Streamlining distribution centre operations at Carrefour

The challenge

Optimising distribution centre operations to accommodate fluctuating demand

This Carrefour distribution centre was crucial to managing daily flows, with peaks reaching up to 1.7 times normal levels. Operations were highly mechanised and automated, and the retailer maintained rigorous control over the streams of physical items and data. Although there were clearly defined seasonal phases, the distribution centre also had to meet hard-to-anticipate variations in demand.

Carrefour wanted to understand the optimal way to respond to these variations, so they could consistently provide the highest-possible service levels to customers.

The solution

Using Twinn Witness predictive simulation software to create a virtual model of distribution centre operations

Carrefour turned to Twinn Witness predictive simulation software, formerly under the Lanner brand, to provide in-depth insight. By creating virtual models of assets, operations and processes, predictive simulation lets you experiment with ‘what-if’ scenarios and validate decisions in a risk-free environment. It was the ideal solution for understanding the complex, dynamic variables involved in Carrefour’s distribution centre operations.

The Witness model incorporated more than 17,000 variables, including 260 km of conveyors, 100+ people, 50+ vehicles and 350 cart circuits. We designed it with a user-friendly Excel interface, so it was simple for Carrefour users – in just a few seconds, they could create a new scenario drawing on a wide range of data.

As a result, Carrefour could easily experiment with:

• Resource levels based on demand
• System limitations
• Options for managing operations when flows reached critical levels
• Lorry arrival and departure schedules
• Flow allocation
• Stock capacity, especially for the main automated warehouse
• Line changes

The impact

Evidence-based insight that pre-empts bottlenecks and streamlines logistics

Using its ‘virtual distribution centre’, Carrefour had an evidence-based way to understand how operational changes affected flows and service levels. Importantly, the model highlighted high-risk problems before they affected real-life operations, so Carrefour could pre-empt issues and optimise operations.

One key area of impact was related to logistics. Using the Witness model, Carrefour gained a better understanding of limits for accommodating incoming lorries. They discovered that the sorting machine at reception represented a potential bottleneck, and were able to identify and validate solutions for avoiding sorting machine overload.