Optimal replenishment for fresh produce

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Summary of the entity:

Migros is one of the largest FMCG retailers in Turkey. With more than 2000 stores and 30.000 employees, Migros is also the pioneer of organized retailing in Turkey. Migros today offers spacious stores in a wide range of formats and locations whose vast selection of cosmetics, stationery, glass and kitchenware, electronic appliances, book, textiles, and other items along with groceries and other necessities give it the ability to satisfy the shopping needs of its customers.

The company aims to be always the first choice of customers by providing a unique convenience and trustworthy shopping experience through its ultimate service approach, pioneer applications, broad product portfolio and family budget friendly pricing strategy.

Summary of the challenge:

The objective is to improve processes related to fresh produces thanks to i) the creation of monthly estimates for fresh produce production in Turkey, and ii) the optimization of logistic operations by using the provided data for shipments of products.

Description of the global challenge:

Fresh produces are one of the main reasons for customers in the process of choosing a retailer. The quality of the fresh produces is an important differentiator. In addition to the revenue they produce, fresh produces also help increase the footfall and provide cross sell opportunities. It is of great importance to optimize the processes related to fresh produces such as purchasing, logistics, inventory management. This is especially crucial to increase the quality of the products offered to customers and to reduce waste and other losses that occur during distribution and retail.

In this global challenge it is aimed to improve processes related to fresh produces. To that extent, two different sub-challenges have been defined. The first one is oriented to get an estimation model to create monthly estimates for fresh produce production in Turkey, whereas the second one, is aimed at optimizing logistic operations by using the provided data for shipments of products.

It is possible to enrichen the predictive models using data from agriculture, weather forecast, or public data from relevant national/international bodies

Sub-challenges composing this experiment:

• Estimating Fresh Produce Production and Consumption in Turkey
• Reducing Waste in Fresh Produce Operations

Expected global results:

1. Reduce waste by 5%
2. Increase revenue by 5%

REDUCING WASTE IN FRESH PRODUCE OPERATIONS

Code:

REACH-2020-READYMADE-MIGROS_2.2

Summary of the sub-challenge:

The main goal is to reduce waste and improve the product quality for fresh procedures sold at MIGROS, by getting a model that allows to estimate the sales of each product.

Description of the challenge:

The objective is to reduce waste and to improve the product quality for fresh produces sold at Migros. MIGROS tackles this issue by trying to improve the logistical operations using company data.

MIGROS provides store and product level data showing the sales, losses and inventory level for each product. It is expected to have a model to estimate the sales of each product to help the company planning its logistics to reduce the waste.

MIGROS provides store and product level sales, losses, and inventory data. This allows applicants to come up with analytical models to plan the logistics (may be even purchasing) accordingly. The applicants are encouraged to investigate external data sets to solve the problem.

Data to be used:

• Sales and inventory data

It is possible to enrichen the analytical models using data from agriculture, weather forecast.

Expected outcomes:

• Reduce waste 5%