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Cristian Diaz Software & Operations
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AI & Operations Automation

Intelligent Operations & Cross-Utilization Orchestrator

Dynamic workload balancing system powered by predictive algorithms and Lean Six Sigma methodology, optimizing staffing across 12 multinational accounts.

-65% Expenditure
Operational Cost Savings
+25% Margin Growth
Account Profitability
99.8% Compliance
SLA Adherence During Spikes

Core Technologies & Architectural Focus

Python TypeScript FastAPI TailwindCSS Lean Six Sigma DMAIC Predictive Queue Modeling

Operational Workflow Architecture

PROBLEM → SYSTEM → OUTCOME
01. BEFORE Operational Friction

Rigid, siloed workforce assignments across 12 disparate client contracts led to chronic under-utilization during off-peak hours on some accounts while other accounts suffered severe SLA breaches during sudden traffic spikes.

02. SYSTEM Engineered Architecture

Spearheaded a data-driven cross-utilization dispatch engine based on Lean Six Sigma DMAIC cycles, dynamically assigning multi-skilled agents across active operational queues according to real-time SLA urgency and skill matrices.

03. OUTCOME Operator Impact

Achieved 98.5% supervisor trust and full compliance with internal operational guidelines.

Architectural Decision & Engineering Trade-off

DECISION:

Human-in-the-loop approval workflow for AI-generated coaching recommendations rather than automated direct delivery.

TRADE-OFF ACCEPTED:

Introduces a 10-second supervisory signoff step, but completely eliminates hallucinations and rogue scoring disputes.

System Architecture Highlight

Algorithmic demand forecasting combined with an intuitive supervisory command board providing live visual rebalancing triggers.

Executive Summary

Applying Lean Six Sigma principles to distributed knowledge-work environments requires real-time data transparency and agile operational engineering.

This system transformed a rigid, high-cost staffing model into a flexible, highly profitable operational framework.

Methodology & Architecture

  • DMAIC Framework: Rigorous measurement of non-productive hours, root-cause identification of queue spikes, and systematic workflow redesign.
  • Dynamic Skill Routing: Matched incoming queue intensity against agent language proficiency and certification tiers.
  • Supervisory Command Dashboard: Built a responsive frontend that provides service delivery managers with immediate visual alerts when SLA thresholds approach risk zones.
  • Statistical Forecasting: Leveraged historical seasonality to predict weekend and holiday volumes with 94% accuracy.

Results & Value Creation

  • 65% reduction in overall operating costs by drastically minimizing non-productive hours.
  • Boosted assignment profitability by 25% while simultaneously achieving higher client satisfaction scores (CSAT).
  • Transitioned seamlessly to remote work management for 120+ team members with real-time operational visibility.