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Blue Yonder > Case Studies > Successful Demand Forecasting at dm
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Successful Demand Forecasting at dm

Technology Category
  • Analytics & Modeling - Predictive Analytics
Applicable Industries
  • Retail
Applicable Functions
  • Logistics & Transportation
  • Sales & Marketing
Use Cases
  • Demand Planning & Forecasting
  • Predictive Replenishment
Services
  • Data Science Services
The Challenge
dm, a large retail company, faced several challenges in its operations. The company needed to improve the cooperation between the manufacturer and the distribution center to ensure product availability. It also needed to provide valid predictions for industry partners. The company was dealing with the issue of short-term demand for goods in stores versus long delivery times of industry partners. It needed to make precise sales forecasts, even for exceptional cases like holidays or vacations. The company also wanted to avoid over- and understaffing in its stores.
About The Customer
dm is a large retail company that operates numerous stores. The company has a complex supply chain that involves manufacturers, distribution centers, and individual stores. It deals with a wide range of products, and its operations are affected by various factors such as store hours, market days, and holidays. The company aims to optimize its operations by accurately predicting sales and demand, ensuring product availability, and efficiently planning staff.
The Solution
dm chose Blue Yonder to predict sales accurately in individual stores and thus reliably carry out staff planning. The forecasts considered each store’s daily sales from the last 10 years and adjustable parameters, including store hours. This was necessary to determine the number of employees needed as accurately as possible. Other external data were factored in addition to this, such as pending market days or holidays in neighboring states. Blue Yonder also delivered precise demand forecasts for dm distribution centers for the next six months. This guaranteed that the expected availability of goods was met in stores, as well as optimized delivery time and manufacturer logistics.
Operational Impact
  • Precise staff planning with exact sales predictions
  • Optimized workflows
  • Satisfied employees and customers
Quantitative Benefit
  • Increased security for industry partner planning and ordering
  • A basis for long-term raw material planning
  • Meeting demands for availability of goods and ending up with less overstock

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