Bill Overview
Title: Chance to Compete Act of 2022
Description: 2022 This bill modifies examination requirements and other components of the federal hiring process for positions in the competitive service. Specifically, the bill provides that a qualifying examination includes a résumé review that is conducted by a subject matter expert. Additionally, beginning two years after the bill's enactment, the bill prohibits examinations from consisting solely of a self-assessment from an automated examination, a résumé review that is not conducted by a subject matter expert, or any other method of assessing an applicant's experience or education; an agency may waive these requirements when necessary but must report any such waivers. Agencies may use subject matter experts to develop position-specific technical assessments that allow applicants to demonstrate job-related skills, abilities, and knowledge; assessments may include structured interviews, work-related exercises, procedures to measure career-related qualifications and interests, or other similar assessments. The bill also allows agencies to establish talent teams to support and improve hiring practices. The Office of Personnel Management (OPM) must create online platforms through which agencies may share and customize technical assessments and share the résumés of qualifying applicants. The OPM must also create online platforms with information about (1) the types of assessments used and hiring outcomes, (2) educational requirements for certain positions and related justifications, and (3) authorities and programs that support agency recruitment and retention.
Sponsors: Rep. Hice, Jody B. [R-GA-10]
Target Audience
Population: People applying for positions in the federal competitive service
Estimated Size: 2000000
- The Chance to Compete Act of 2022 impacts federal hiring processes, which directly affects job applicants seeking federal competitive service positions.
- There are approximately 1.9 million federal employees in the U.S., and many positions become vacant and need to be filled annually, implying a large number of applicants who may be impacted.
- The bill would likely affect future applicants who would need to undergo the new recruitment process.
- The use of subject matter experts and improved assessment methods would primarily impact the career prospects of individuals seeking employment in these positions.
Reasoning
- The Chance to Compete Act of 2022 impacts individuals applying for federal jobs, which are typically subject to rigorous competitive service requirements. Our focus is on the potential improvement in the hiring process which may influence the perceived fairness and effectiveness of recruitment by using subject matter experts, structured interviews, and work-related exercises.
- Given that there are about 1.9 million federal employees and a substantial portion would apply to such positions over time, this policy primarily impacts those qualified individuals actively seeking federal employment during the policy's enactment period and beyond.
- Budget and scope limitations imply targeting people who are significantly affected by federal hiring processes, particularly those preparing to apply or currently in the hiring pool where these changes are phased in.
Simulated Interviews
Policy Analyst (Washington, D.C.)
Age: 29 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 5.0 years
Commonness: 11/20
Statement of Opinion:
- I believe that with subject matter experts reviewing applications, the selection process will be fairer and more aligned with the job criteria.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 8 | 7 |
| Year 5 | 8 | 7 |
| Year 10 | 8 | 6 |
| Year 20 | 7 | 6 |
Software Engineer (San Francisco, CA)
Age: 35 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 10/20
Statement of Opinion:
- The addition of technical assessments is great as it measures practical skills, which is important in my field.
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 | 9 | 5 |
| Year 10 | 9 | 5 |
| Year 20 | 8 | 5 |
Recent College Graduate (Chicago, IL)
Age: 24 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 5.0 years
Commonness: 14/20
Statement of Opinion:
- I'm hopeful this policy will help new graduates like me stand out if we can show our skills through practical exercises rather than just through résumés.
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 |
IT Specialist (Austin, TX)
Age: 40 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 3.0 years
Commonness: 13/20
Statement of Opinion:
- The revised hiring process could make it easier for experienced professionals like me to showcase our competencies effectively.
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 | 7 | 6 |
| Year 10 | 6 | 6 |
| Year 20 | 6 | 6 |
Administrative Officer (Denver, CO)
Age: 32 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 3.0 years
Commonness: 12/20
Statement of Opinion:
- Subject matter expert reviews could make inter-departmental transfers more transparent and merit-based.
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 | 6 | 5 |
| Year 10 | 6 | 5 |
| Year 20 | 6 | 5 |
Data Analyst (New York, NY)
Age: 45 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 6.0 years
Commonness: 9/20
Statement of Opinion:
- I hope that using talent teams will improve the efficiency of hiring processes and result in better job matches.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 6 |
| Year 2 | 8 | 6 |
| Year 3 | 8 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 7 | 6 |
| Year 20 | 7 | 6 |
University Professor (Boston, MA)
Age: 50 | Gender: female
Wellbeing Before Policy: 8
Duration of Impact: 2.0 years
Commonness: 8/20
Statement of Opinion:
- The policy seems to support a more structured approach to hiring, which is critical for senior roles.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 8 | 7 |
| Year 5 | 8 | 7 |
| Year 10 | 7 | 7 |
| Year 20 | 7 | 7 |
Social Worker (Los Angeles, CA)
Age: 28 | Gender: other
Wellbeing Before Policy: 5
Duration of Impact: 4.0 years
Commonness: 15/20
Statement of Opinion:
- A more transparent hiring process at the federal level could create more opportunities for professionals outside the DC area.
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 | 8 | 5 |
| Year 10 | 7 | 5 |
| Year 20 | 6 | 5 |
Project Manager (Houston, TX)
Age: 39 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 3.0 years
Commonness: 11/20
Statement of Opinion:
- The integration of work-related exercises could better showcase my project management skills, making the process fairer.
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 | 6 | 6 |
| Year 20 | 6 | 6 |
Government Contractor (Phoenix, AZ)
Age: 30 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 5.0 years
Commonness: 10/20
Statement of Opinion:
- OPM's new platforms might speed up hiring, which is beneficial when shifting from contract to permanent positions.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 8 | 7 |
| Year 5 | 9 | 7 |
| Year 10 | 8 | 6 |
| Year 20 | 7 | 6 |
Cost Estimates
Year 1: $80000000 (Low: $50000000, High: $120000000)
Year 2: $82000000 (Low: $51000000, High: $123000000)
Year 3: $84000000 (Low: $52000000, High: $126000000)
Year 5: $88000000 (Low: $54000000, High: $132000000)
Year 10: $96000000 (Low: $58000000, High: $144000000)
Year 100: $120000000 (Low: $72000000, High: $180000000)
Key Considerations
- The initial setup costs for developing online platforms and training existing staff are significant, but are expected to decline after implementation.
- Long-term savings through reduced hiring costs and improved processes could offset some ongoing costs.
- Centralization of assessments could enhance inter-agency hiring capabilities and efficiencies.
- An accurate estimation of ongoing annual costs is challenging due to variability in agency engagement and technology adoption rates.