.
Paycom — Data system for segmented hiring teams
Paycom — Data system for segmented hiring teams
Paycom — Data system for segmented hiring teams
Designed a database system that recovered an estimated $137k per client in annual recruiter productivity.
Designed a database system that recovered an estimated $137k per client in annual recruiter productivity.
Color & branding have been adjusted post-project to meet Paycom's portfolio sharing standards.
Color & branding have been adjusted post-project to meet Paycom's portfolio sharing standards.
Role
Product Design Intern (Lead)
Collaboration
3 Product Designers
3 Product Managers
1 Senior Product Designer
Duration
2.5 months
Role
Product Design Intern (Lead)
Collaboration
3 Product Designers
3 Product Managers
1 Senior Product Designer
Duration
2.5 months
Role
Product Design Intern (Lead)
Collaboration
3 Product Designers
3 Product Managers
1 Senior Product Designer
Duration
2.5 months
This image is captured from Paycom's homepage.
Our team identified friction and bottlenecks within the pre-hire experience, estimating an annual loss of $137k per client in recruiter productivity due to manual candidate tracking.
We designed a unified platform that eliminated the manual ledger, giving recruiters instant visibility and recovering millions in lost productivity across Paycom's client base.
Our team identified friction and bottlenecks within the pre-hire experience, estimating an annual loss of $137k per client in recruiter productivity due to manual candidate tracking.
We designed a unified platform that eliminated the manual ledger, giving recruiters instant visibility and recovering millions in lost productivity across Paycom's client base.
Research
40% of users are forced to context switch due to complicated workflows, inconsistent data, and poor status visibility.
Our team compiled 84+ product experience feedback tickets within Jira, with users expressing pain-points with complicated workflows, data inconsistency, and the lack of clarity & visibility throughout the existing pre-hire onboarding tools.
Research
40% of users are forced to context switch due to complicated workflows, inconsistent data, and poor status visibility.
Our team compiled 84+ product experience feedback tickets within Jira, with users expressing pain-points with complicated workflows, data inconsistency, and the lack of clarity & visibility throughout the existing pre-hire onboarding tools.
Interviews
I interviewed 10 hiring specialists across different roles (Full Lifecycle Recruiter, Screening Recruiter, Background Check Specialist, & WOTC Specialist), revealing varied workflows that informed a more inclusive and adaptable design.
Discussions informed that WOTC specialist was not a major stakeholder to these products, allowing me to focus on creating decision-point process maps for the initial 3 roles.
Research
Interviews
I interviewed 10 hiring specialists across different roles (Full Lifecycle Recruiter, Screening Recruiter, Background Check Specialist, & WOTC Specialist), revealing varied workflows that informed a more inclusive and adaptable design.
Discussions informed that WOTC specialist are not a major stakeholder to these products, allowing me to focus on creating decision-point process maps for the initial 3 roles.
Interview Findings
Relying on manual tracking systems slows workflows significantly.
“[I spend] at least an hour per candidate, and 70% of my time in my ledger.” - Talent Acquisition Operations Specialist
“It’s a very manual process... That’s why we call out that it would be really nice to [improve the system] and not rely so much on a manual ledger.” - Supervisor of Talent Acquisition
Candidate bottlenecks are hard to identify due to poor status visibility.
“It’s hard to keep track of where my candidates are at, and it’s hard to see where they get stuck.” - Collegiate Recruiter II
“We have to manually go into 'offered candidates' [in ATS] almost every hour ... I have to sift through [to see] where a candidate is in the process.” - Talent Acquisition Operations Specialist
Interview Findings
Relying on manual tracking systems slows workflows significantly.
“[I spend] at least an hour per candidate, and 70% of my time in my ledger.” - Talent Acquisition Operations Specialist
“It’s a very manual process... That’s why we call out that it would be really nice to [improve the system] and not rely so much on a manual ledger.” - Supervisor of Talent Acquisition
Candidate bottlenecks are hard to identify due to poor status visibility.
“It’s hard to keep track of where my candidates are at, and it’s hard to see where they get stuck.” - Collegiate Recruiter II
“We have to manually go into 'offered candidates' [in ATS] almost every hour ... I have to sift through [to see] where a candidate is in the process.” - Talent Acquisition Operations Specialist
Scope Refinement
Collapsing 3 roles Into 1, reducing redundancy and building for scale.
Interview insights refined the project scope, shifting focus away from specialized roles like Background Check Specialists and Screening Recruiters due to significant overlap in workflows, towards a broader category of Onboarding Specialists.
Recruiting Supervisors also emerged as a new key stakeholder, prompting their inclusion in the primary user group.
Scope Refinement
Collapsing 3 roles Into 1, reducing redundancy and building for scale.
Interview insights refined the project scope, shifting focus away from specialized roles like Background Check Specialists and Screening Recruiters due to significant overlap in workflows, towards a broader category of Onboarding Specialists.
Recruiting Supervisors also emerged as a new key stakeholder, prompting their inclusion in the primary user group.
Personas
Personas
Competitive Analysis
Competitors track candidates, but can't audit decisions, manage pending tasks, or filter beyond the basics.
Competitive Analysis
Competitors track candidates, but can't audit decisions, manage pending tasks, or filter beyond the basics.
Ideation
Translating product goals into actionable features.
Utilizing discussions with the product team, I created a product goal list and translated them into potential features.
