Replenishment and Price Optimization at OTTO
Company Size
1,000+
Region
- Europe
Country
- Germany
Product
- Blue Yonder Demand Forecast & Replenishment
- Blue Yonder Price Optimization
Tech Stack
- Artificial Intelligence
- Machine Learning
- Data Analytics
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Productivity Improvements
- Revenue Growth
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Predictive Analytics
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- E-Commerce
- Retail
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Demand Planning & Forecasting
- Inventory Management
Services
- Data Science Services
- System Integration
About The Customer
OTTO is a German multichannel retailer based in Hamburg that successfully transitioned from a classic mail-order retailer to an online retailer by permanently adapting its business processes and reorienting its enterprise. The online shop (www.otto.de) is the focus of the retailer‘s business, accounting for 90% of its annual sales of more than EUR 2.5 billion (fiscal year 2015/16). The company offers a wide range of products including fashion items, technical products, furniture, sports articles, shoes, and toys. The online shop boasts around 6,000 brands and more than 2.2 million items, including more than 1 million goods sold by retail partners.
The Challenge
OTTO, a German multichannel retailer, faced challenges in its competitive environment characterized by low margins, high competitive pressure, and rapidly changing market conditions and customer demands. The company needed to balance product availability and pricing for every single article in its extensive product portfolio. One of the greatest challenges was predicting the sales of an article at an early stage, as the profitable purchase of goods determines overall success. OTTO also faced challenges in reducing delivery times for partner products, which were longer than for OTTO’s own brands due to more complicated logistics processes. The retailer needed to know which articles would sell, how frequently, and in what sizes and amounts to order the right articles in advance based on the forecasts and expedite delivery to the customer.
The Solution
OTTO partnered with Blue Yonder, a JDA company, to implement AI solutions to improve its customer experience, increase sales, reduce stock levels, and decrease returns by basing strategic decisions on data insights. Blue Yonder’s article sales forecasts became a fixed part of the operative business processes at OTTO, providing an up-to-date forecast per color and size, based on hundreds of different input variables. Blue Yonder’s Demand Forecast & Replenishment solution was used for merchandise planning in OTTO’s central distribution center with a selection of brand partners. The solution evaluates around 3 billion transactions including sales, prices, and inventories and provides machine-driven ordering decisions in advance. Blue Yonder Price Optimization was used to find the “ideal” price for each product according to the chosen price strategy. The solution examines and measures the connection between price changes and demand patterns, and based on a number of price-quantity pairs, it can pinpoint the price elasticity for every item.
Operational Impact
Quantitative Benefit
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