Using Predictive Analytics in Supply Chain Management Helped a German OEM Manufacturer Increase Accuracy of their Demand Forecast by 37%

May 31, 2021

Engagement Summary

Understanding demand and forecasting accurately remain a significant challenge for OEM manufacturers across the globe. OEM industry demand has never been linear and is affected by uncountable variables, some of which are beyond control. Predictive analytics allows businesses to improve demand forecasting and supply planning, allowing organizations to determine optimal inventory levels to satisfy demand while minimizing stock. This success story revolves around a German OEM manufacturing company that wanted to leverage Quantzig’s predictive analytics solutions to shift from a monolithic architecture of their supply chain management network.

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About the client

The client is a German OEM manufacturer based with production hubs in Berlin and active operations across the globe. The client operates through a complex network of over 100 subsidiaries and has regional entities in several countries worldwide.

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Business Challenge

This client is an OEM supplier of car accessories worldwide with numerous warehouses and factories spread across Europe and Asia. Their business process includes raw material procurement, warehouse management, supply chain management and operations, and transportation of finished products. The pandemic outbreak has slowed down manufacturing due to the shortage of workforce, making it difficult for the client to keep up with demand.

The primary business challenges faced by the client were –

  1. Shortage of workforce and increased global restrictions made it difficult for the client to manage logistics operations.
  2. The monolithic architecture of the supply chain network was leading to frequent system failures.
  3. Unable to predict bottlenecks and roadblocks
  4. Ineffectual attempts of improving workflow
  5. High cost of production

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Solution Offered

Quantzig’s SMEs helped the client build a scalable logistics and supply chain management and operations architecture that enabled them to improve their warehouse efficiency across Europe, thus reducing the delivery time.

Quantzig’s experts also derived a demand and planning optimization model powered by predictive analytics that helped the client improve their existing supply chain management and operations, pre-empt bottlenecks and roadblocks, avoid unplanned downtime, and optimize inventory management.

Business Outcome

The critical business outcomes for the client after making use of predictive analytics in their supply chain management were –

  1. Increased accuracy of demand forecast by 37% over six months
  2. Automated manual work and reduced paperwork for warehouse workforce, thus improving productivity by 8.7%
  3. Deployed a microservice logistics and supply chain network
  4. Streamlined inventory management for 75 warehouses across Europe

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