JAGGAER is prototyping the world’s first artificial intelligence-based algorithm for predicting the probability of on-time delivery of goods and materials in direct procurement. The JAGGAER OTD Predictor will provide immediate information about the likelihood of delays to deliveries from suppliers, enabling supply chain managers to mitigate risks of disruptions to production flows and reduce the costs that these can cause.
ZEISS will be a partner of JAGGAER for the ramp of the OTD Predictor.
“The algorithm predicts if an order will be delivered on time. In our tests, the accuracy was greater than 95 percent!” says Michael Rösch, SVP Operations for JAGGAER in the DACH region. “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.”
The OTD Predictor has been “trained” by feeding millions of line items through the algorithm to learn from previous events. It uses 50 separate data dimensions to predict outcomes. “Until now, supply chain management professionals have had to rely on historical evidence and subjective judgment to assess the risk of late delivery. The JAGGAER OTD Predictor will allow them to move from the reactive to the proactive,” says Rösch. “Because it relies on large volumes of data to make accurate predictions, its application is specifically for direct spend categories with a high volume of transactions. The OTD Predictor’s machine learning algorithms mean that these predictions should get even more accurate over time.”
“I am especially pleased that we will be unveiling the JAGGAER OTD Predictor at eLösungstage, which is the main annual event hosted by the professional association for supply chain managers, buyers and logisticians in Germany and Central Europe. I am sure it will generate lots of interest,” Rösch concluded.