Reduced Procurement Costs Powered By Enriched Demand Forecasting

Optimize your procurement by augmenting your demand forecasting models with better data

Procurement managers must constantly plan material purchasing strategies in advance while relying on data that is, many times, insufficient. Failing to keep track of rapidly changing customer preferences can result in losing thousands of dollars ordering the wrong materials. However, if you can predict demand more accurately, you can understand where to prioritize your procurement efforts, and the best times to purchase materials.
The problem

Our customer was having trouble with procurement due to rapid changes in market preferences and fluctuations. Although they could quickly source components, they, too often, were buying the wrong types, leading to shortages, wasted inventory, and unnecessary surplus. The result was spiraling procurement costs and delays in the company’s production and supply chains. The company’s procurement models are built on historic data, as opposed to more dynamic data streams.

The solution

By tapping into thousands of external data sources that offered greater context, our customer was able to build a more reliable forecasting model that optimized predictions. The new model identified key features to determine demand, including: 

  • Purchasing patterns based on seasonal and weather conditions
  • Demand for products compared to annual earnings and sales volume
  • Vendor purchasing habits based on external and internal events 
  • Seasonal purchasing based on region and location 
  • Social media interactions and analysis by product
The results:

Reduced inventory costs and better procurement

Switching to an ML-based and dynamic demand forecasting system allowed the manufacturer to boost its accuracy by 9% in the short run, which led to a rapid reduction in inventory costs of nearly 17%. More importantly, it enabled the company to better adapt to rapidly changing manufacturing conditions. The company overhauled their procurement process to just-in-time shipping, empowered by accurate forecasting that reduces costs without sacrificing quality.

Discover how to reduce inventory costs and improve forecasting strategies with better data.

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