Business Case: Food Industry

Mass consumer products manufacturer: Picking Optimization – Order Preparation

Initial Situation

A company in the food sector produces its products in rotating shifts at a 24/7 frequency in order to supply the necessary stock to meet the demand of its orders.
However, its Picking or Order Preparation area reports problems when assembling them. They must make as many packages as orders are generated since there is no standardized order for common customers. This means that it takes a long time to prepare each order which in turn leads to an inefficient management of resources.

Proposed Solution

The proposal carried out consists of modifying the Sales Process in such a way as to offer the same composition of an order to customers with similar purchasing behavior.
In this way, the Picking area will be able to standardize its packaging process, and instead of processing each order individually, it will be able to develop different mixes of products that make up a single order that caters to a large group of customers.
This is developed thanks to a statistical analysis in which the composition of each order of the company is analyzed in a period of time, identifying groups of similar orders, and being able to carry out a Clustering or Customer Segmentation based on their purchasing behavior. The solution, on the other hand, constitutes an iterative development given that the seasonality of the requested products must be taken into account, so it is necessary to redefine this composition of similar orders at each stage of the year.

Technology Used

R – Power BI


With the implementation of the solution, it was possible to define a limited catalog of similar orders that correspond to almost 60% of the monthly orders received by the company. A sensitivity analysis demonstrates the effectiveness of these “common” orders.