By using the JAGGAER’s OTD Predictor, companies can identify where there is a risk of late delivery, and take actions to mitigate that risk
JAGGAER, the largest independent spend management company in the world, announced that it is developing the world’s first artificial intelligence (AI)-based algorithm – OTD Predictor that can predict the probability of goods and materials on-time delivery in the direct procurement.
The new algorithm will offer real-time information in case of any delays in the goods and material deliveries from suppliers, helping the supply chain managers to reduce risks of disruptions to production process and to cut the costs due to these disruptions.
JAGGAER also partner with ZEISS, a global leading technology enterprise in the fields of optics and optoelectronics, for ramping up of the OTD Predictor.
Accurate on time delivery prediction
Briefing about the new solution, Michael Rösch, SVP Operations for JAGGAER, said, “The algorithm predicts if an order will be delivered on time. In our tests, the accuracy was greater than 95 per cent. This is of huge potential benefit to manufacturing companies, especially those that rely on just-in-time component and materials delivery.”
“By using the OTD Predictor, companies can identify where there is a risk of late delivery, and take actions to mitigate that risk, for example by spreading an order over a second or third source,” he added.
Rösch further said that till now, supply chain management professionals have had to depend on historical evidences and subjective judgement for assessing the risks of late delivery. The OTD Predictor will enable them to move from reactive to proactive approach.
Ideal for direct spend categories
“The OTD Predictor relies on huge volumes of data making accurate predictions, therefore its application is ideal for direct spend categories having a vast volume of transactions. In addition, machine learning (ML) algorithms of the OTD Predictor mean that the predictions should get even more accurate over time,” he added.
JAGGAER OTD Predictor has been fed with millions of line items by way of the algorithm to learn from earlier events. The solution utilises 50 separate data dimensions for predicting the outcomes.