Predictive Network Optimization
We helped a European mobile network operator optimize cell-tower capacity using predictive traffic models, deferring a €3M tower buildout while maintaining service quality.
A European mobile network operator scaling across regional markets.
The Challenge
Peak demand around commuter hours and stadium events was saturating specific cell towers, triggering quality-of-service complaints. The finance team was under pressure to fund accelerated tower upgrades to catch up.
Our Approach
We built a predictive capacity model that anticipates traffic concentration at specific cells based on time-of-day, local events, and historical patterns. The system pre-balances load across neighbouring towers before saturation occurs.
- Cell-level traffic pattern analysis across the network
- Event-driven pre-balancing to anticipate saturation
- Carrier-aware QoS adjustments for latency-sensitive traffic
- Software-layer optimization avoiding hardware capex
The Results
The operator smoothed out peak-hour saturation without accelerating tower buildout. Customer-reported QoS incidents dropped significantly, and leadership gained roughly 12 months of runway before the next capex cycle.
Continuous Optimization
The model continues to refine its predictions, adapting to changing usage patterns such as major sporting events, festivals, and seasonal commuter shifts.