Telecom — Telecom Product Demand Forecasting Pipeline

Overview

The telecom product demand forecasting pipeline is designed to accurately predict the demand for telecom products, thereby reducing stockouts and optimizing inventory levels. It ingests historical sales data along with external factors such as promotional activities and weather conditions. The data ingestion process involves normalizing these diverse data sources to ensure consistency and reliability. Once the data is prepared, time series models are applied to forecast future demand effectively

The telecom product demand forecasting pipeline is designed to accurately predict the demand for telecom products, thereby reducing stockouts and optimizing inventory levels. It ingests historical sales data along with external factors such as promotional activities and weather conditions. The data ingestion process involves normalizing these diverse data sources to ensure consistency and reliability. Once the data is prepared, time series models are applied to forecast future demand effectively. Quality control measures are implemented throughout the process to maintain data integrity and accuracy, ensuring that any anomalies are identified and rectified promptly. The final forecasts are made available through a forecasting API, allowing stakeholders to access real-time insights. Key performance indicators (KPIs) such as Mean Absolute Percentage Error (MAPE) are monitored to evaluate the forecasting model's performance continuously. In the event of a processing failure, a robust recovery mechanism is in place to ensure minimal disruption. This pipeline not only streamlines inventory management but also enhances overall operational efficiency, leading to improved customer satisfaction and reduced costs.

Part of the Market & Trading Intelligence solution for the Telecom industry.

Use cases

• Reduces stockouts through accurate demand forecasting
• Optimizes inventory levels to lower holding costs
• Enhances responsiveness to market changes
• Improves customer satisfaction with product availability
• Supports data-driven decision-making for promotions