Many Degreed customers — companies like Verizon, Ericsson, TD Bank, and Volkswagen — faced the same challenge: their employees’ skills were scattered across multiple systems. Workday, SAP SuccessFactors, Pluralsight, and even Degreed all tracked proficiency differently.

This made it nearly impossible for leaders to see a reliable picture of workforce skills, and for learners to understand their own growth.

I was the lead product designer on a small team tasked with creating a new platform that could solve this.

Role: Lead designer

Timeline: 3–4 months for beta and MVP

Team: PM, engineers (backend, frontend, data science), design

Challenge: Normalize skill data across systems without losing trust or flexibility.

For admins: Skill data was fragmented across tools, each with its own scales and taxonomies. Comparing data or making workforce decisions was nearly impossible.

For learners: The same skill might show up differently depending on the system — leading to inconsistent and confusing feedback.

Provide a single, reliable view of skills for both admins and learners.

Support any source format — numbers, percentages, letter grades, custom scales.

Build transparency and trust by showing how data was mapped.

Pilot a new frontend and backend tech stack that could influence Degreed’s platform long-term.

We started with customer workshops and sketches, quickly moving into wireframes. These weren’t just design artifacts — they doubled as blueprints for engineering, who began building APIs and database structures in parallel.

Once workflows were clear, we shifted into heavy design exploration.

We tested a wide range of approaches — from dense data tables to colorful scale mappings to compact dropdown layouts.

Each iteration revealed something new:

The goal wasn’t just polish — it was pressure testing. Could the interface handle the complexity of multiple skill sources while still feeling approachable and fast?

One insight rose above the rest: auto-mapping.

Instead of requiring admins to select the appropriate levels from a dropdown, auto-mapping made the process efficient and trustworthy. Clients loved it, and it became the turning point in our design direction.

Skill Source Mapping — connect and align scales across systems.

Taxonomy Management — import, edit, and unify skill lists.

Admin Dashboard — track mapping activity and results.

Unified Learner Profile — show a consistent skill story across all sources.

Beta delivered in 3 months; MVP shortly after.

Customers could finally see skill data unified in one place.

Admins saved significant time and gained confidence in reporting.

Learners had a consistent view of their skills across all sources.

Degreed adopted the new design system and tech stack for the main platform.

Weekly client calls with Verizon, Ericsson, TD Bank, and Volkswagen kept the solution grounded in real workflows.

Designing for trust in data proved just as important as designing for usability.

Auto-mapping showed how AI/ML can drive efficiency while keeping humans in control.

If I could go further, I would add stronger visualization tools to help leaders plan workforce development at scale.