Blue Yonder Case Studies Kaufland Optimizes Its Replenishment Process

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	Kaufland Optimizes Its Replenishment Process Blue Yonder

Kaufland Optimizes Its Replenishment Process

Blue Yonder

Technology Category	Analytics & Modeling - Predictive Analytics
Applicable Industries	Retail
Applicable Functions	Logistics & Transportation
Use Cases	Predictive Replenishment
Services	Data Science Services
Challenge	Kaufland, a supermarket chain active throughout Europe with about 1,200 stores, offers a range of around 60,000 items to its customers. The main product focus includes fresh food comprised of fruit and vegetables, dairy, meat and fish. The range also includes household goods, electronics, textiles, stationery, toys and seasonal items, as well as weekly promotional merchandise. Kaufland set itself the ambitious goal of automating the replenishment process in its fresh meat division, as their existing supply chain processes had reached their limits. Read More
About Customer	Kaufland is a supermarket chain that operates throughout Europe with about 1,200 stores. The company offers a range of around 60,000 items to its customers, with a main product focus on fresh food including fruit, vegetables, dairy, meat, and fish. In addition to fresh food, Kaufland's range also includes household goods, electronics, textiles, stationery, toys, and seasonal items, as well as weekly promotional merchandise. Kaufland operates seven logistic centers and four meat manufacturing plants. Read More
Solution	Kaufland implemented Blue Yonder’s forecasting and replenishment capabilities to achieve a high degree of automation for central planning in daily orders. Additionally, production processes could be closely integrated into the supply chain as a whole, thus creating even greater synergy with demand planning. As well as internal data, important factors such as promotions, holidays and weather were taken into account and factored into the ordering decisions. The robust algorithm, Blue Yonder’s superior machine learning technology and their ability to highly automate the decision-making process were among the factors that convinced Kaufland to implement Blue Yonder across all their German stores. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Applicable Industries

Retail

Applicable Functions

Logistics & Transportation

Use Cases

Predictive Replenishment

Services

Data Science Services

Challenge

Kaufland, a supermarket chain active throughout Europe with about 1,200 stores, offers a range of around 60,000 items to its customers. The main product focus includes fresh food comprised of fruit and vegetables, dairy, meat and fish. The range also includes household goods, electronics, textiles, stationery, toys and seasonal items, as well as weekly promotional merchandise. Kaufland set itself the ambitious goal of automating the replenishment process in its fresh meat division, as their existing supply chain processes had reached their limits.

About Customer

Kaufland is a supermarket chain that operates throughout Europe with about 1,200 stores. The company offers a range of around 60,000 items to its customers, with a main product focus on fresh food including fruit, vegetables, dairy, meat, and fish. In addition to fresh food, Kaufland's range also includes household goods, electronics, textiles, stationery, toys, and seasonal items, as well as weekly promotional merchandise. Kaufland operates seven logistic centers and four meat manufacturing plants.

Solution

Kaufland implemented Blue Yonder’s forecasting and replenishment capabilities to achieve a high degree of automation for central planning in daily orders. Additionally, production processes could be closely integrated into the supply chain as a whole, thus creating even greater synergy with demand planning. As well as internal data, important factors such as promotions, holidays and weather were taken into account and factored into the ordering decisions. The robust algorithm, Blue Yonder’s superior machine learning technology and their ability to highly automate the decision-making process were among the factors that convinced Kaufland to implement Blue Yonder across all their German stores.

Impact #1	Kaufland achieved its goal of creating maximum efficiency within the fresh meat supply chain.
Impact #2	Centralized and highly automated planning was implemented, which significantly minimized the amount of work needed within individual stores.
Impact #3	Product availability was improved, resulting in optimized stock levels, ensured product freshness and reduced write-offs.

Impact #1

Kaufland achieved its goal of creating maximum efficiency within the fresh meat supply chain.

Impact #2

Centralized and highly automated planning was implemented, which significantly minimized the amount of work needed within individual stores.

Impact #3

Product availability was improved, resulting in optimized stock levels, ensured product freshness and reduced write-offs.

Benefit #1	High level of replenishment automation
Benefit #2	Significantly improved product availability

Benefit #1

High level of replenishment automation

Benefit #2

Significantly improved product availability

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Overview

Kaufland Optimizes Its Replenishment Process

Operational Impact

Quantitative Benefit