Retail & CPG : Demand Forecasting

Demand Forecasting

A large retailor in Europe had a challenges of either high inventory or demand shortages for the finished goods leading to higher inventory costs and lost sales. The planners were relying on the excel spreadsheets to forecast demand at each SKU level and store level.

Our experts built an automated forecasting solutions using AWS Data and AI Services to accurately forecast demand and optimize inventory at the store level. Here is a solution overview:

Solutions

Data Ingestion : Data from various sources, such as sales transactions, inventory data, and customer data, is ingested into an Amazon S3 bucket, which serves as a data lake.

Data Preparation: The data is cleaned, transformed, and prepared for analysis using AWS Glue. Glue can be used to automate the data preparation process, making it easier to manage and scale.

Forecasting: Amazon Forecast is used to create a demand forecasting model based on the cleaned and prepared data. Forecast uses machine learning algorithms to generate highly accurate demand forecasts at the store level.

Analysis and Visualization: The demand forecasting results are analyzed and visualized using Amazon QuickSight. QuickSight provides real-time visualizations of the forecasted demand, allowing retail companies to quickly understand the data and make informed decisions.

Inventory Optimization: The demand forecasts generated by Amazon Forecast are used to optimize inventory levels at the store level using Amazon SageMaker. SageMaker can be used to create a machine learning model that optimizes inventory based on the demand forecast, ensuring that each store has the right amount of inventory to meet customer demand.

Alerts and Notifications: The solution can be set up to send alerts and notifications to store managers and other stakeholders when inventory levels are running low or when demand is higher than expected.