AI Case Study

Leroy-Merlin forecasts sales and suggests orders to department managers to optimise supply chain with machine learning

Leroy-Merlin, the French headquartered home improvement and gardening retailer has implemented Vekia’s ProOrder tool to optimise their supply chain. The solution is able to make sales forecasts and order suggestions to department managers each morning using machine learning.


Industry

Consumer Goods And Services

Homebuilding And Construction

Project Overview

"To optimize its supply chain, Leroy-Merlin uses Vekia’s ProOrder tool, which operates according to the principles of machine learning, to make sales forecasts and order suggestions to department managers each morning. The tool takes into account sales history, store inventory and current business transactions, as well as future events (holidays, upcoming promotions etc) and calculates the optimal orders to be passed in order to minimize the cost Global (CA lost in case of break, logistical costs, margin of error …)."

Reported Results

"Its implementation has resulted in an overhaul of the organization and its processes: for this self-learning tool to work, the data provided to it must be the right ones."

Technology

"The tool, ProOrder, is a Solution built on Machine Learning. The sales forecasts it generates are based on a relevant model computed from the past behaviour of all channels embedded with specific events (business operations, sales periods, etc.)."

Function

Supply Chain

General Supply Chain

Background

"'Even in a traditional world like DIY, building or decoration, our business is undergoing a revolution, and our customers are changing: they buy, learn and prepare their purchases differently. Demanding,' explains Luc de Rycke.

The brand, which has 130 stores in France, is aiming for 6 billion euros in sales in 2017. 'If we still want to exist in 20-30 years and realize 12 billion euros by that date, we make the changes that will allow us to always be a reference with our customers.'

The main investments were first made in the shops and for the website, on the “front office” part, visible to customers. 'Developing what the customer sees is good, but it does not just mean placing an order or going into a store. It takes the whole buying experience to be fluid and qualitative.' This “fluidity” depends in particular on the reliability of the information provided online and the competitiveness of the offer, delivery and availability of products. All these elements require investments in back-office tools."

Benefits

Data

historical data, such as business operations, sales periods