The resulting model captured the necessary metrics and provided simulation comparable to the real world.
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As a result, factors such as service time, product freshness, and waste, among other service metrics, were also included in the model.įinally, according to the rigor of HAVI’s analytics process, the model was subject to validation and calibration, including trials in McDonald’s test kitchen. On the output side, it was vital to measure the customer experience. Layout of a modeled kitchen (click to enlarge) Decision variables of the simulation model included: Using AnyLogic, these requirements could be met and simulated, along with the spatial constraints and the wide variety of equipment and labor configurations. An increase in the variety of items being cooked simultaneously.
![anylogic customer market tutorials anylogic customer market tutorials](https://www.anylogic.com/upload/iblock/505/5055db7047f50de37ec154897f6ba401.jpg)
To meet McDonald’s requirements, the model considered: HAVI employs an iterative hypothesis-driven process for its simulation and analytics, balancing data with human experience. The value of the model was to enable more informed decision-making for equipment purchases and staffing. Working with HAVI, a simulation model was created that reflected the enormous complexity of the supply chain and operations across the 14,000 restaurants. McDonald’s business objective was to equip and staff its kitchens to obtain the best financial yield possible for the menu expansion. When McDonald’s wanted to build on the success of the All-Day Breakfast launch by expanding all-day availability to more menu items at 14,000 restaurants, they encountered a number of challenges (menu complexity, new equipment needs, space constraints).Īll-Day Breakfast launch plan (click to enlarge) They provide services for supply chain management, packaging, logistics, recycling and waste.
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HAVI is a $5 billion global company and McDonald’s long-time supply chain and packaging partner.