World’s First Artificial Intelligence-based On Time Delivery Predictor

JAGGAER Launches World’s First Artificial Intelligence-Based On-Time Delivery Predictor

  • Innovation
  • Press Release

Carl Zeiss wants to be ramp-up customer for JAGGAER OTD Predictor.

RESEARCH TRIANGLE PARK, NC, March 12, 2019:  JAGGAER, the world’s largest independent spend management company, 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 management to mitigate risks of disruptions to production flows and reduce the costs that these can cause. It will be available for view at the tenth BME e solution days, which takes place in Düsseldorf on 12 to 13 March 2019. JAGGAER is a premium partner.

ZEISS, the internationally leading technology enterprise operating in the fields of optics and optoelectronics, 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! said 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,” he adds. “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.


 

About JAGGAER: Global Spend Management Solutions

JAGGAER is the world’s largest independent spend management company, with more than 2,000 customers connected to a network of 3.7 million suppliers in 70 countries, served by offices located in North America, Latin America, throughout Europe, the United Kingdom, Australia, Asia and the Middle East. JAGGAER offers the industry’s most comprehensive SaaS-based spend management and supply chain solutions with advanced Spend Analytics, Sourcing, Supplier Management, Contract Lifecycle Management, Procure-to-Pay, Supply Chain Collaboration and New Product Introduction capabilities. JAGGAER has pioneered spend management solutions for over two decades and continues to lead the innovation curve by listening to customers and analyzing the market. Our solutions are trusted by the world’s largest manufacturing, education, health care, retail, consumer package goods, logistics, construction, utilities companies and public service organizations.

ABOUT ZEISS

ZEISS is an internationally leading technology enterprise operating in the fields of optics and optoelectronics. In the previous fiscal year, the ZEISS Group generated annual revenue totaling more than 5.8 billion euros in its four segments Industrial Quality & Research, Medical Technology, Consumer Markets and Semiconductor Manufacturing Technology (status: 30 September 2018).

Related Blog Posts

We use cookies to ensure that we give you the best experience on our website. This includes cookies from third party social media websites and advertising cookies that may analyze your use of this site. Learn more