AI model predicted supplier and customer deliverability with a 90% precision

Johan Öhlin
Head of Advanced Analytics

Purchasing teams handling inbound products and materials from suppliers often find themselves in a continuos loop of reactive, time-consuming and often manual tracking exercises when suppliers deliver late. Similarly, sales and customer service teams face the reality of handling dissatisfied customers when outbound orders, in turn, are delivered late to the final customer. Regardless if delay is in- or outbound, it is often a contributing factor in overall Supply Chain interruptions, increasing business risk, generating resource cost and increasing customer dissatisfaction.

Our Predictive Order Monitoring solution (or POM in short) uses AI models that can accurately predict which purchase or customer order will arrive late, this long before the order is dispatched. Through the Optilon Web Interface, team members can then view predictive statuses and taken proactive actions to course-correct delay.

90% precision in predicting order delay
We delivered a soluton for a global manufacturer who historically had experienced order delays from the suppliers. The AI model delivered a results close to 90% precision compared to the reality.

Summing up we could say that the solution:

  • Predicts supplier reliability and customer deliverability, order by order, day by day
  • The AI model continuously learns and predicts order delay and recommends proactive actions
  • The solution decreases order and production issues and creates a better customer satisfaction

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