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AI-Powered Demand Forecasting System for Beverage Production Optimization

coderio.com

Food & Beverage

Consumer products & services

Logistics

Challenges in Demand Forecasting and Inventory Management

Inaccurate demand predictions led to inventory inefficiencies, excess stock costs, and production planning challenges. The company required a dynamic system to analyze complex patterns, seasonality, and special event impacts to optimize supply chain operations.

About the Client

A leading CocaCola bottler operating in Latin America, focused on innovation, sustainability, and operational efficiency in beverage production and distribution.

Key Goals for the Predictive System

Develop AI-driven models to forecast daily retail sales with 85%+ accuracy
Optimize production planning and workforce allocation
Enable adaptability to special events and market fluctuations
Reduce inventory management costs through precise demand predictions

Core System Capabilities

Time series analysis using SARIMA and Prophet models
Event-driven demand adjustment for holidays/promotions
Scalable cloud architecture on AWS SageMaker
Integration with production planning and inventory systems

Technology Stack

Python

AWS SageMaker

Facebook Prophet

SARIMA Models

System Integrations

ERP systems
Supply chain management platforms
Sales data repositories

Performance Criteria

High scalability for Latin American market expansion
Real-time prediction processing
Data security compliance with beverage industry standards

Expected Business Outcomes

Implementation of the AI forecasting system is projected to reduce inventory costs by 20-30%, improve production efficiency through accurate resource planning, and enable dynamic adjustments to market changes while maintaining CocaCola's leadership in beverage industry innovation.