Analytics & KPIs

Context

 This representative model is based on my experience designing enterprise learning analytics systems that integrate AI-enabled measurement, performance enablement, and business intelligence. It reflects how I architect data frameworks that translate learning activity into actionable insight and strategic decision-making.

The Problem

 Many learning organizations collect extensive data from LMS platforms, assessments, and AI tools, but lack clear metrics, coherent dashboards, and analytic models that connect learning activity to real performance improvement and business outcomes. As a result, learning impact is difficult to prove, optimize, or justify at an executive level.

My Approach

 I design analytics as a decision-support system, not just a reporting layer:

• Define outcome-driven KPIs aligned to business objectives
  
  

• Design data flows that connect learning systems, AI signals, and business platforms
  
  

• Build dashboards that surface meaningful patterns, not just raw metrics
  
  

• Interpret skill, performance, and business signals holistically
  
  

• Use insights to drive program optimization, prioritization, and investment decisions
  
  

What This Demonstrates

• Learning analytics and measurement architecture
  
  

• KPI modeling aligned to performance and business value
  
  

• Business intelligence thinking applied to learning systems
  
  

• Data-driven decision making and optimization
  
  

• ROI-focused learning strategy
  
  

Tools & Methods

 BI dashboards (Power BI, Tableau), KPI and metric design, data modeling, learning analytics frameworks, performance metrics, AI-enabled data interpretation, and analytics-driven program optimization.