Download PDF
Blue Yonder > Case Studies > Retailer CRV Increases Shopper Intelligence with Blue Yonder
Blue Yonder Logo

Retailer CRV Increases Shopper Intelligence with Blue Yonder

Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Functional Applications - Inventory Management Systems
Applicable Industries
  • Retail
Applicable Functions
  • Logistics & Transportation
  • Warehouse & Inventory Management
Use Cases
  • Demand Planning & Forecasting
  • Inventory Management
Services
  • Software Design & Engineering Services
  • System Integration
The Challenge
Retailer CR Vanguard (CRV), part of the CR Group, operates more than 3,240 stores across China, with total sales revenue of nearly 90 billion yuan. As one of the largest retailers in China, CRV must strategically orchestrate planning and merchandising across these stores in multiple formats, including hypermarkets, supermarkets, and convenience stores. The company's objective is to be customer-centric by leveraging best-in-class technology to understand and meet shopper needs, even as demand volatility increases. However, CRV's demand planning was accomplished by a homegrown solution that failed to capture the complexity of 3,000 stores, multiple formats, and localized shopper needs.
About The Customer
Retailer CR Vanguard (CRV) is part of CR Group, a state-held company directly managed by China’s central government and a Fortune Global 500 enterprise. CRV owns many popular retail brands including CR Vanguard, Suguo, Olé, blt, V+, Tesco express and V>nGO. CRV operates more than 3,240 stores across China, with total sales revenue of nearly 90 billion yuan. As one of the largest retailers in China, CRV must strategically orchestrate planning and merchandising across these stores in multiple formats, including hypermarkets, supermarkets, and convenience stores. The company's objective is to be customer-centric by leveraging best-in-class technology to understand and meet shopper needs, even as demand volatility increases.
The Solution
In 2009, CRV partnered with Blue Yonder on an implementation of category management solutions to drive revenues through customer-centric plans, assortments, and displays. Based on that success, CRV next implemented demand, fulfillment, and replenishment solutions from Blue Yonder. Today CRV has established a complete closed-loop planning process that enables its consumer-centered, highly successful retail model. Blue Yonder’s industry-leading forecasting algorithms and machine learning capabilities are built to manage localization, seasonality, fashion trends, and other demand complexities. Now the forecasting process is more accurate and more autonomous, requiring minimal human intervention. Across CRV's stores, Blue Yonder has helped increase sales, while decreasing inventory, by matching products more precisely to local needs.
Operational Impact
  • Blue Yonder’s demand planning solution helps CRV manage demand volatility and inevitable disruptions. The retailer can continue to meet localized customer needs across over 3,000 stores as conditions shift dynamically.
  • Fulfillment and replenishment capabilities from Blue Yonder enable CRV to maximize the value of its inventory investments. The retailer can deliver the right product to the right place at the right time to maximize both shopper satisfaction and profit margins.
  • Space planning solutions from Blue Yonder support increased localization by leveraging automation and data science. In every store, CRV can prioritize space devoted to high-demand offerings that will increase revenue and maximize financial return.
Quantitative Benefit
  • Increased daily inventory value
  • Reduced days of inventory
  • Decreased out-of-stocks

Related Case Studies.

Contact us

Let's talk!

* Required
* Required
* Required
* Invalid email address
By submitting this form, you agree that IoT ONE may contact you with insights and marketing messaging.
No thanks, I don't want to receive any marketing emails from IoT ONE.
Submit

Thank you for your message!
We will contact you soon.