Skill Intelligence
for Enterprise
Skill Intelligence
for Enterprise
Skill Intelligence
for Enterprise
Skill Intelligence
for Enterprise
The Problem
Large enterprise clients at Degreed — like Bank of America, Citi, and Unilever use multiple platforms to measure employee skills. Each one has its own unique rating scale: some use levels 1–5, others 0–4, or even 1–100. Each platform also defines level names and requirements differently.
This made it complicated and time-consuming for admins to understand an employee’s true skill level. It created confusion for learners too — like Alex, whose skills looked different in every system, with no clear way to compare or combine them.
Sophia
L&D Manager
“Our skill data is disconnected and spread across four different systems, each measuring proficiency in its own way”
Alex
Project Manager
“I can’t tell which version of my skill data my manager actually sees.”
The Problem
Large enterprise clients at Degreed — like Bank of America, Citi, and Unilever use multiple platforms to measure employee skills. Each one has its own unique rating scale: some use levels 1–5, others 0–4, or even 1–100. Each platform also defines level names and requirements differently.
This made it complicated and time-consuming for admins to understand an employee’s true skill level. It created confusion for learners too — like Alex, whose skills looked different in every system, with no clear way to compare or combine them.
Sophia
L&D Manager
“Our skill data is disconnected and spread across four different systems, each measuring proficiency in its own way”
Sophia
L&D Manager
“Our skill data is disconnected and spread across four different systems, each measuring proficiency in its own way”
Alex
Project Manager
“I can’t tell which version of my skill data my manager actually sees.”
Alex
Project Manager
“I can’t tell which version of my skill data my manager actually sees.”
Skill Data Sources
Skill
Stakeholder Alignment
Level 4 Advanced
85% Proficient
63/100
Level 3 Intermediate
The Solution
To solve this, we designed a flexible system that lets companies unify employee skill ratings from multiple platforms into one clear, consistent view. Admins can import different rating sources, define how each system maps to a shared scale, and instantly generate a normalized skill level for every learner. This replaced guesswork and manual spreadsheets with an automated framework that works for complex enterprise needs.
Extending the Platform
In addition to scale mapping, we designed powerful tools for admins to manage every part of their company’s skills data. They could upload entire skill taxonomies, organize frameworks by region or department, and use built-in tools to localize skills into multiple languages — ensuring global teams always see clear, relevant skill information.
Extending the Platform
In addition to scale mapping, we designed powerful tools for admins to manage every part of their company’s skills data. They could upload entire skill taxonomies, organize frameworks by region or department, and use built-in tools to localize skills into multiple languages — ensuring global teams always see clear, relevant skill information.
These tools gave admins full control over their organization’s skills, from uploading entire catalogs to managing translations for a global workforce and creating custom rating sources that connect with their existing systems. This flexibility turned Skaas into a true backbone for enterprise skills data, adaptable to any company in any region.
Skill normalization brings Alex’s scattered ratings into one clear level. Managers know exactly where she stands, without extra guesswork or manual mapping. It saves time and makes development decisions faster and more confident.`
Skill normalization brings Alex’s scattered ratings into one clear level. Managers know exactly where she stands, without extra guesswork or manual mapping. It saves time and makes development decisions faster and more confident.`
Alex Smith
Skill
Data Analysis
Primary Level
Level 3
Conclusion
This project gave large companies a way to trust and compare skill data across messy systems — saving time for admins and removing confusion for learners and managers alike.
I led the design end-to-end on this brand new app, working with a small team of four to take it from an abstract concept to a fully coded beta in under six months. Along the way, we used new technology, built a fresh design system, and set the foundation for how Degreed now handles skill ratings and enterprise integrations at scale.
We built this as a small, tight-knit team — designing, testing, and shipping something meaningful together.
Conclusion
This project gave large companies a way to trust and compare skill data across messy systems — saving time for admins and removing confusion for learners and managers alike.
I led the design end-to-end on this brand new app, working with a small team of four to take it from an abstract concept to a fully coded beta in under six months. Along the way, we used new technology, built a fresh design system, and set the foundation for how Degreed now handles skill ratings and enterprise integrations at scale.
We built this as a small, tight-knit team — designing, testing, and shipping something meaningful together.