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

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

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

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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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