Ideation
Translating product goals into actionable features.
Utilizing discussions with the product team, I created a product goal list and translated them into potential features.
Feature Prioritization
Mapping business value against build complexity.
I created a feature prioritization matrix to consider both business value and complexity/effort of implementation.
Feature Prioritization
Mapping business value against build complexity.
I created a feature prioritization matrix to consider both business value and complexity/effort of implementation.
Prototype
Creating a Mid-Fidelity to validate core features.
Utilizing Paycom's existing design system and components, I designed a Mid-Fidelity prototype of the onboarding main dashboard.
Prototype
Creating a Mid-Fidelity to validate core features.
Utilizing Paycom's existing design system and components, I designed a Mid-Fidelity prototype of the onboarding main dashboard.
I also created a feature callout diagram outlining each component's function, purpose, and open questions to align the onboarding product team before moving into testing.
Testing & Feedback
I led 3 rounds of user testing across 8 recruiting roles, validating features, and incorporated feedback from the onboarding product team.
Testing & Feedback
I led 3 rounds of user testing across 8 recruiting roles, validating features, and incorporated feedback from the onboarding product team.
Key Findings
Nested features enable intuitive workflows, minimizing navigation.
Users found “My Checklist” and “Incomplete Candidate Actions” less intuitive as separate cards, preferring these items to be integrated within candidate profile details. 'Document Downloading' should only be visible when users select candidates.
Analytics should be separate from the dashboard landing page.
Managers & Recruiters want a "quick glimpse of staffing strategy trajectory", which shouldn't require scrolling to locate.
Clearer feature naming improves context and skimmability.
Replacing feature names allowed functionality to be more quickly recognized. For example: Progress Tracking -> Candidate Progress Tracker, Onboarded -> Ready to Start
Key Findings
Nested features enable intuitive workflows, minimizing navigation.
Users found “My Checklist” and “Incomplete Candidate Actions” less intuitive as separate cards, preferring these items to be integrated within candidate profile details. 'Document Downloading' should only be visible when users select candidates.
Analytics should be separate from the dashboard landing page.
Managers & Recruiters want a "quick glimpse of staffing strategy trajectory", which shouldn't require scrolling to locate.
Clearer feature naming improves context and skimmability.
Replacing feature names allowed functionality to be more quickly recognized. For example: Progress Tracking -> Candidate Progress Tracker, Onboarded -> Ready to Start
Nested Features & Naming Convention
“My Checklist” and “Incomplete Candidate Actions” cards were removed and integrated into candidate profile details, repositioning the dashboard as a candidate database with quick-glance analytics.
Naming conventions were refined to improve clarity and recognizability.
Progress Tracking -> Candidate Progress Tracker, Onboarded -> Ready to Start, Assign to -> Assignee, Stage -> Status, Onboarding Management -> Candidate Onboarding Management.
Nested Features & Naming Convention
“My Checklist” and “Incomplete Candidate Actions” cards were removed and integrated into candidate profile details, repositioning the dashboard as a candidate database with quick-glance analytics.
Naming conventions were refined to improve clarity and recognizability.
Progress Tracking -> Candidate Progress Tracker, Onboarded -> Ready to Start, Assign to -> Assignee, Stage -> Status, Onboarding Management -> Candidate Onboarding Management.
Analytics Breakdown
Addressing the need for a separated analytics pages, I prototyped 4 pages of stage breakdowns.
Analytics Breakdown
Addressing the need for a separated analytics pages, I prototyped 4 pages of stage breakdowns.
Final Deliverables
Prototype Presentation
I presented my work to cross-functional stakeholders (including product and design leadership), owning the development of the Candidate Progress Tracker, Management Tables, Stage Breakdown, Dynamic Actions Dropdown Menus, and Candidate Stage Drawer.
Final Deliverables
Prototype Presentation
I presented my work to cross-functional stakeholders (including product and design leadership), owning the development of the Candidate Progress Tracker, Management Tables, Stage Breakdown, Dynamic Actions Dropdown Menus, and Candidate Stage Drawer.
Final Deliverables
Feature specification & requirements
I created a feature specification and requirements table outlining functionality, dependencies, and key design considerations to align stakeholders on implementation details.
Final Deliverables
Feature specification & requirements
I created a feature specification and requirements table outlining functionality, dependencies, and key design considerations to align stakeholders on implementation details.
Final Deliverables
Product requirements document (PRD)
I developed a 16-page Product Requirements Document to ensure a detailed and structured handoff for the product, design, & engineering teams.
Final Deliverables
Product requirements document (PRD)
I developed a 16-page Product Requirements Document to ensure a detailed and structured handoff for the product, design, & engineering teams.
Impact
Recovered an estimated $137k per client in recruiter productivity.
My contributions reduced reliance on external spreadsheets and decreased unnecessary navigation steps required to access key information.
Impact
Recovered an estimated $137k per client in recruiter productivity.
My contributions reduced reliance on external spreadsheets and decreased unnecessary navigation steps required to access key information.
Future Considerations
What i'd solve next: A/B testing data visualization.
Given more time, I'd run additional user testing focused specifically on the analytics data visualizations to validate how effectively they support interpretation.
Future Considerations
What i'd solve next: A/B testing data visualization.
Given more time, I'd run additional user testing focused specifically on the analytics data visualizations to validate how effectively they support interpretation.