential election) by certain congressional committees. The bill requires the Office of Personnel Management (OPM) to publish the information contained in the PLUM Book on a public website in a format that is easily searchable and that otherwise meets certain data standards. Agencies must upload updated information to the website on an annual basis; OPM must verify the accuracy of the information within 90 days of establishing the website in coordination with the White House Office of Presidential Personnel. The bill terminates publication of the PLUM Book in its current form on January 1, 2026.

Sponsors: Sen. Carper, Thomas R. [D-DE]

Target Audience

Population: People engaged with U.S. Government employment and appointments data

Estimated Size: 30000

Reasoning

Simulated Interviews

Government Relations Specialist (Washington D.C.)

Age: 34 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 5.0 years

Commonness: 12/20

Statement of Opinion:

  • Having easier access to appointment information will undoubtedly help our firm advise clients more efficiently.
  • I expect to spend less time tracking down this information, which will make my job smoother.
  • Concerns exist about the reliability of website updates, especially initially.

Wellbeing Over Time (With vs Without Policy)

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

IT Specialist at a Federal Agency (California)

Age: 45 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 2.0 years

Commonness: 15/20

Statement of Opinion:

  • Transitioning to an online directory will mean more work on the front end for IT departments, but it'll modernize our systems.
  • Initial bugs and data inaccuracies may cause operational headaches, though I see long-term benefits.

Wellbeing Over Time (With vs Without Policy)

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

Investigative Journalist (New York)

Age: 29 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 10.0 years

Commonness: 10/20

Statement of Opinion:

  • The online directory will make it easier and faster to research appointments and positions, enhancing my work.
  • However, reliability heavily depends on the update frequency and accuracy from the agencies involved.

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 5
Year 20 7 5

Federal Employee (Kansas)

Age: 52 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 1.0 years

Commonness: 20/20

Statement of Opinion:

  • As a federal employee, I'm more concerned about the internal impacts of the policy, such as accuracy and privacy of data.
  • Overall, impacts on my daily life may be minimal.

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

HR Specialist in a Federal Agency (Virginia)

Age: 40 | Gender: other

Wellbeing Before Policy: 7

Duration of Impact: 5.0 years

Commonness: 14/20

Statement of Opinion:

  • Implementation adds a new level of complexity in terms of data fidelity and updates.
  • If executed well, this could streamline processes and reduce manual paperwork.

Wellbeing Over Time (With vs Without Policy)

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

Political Analyst (Texas)

Age: 37 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 4.0 years

Commonness: 13/20

Statement of Opinion:

  • Open access will provide significant data for my analysis work, allowing for better insights.
  • Dependability of information accuracy is critical and some skepticism exists regarding initial implementation phase.

Wellbeing Over Time (With vs Without Policy)

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

Retired Federal Employee (Maryland)

Age: 62 | Gender: female

Wellbeing Before Policy: 8

Duration of Impact: 2.0 years

Commonness: 18/20

Statement of Opinion:

  • While I may not interact with it daily, I appreciate the shift to modern and transparent tools for current and future federal employees.
  • It might help people earlier in their careers understand the landscape better.

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 8 8
Year 10 8 8
Year 20 8 8

Graduate Student in Political Science (Illinois)

Age: 30 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 4.0 years

Commonness: 10/20

Statement of Opinion:

  • Having online and up-to-date data will be extremely helpful for my studies and future career in academia.
  • My concerns include potential access barriers if data standards aren’t user-friendly.

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 7 5
Year 20 6 5

Small Business Owner (Florida)

Age: 50 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 0.0 years

Commonness: 16/20

Statement of Opinion:

  • I don’t think this policy will directly affect my business much, but it's good to see more transparency from the government.
  • I'm hopeful that smoother processes for federal appointments might indirectly streamline contracting processes.

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

Data Scientist (Nevada)

Age: 27 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 3.0 years

Commonness: 12/20

Statement of Opinion:

  • I anticipate this will make aggregating data regarding federal positions easier and faster.
  • The accuracy and format of this data will determine how useful it ultimately is for deeper analysis.

Wellbeing Over Time (With vs Without Policy)

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

Cost Estimates

Year 1: $5000000 (Low: $3000000, High: $8000000)

Year 2: $2500000 (Low: $1500000, High: $4000000)

Year 3: $2500000 (Low: $1500000, High: $4000000)

Year 5: $2500000 (Low: $1500000, High: $4000000)

Year 10: $2500000 (Low: $1500000, High: $4000000)

Year 100: $2500000 (Low: $1500000, High: $4000000)

Key Considerations