Nestlé Success Story

Apr 15, 2024

Pyplan Partners with Nestlé on Demand Planning and Production Optimization

About Nestlé

Netle Success Story

For over 100 years, Nestlé has been dedicated to food production. It has more than a dozen product families, including global icon brands and local favorites, with more than 1350 different SKUs. Among the product families that Nestlé Brazil produces and sells there are: beverages, coffees, dairy products, cereals, chocolates, nutrition, baby food and even pet food.

The project challenge

Until now, no tool had the flexibility and speed that Nestlé required to plan the Demand and Production processes in an integral way and within the same environment. That’s why Pyplan Partners with Nestlé on Demand Planning and Production Optimization.

Production planning is essential for optimizing the overall process, considering the products, resources and processes involved, as well as the expected demand for each product line.

Nestlé sought to find a tool that automates and optimizes the Demand and Production Planning processes, in a way that would allow users to have full visibility of both the hierarchy of its large product portfolio (by segment, family, brand, SKU, among others) and the logistics point, factories and production lines.

Solution Design

The proposed solution system integrated the existing Distribution Module, with the Demand Planning and Production Optimization Modules.

Demand Planning Module

The aim was to develop a single planning model, based on existing models and best practices. This module included forecast adjustments to the Baseline, BIAS analysis, trend and evolution analysis, trade marketing alignment, risk analysis and volume division by SKU.

Production Optimization Module

With the implementation of this module, the major challenge was to develop the Master Production Schedule, which established the Mixing, Volume and Production Deadlines considering sales, operations and stock planning.

Benefits achieved by Nestlé Brasil

  • Optimizing production by identifying possible bottlenecks in the process in advance
  • Matching production to demand, optimizing stock levels, avoiding shortages or lost sales
  • Anticipating resource needs: inputs, labor or investments in production line capacity
  • Automation of different processes saving up to 75% of the invested time in carrying out operational tasks.