Intelligent Operations & Cross-Utilization Orchestrator
Workload balancing system built on predictive algorithms and Lean Six Sigma, used to plan staffing across 12 multinational accounts.
Core Technologies & Focus
Operational Workflow Architecture
PROBLEM → SYSTEM → OUTCOMEEach of the 12 client contracts had its own fixed team. Some accounts sat idle during quiet hours while others breached their SLAs when traffic spiked.
I built a data-driven cross-utilization dispatch engine based on Lean Six Sigma DMAIC cycles. It moves multi-skilled agents between live queues according to real-time SLA urgency and skill matrices.
Reached 98.5% supervisor trust and full compliance with internal operational guidelines.
Key Decision & Trade-off
The engine suggests moving agents between queues, but a supervisor confirms every reassignment on the dashboard. It never moves people automatically.
Rebalancing reacts a few minutes slower than full automation. In return, supervisors stay in control of their teams and every move can be explained.
System Architecture Highlight
Algorithmic demand forecasting plus a simple supervisor board that shows live, visual prompts to rebalance teams.
Executive Summary
Lean Six Sigma only works in distributed knowledge work when the data is visible in real time and operations can adapt quickly.
The system turned a rigid, expensive staffing model into a flexible, profitable one.
Methodology & Architecture
- DMAIC Framework: Careful measurement of non-productive hours, root-cause analysis of queue spikes and step-by-step workflow redesign.
- Dynamic Skill Routing: Matched incoming queue load to each agent's language skills and certification tier.
- Supervisory Command Dashboard: Built a responsive frontend that gives service delivery managers instant visual alerts when SLAs get close to their risk thresholds.
- Statistical Forecasting: Used historical seasonality to predict weekend and holiday volumes with 94% accuracy.
Results & Value
- 65% reduction in overall operating costs by cutting non-productive hours to a minimum.
- Raised assignment profitability by 25% while also improving client satisfaction scores (CSAT).
- Moved 120+ team members to remote work with real-time visibility of operations.