A restaurant holding company with 5 different brands, more than 150 locations throughout Chile, and more than 3,000 workers, sought to optimize the allocation of staffing and shifts at its points of sale. The company was generating shifts in a manual and discretional way, which caused multiple risks, such as inefficiencies, errors and higher costs. The scale of the business made it imperative to find a different solution to properly allocate employees in the various stores. In particular, it was established as a goal to generate an automated shift optimization model that considers multiple variables (e.g. process times, projected sales, labor legislation, among others) to determine the appropriate number of personnel per location, at all times, to ensure the defined levels of attention and service, minimizing costs, complying with labor legislation and ensuring fair and orderly shifts for employees.
With this new model, it was possible to eliminate the discretionary power of supervisors when assigning personnel and to make better use of personnel hours throughout the country.
Brain Food staff became involved in the operation of each of the chains studied, understanding the difficulties and particularities of the work of the people to be modeled. Thousands of measurements were taken of product processing times and of the administrative processes within each store, to obtain a significant sample for each one of them, and thus estimate how long it took on average to process each product in each of the stores studied. Taking these inputs and together with other variables (such as labor legislation and a productive sales model created by Brain Food), an automated model was generated and made available in the Brain Food suite, where the model can be run, parameters can be changed and the results obtained can be visualized.
In-depth analysis of premises operation with actual endowment utilization
Automated model that allows defining optimal allocations per location according to context
Application that allowed for manual inputs and intuitive operation by decision-makers
Differentiated opening hours
Proximity to warehouses from which supplies are replenished
Physical layout of the premises
Number of boxes
Number of production lines
Distribution of sales in the product mix
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