Smart Forecasting Solution Aligns Supply with Demand for Global Consumer Goods Leader

Smart Forecasting Solution Aligns Supply with Demand for Global Consumer Goods Leader Banner

Client Profile.

The client is a UK-based leading consumer goods company delivering health, hygiene and nutrition products across hundreds of product lines to global markets. In an increasingly competitive and volatile market, the company manages a complex supply chain network of 40,000+ individual retailers across 200 countries.

Business Need.

The company was using a demand forecasting model to predict weekly demand, plan raw material procurement and schedule production. To feed in historical data, they managed multiple data pools in SAP and JDE systems. Time series data models like ARIMA, STLARIMA were used to predict demand for each SKU. By considering parameters like sales, trends and seasonality, their system generated reports for forecast quantity vs. actual sales in a production line.

However, these reports were erroneous, incomplete and conflicting across functions due to lack of visibility into system metrics like logistics center and stock level.

The company needed to strengthen its forecast model and make it more robust to ensure enhanced forecast accuracy and timely responses to critical operational concerns like inventory optimization, procurement of raw materials, and stock visibility.


A root-cause analysis into the problem statement by HitechDigital data scientists and a review of the existing forecast model threw up the following challenges:


Delivered customized data solution using data mapping of sales, brand and promotional data for seamless integration of all supply chain operations including product availability, management and operations-right from suppliers to customers. Also provided analytical inputs to augment and enhance their existing data models through data pre-processing (data cleansing and standardization) and forecasting solutions.

The solution helped to:


Business Impact.

Increased stock visibility in a regular and volatile environment
Better forecasting accuracy
Improved inventory management for all products
Enhanced product lifecycle
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