Project Spotlight: Advanced Machine Learning for Forecast Optimization

A high-impact engagement with a major U.S. telecommunications provider serving millions of customers nationwide, focused on enhancing their forecasting accuracy through the strategic application of advanced machine learning (ML) techniques.

The Challenge:
Traditional forecasting methods struggled to keep pace with the complexity of a large telecom operation—characterized by fluctuating demand, evolving consumer behavior, and a fast-changing technology landscape. Forecast errors were resulting in inefficiencies across network capacity planning, workforce allocation, and revenue projections.

The Solution:
A scalable, AI-powered forecasting framework by:

• Engineering advanced ML models (e.g., gradient boosting, ensemble learning, time-series neural nets) tailored to subscriber behavior, churn patterns, product demand, and regional trends

• Integrating structured and unstructured data—billing, usage, CRM, network data, and external economic indicators

• Automating feature selection and training pipelines to support model agility

• Building a user-friendly dashboard for Finance, Operations, and Product teams to explore forecast outputs and scenario simulations

Key Results:

• Forecast accuracy improved by over 25%, significantly reducing over- and under-projection risk

• Enabled dynamic, rolling forecasts at national and regional levels

• Reduced manual effort in forecasting by over 60%

• Provided actionable insights for customer retention, pricing, and service bundling strategies

This project underscored the power of applied ML to move beyond intuition and into data-driven foresight — unlocking real business value at scale.

Proud to partner with innovative clients who embrace the future of forecasting!

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