FMCG Case Study: Python-Based Demand Forecasting Solution| Clarion

Enhancing Supply Chain Efficiency with a Python-based Demand Forecasting Solution for A Consumer Goods Company

A leading consumer goods company struggled with forecasting demand for its variety of products. They wanted to address inventory mismanagement and build a data-driven solution for accurate prediction.

Clarion's Solution:

Our Python developers built a Python-based demand forecasting solution with ML. It analyzes historical sales data. seasonal trends, and external factors that can influence demand. Built with time-series forecasting technique, the system predicts precise demand at the product and regional level.

Business Benefits for our Client:

• Industry holding reduced by 25%: Our Python developers were able to remove excess inventory reducing capital tied up in excess goods.
• Stocks-outs decreased by 35%: By aligning stock levels, our Python programmers were able to improve customer satisfaction
• Production cost was lowered by 20%: Aligning production schedules helped improve manufacturing efficiency.

Conclusion

By deploying a Python-based demand forecasting solution, the consumer goods company was able to address its challenges in the supply chain.