Enhanced forecasting precision
Improved accuracy
Scalable solution
Optimized forecasting strategy
The challenge
Optimizing forecasting accuracy and supply chain efficiency
A U.S.-based Consumer Packaged Goods (CPG) company sought a solution to improve forecasting accuracy across multiple product categories, aiming to optimize inventory management and enhance supply chain efficiency.
Key challenges
Varied data hindered reliable forecasts
Difficulty predicting demand across categories
Struggled to align production with fluctuating demand
The solution
Smarter demand forecasting with AI and AWS
AI-Powered Forecasting
Foresient used for demand predictions
AI algorithms provided actionable insights
Supported short, mid, and long-term decision-making
Scalable cloud infrastructure
Leveraged AWS for scalable operations
Integrated AWS for efficient processing
Ensured seamless forecasting
Implementation approach
1
Scalable compute
Hosted on AWS EC2 for scalable compute
Optimized for large-scale operations
Supported front end, back end, and APIs
2
Data processing
Used AWS EMR (Spark) for data processing
Enabled real-time analysis
Boosted forecasting accuracy
3
Cost-effective storage
Stored data and models in S3
AWS RDS for cost-effective database
Streamlined data access and management
The impact
Enhancing forecasting precision and operational alignment
Improved forecast accuracy
85%-95% forecast accuracy across six categories
Surpassed typical 60%-80% accuracy
Improved demand predictions
Actionable insights
Weekly forecasts by SKU, customer, and region
Delivered short to long-term insights
Optimized inventory and production
Better decision making
Improved supply chain management
Optimized planning and distribution
Aligned production with demand
Looking ahead
Scalability
Expand AWS EC2 for growing demand
Data processing
Enhance analysis with AWS EMR (Spark)
Data management
Optimize storage with AWS RDS and S3
