Solution Overview

EY Demand Forecasting and Inventory Optimization enabled by Microsoft’s Cloud for Retail, builds a trusted data pipeline to standardize, reuse and scale data and models by using predictive data analytics to improve decision-making for inventory optimization. This allows for accurate forecasting, scenario analyses, visualization and incorporation of the following attributes:

Individual customer predictions incorporate customer history, stock keeping unit (SKU) information, and customer/location demographics to better predict demand and optimize target inventory levels through machine learning capabilities
Forecasting models utilize eight different forecasting techniques to find the best-fit model at the location-SKU level. A blended approach of repeat orders and new orders cuts out unnecessary inventory while maintaining service to customers
Simulation engine that estimates inventory improvement, prevents unexpected supply chain gaps and performs a driver analysis to optimize ordering
Scaled computation and storage efficiently distributes artificial intelligence (AI) models and data over multiple clusters. It allows for the calculation of hundreds of thousands of SKUs and locations

Solution Benefits

Improve customer experience with the right inventory

Incorporate customer-specific demand forecasting with predictions at the location and product level
Capitalize on previously unmet customer demands and untapped sales, and improve customer satisfaction by maintaining sufficient supply

Order the right amount of inventory at the right time

Utilize best-fit machine learning models to increase forecasting accuracy and holding a more precise inventory
Reduce human bias through automation and incorporating external/internal factors

Simulate inventory strategies before deploying at scale

Prevent supply chain gaps by simulating seasonal demand and ordering variability
Tweak inventory strategy to determine the optimal inventory approach to balance supply and demand

Leverage vast amount of data utilizing Microsoft Azure cloud technology

Quickly analyze and incorporate large volumes of customer and inventory data in machine learning models and augment existing inventory management systems

Integrate with current inventory system

Offer flexibility with solution add-ons and development
Incorporate the best market tools specific to the client

EY Demand Forecasting and Inventory Optimization

Autor: EY Global