Case study

Predictive Analytics

Demand Forecasting
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The Challenge

One of the top pain points for manufacturing businesses is ever-changing product demand.

A short product life cycle, weather-dependency or marketing campaigns impose great uncertainties that break traditional methods which demand planners often rely on.

The Solution

MACHINE LEARNING FOR DEMAND FORECASTING


 

1. Historical and new data from sources such as CRM & ERP systems, marketing surveys and social media is aggregated.

2. A predictive models is build to identify event outcomes and forecast product demand.

3. The models are monitored to measure business performance. Prediction accuracy is enhanced through continuous improvements.

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Benefits

  • Combine company information with economic indicators, promotional events, weather changes etc.
  • Facilitate spotting new market opportunities
  • Generate granular insights into future demands

Further Use Cases

  • Demand Sensing: Manage and react to real-time changes in purchase behaviour
  • Inventory Planning for Retail
  • Network Capacity Planning to install new cells and base stations
  • Optimize Ad-spend: Proactively adjust ad-spend based on product availability

... and many more

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