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S&OP
FMCG
Machine Learning
Demand Forecasting

Digitizing S&OP for a Leading FMCG Giant

Leading FMCG Company in North America

How a Fast-Moving Consumer Goods Company Replaced Manual Planning with a Scalable, Data-Driven S&OP Platform

Tech Stack

PythonReact.jsCloudMachine LearningRabbitMQ

Process Visualization

Process Visualization

The Challenge

The company's S&OP process relied on fragmented spreadsheets, distributor reports, and manual coordination across regions. With thousands of SKUs and multi-layer distribution, teams spent significant time reconciling data leading to delays, errors, and reactive decision-making.

Fragmented S&OP data across Excel files and regional reports
Time-intensive manual data consolidation and validation
No real-time visibility into demand and stock movement
Judgment-driven forecasts causing overstocking or stockouts
No single source of truth for scenario analysis

The Solution

We built a centralized, cloud-based S&OP platform for high-volume, multi-channel FMCG planning unifying data, automating workflows, and introducing ML-powered forecasting across all distribution levels.

Automated consolidation of actuals, forecasts, and stock data
Multi-level sales visibility (primary, secondary, tertiary)
ML-powered demand prediction across distribution layers
Real-time dashboards with audit trails and governance
Scenario planning for demand, supply, and promotions

Implementation

1

Discovery & cross-functional workflow mapping

2

Cloud-native architecture design

3

Core modules with automated data pipelines

4

ML model development & retraining pipelines

5

Testing, rollout & team adoption

Impact & Results

Operational Impact

  • Eliminated manual reconciliation
  • Improved data accuracy across channels
  • Reduced stockouts and excess inventory

Business Impact

  • Unified sales, supply chain & finance teams
  • Faster decision-making via real-time dashboards
  • Data-driven forecast accuracy

Strategic Impact

  • Scalable platform for growth & expansion
  • Stronger distributor relationships
  • AI-ready data foundation

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