Demand Planning and Production Optimization

Pirelli is the leading tire manufacturer in Brazil and the leader in its sector. It is the most recognized and valued tire brand by Brazilians, Providing them with high-quality, high-performance tires for their vehicles. 





50 %




15 M


The project challenge 

Pirelli was using a combination of different tools and spreadsheets that made the financial planning process complicated, with many manual tasks and projection models that could not be extended to match the complexity of the business. 

The company was looking for a tool to optimize the Financial Planning and Analysis process. Their need was to automate import and update data processes, improve the projection models and facilitate the display of reports at different hierarchical levels, including the head office in Milan (Italy). 

Solution Design 

The solution was developed on the Pyplan platform and consisted in implementing a management tool with three specific modules: 

Variable and Fixed Cost Projection module: PxQ-type models have been created to project variable costs at the highest level of detail: by SKU, sales channels, etc. The data upload forms have been created to make it possible to project fixed costs by cost center. 

Labor Cost Projection Module: With Pyplan FP&A’s multidimensional cubes, robust models have been created to calculate and project labor costs per employee considering production plants, shifts, salary conditions, among others. 

Financial Statement Projection Module: Pyplan FP&A has a financial statement projection module that allows the users to link all the revenue and cost projection models with the financial statements to see the projected results instantly. 


Benefits achieved by Pirelli

Reduced budget preparation time.

Granular visibility of historical data and projections.

Faster updating of monthly forecasts.

Greater clarity and visualization speed for hierarchical areas.

Dynamic linking with other internal data sources (ERP).

Ability to create and analyze multiple scenarios.

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