Case Study
GrowthHub: Enterprise Competency Scoring Engine
Summary
Built a new competency-scoring platform from scratch that generates personalized skill profiles and growth plans for 7,000 employees across five external assessment vendors and internal performance data.
Impact
Launched to 7,000 employees, generating 1,177 custom growth plans and 768 SkillUp badges.
Challenge
The scoring algorithm had to reconcile inconsistent signals across five vendor platforms (SkillUp, LinkedIn, Udemy, HackerRank, and an internal source) plus Workday review data - accounting for whether a skill even had an associated test, how to weight tested versus untested evidence, and which review categories should most strongly nudge employees toward certification. At login, scores across 7,000 employees and roughly 650 skills needed to already be ready, ruling out real-time computation.
Architecture
New Kubernetes (on-prem) and Azure application built around a precomputation engine: scoring logic runs ahead of request time across all employees and skills, persisting results to a dedicated table that the API reads directly at login instead of computing scores live.
Key Decisions
Chose to precompute and store scores ahead of time rather than calculate them synchronously on each login, keeping page load fast regardless of algorithm complexity as vendor sources and weighting rules grew. Co-designed the weighting logic with stakeholders across all five vendor integrations and Workday to align on which signals should carry the most weight.
Scale Considerations
Serves 7,000 employees across roughly 650 tracked skills and five external data sources, fully decoupled from request-time computation via the precomputation architecture.
Last updated: July 11, 2026