Predictive analytics tool leverages AI to identify how a supplier will perform by analyzing past events and on-time delivery data
Resilinc Corporation, the world’s leading supply chain monitoring, mapping, and resiliency solution, is pleased to announce the launch of its Predictive Purchase Order (PO) On-Time Delivery solution. The artificial intelligence (AI)-powered tool predicts how a supplier will perform – in the face of disruption – by analyzing past events and on-time delivery data. Armed with this data, organizations can plan for and mitigate risk before disaster strikes, protecting continuity of supply and avoiding execution delays.
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“To ensure supply chain resiliency, companies need to be able to detect problems promptly, understand the impact, and act quickly. The way to achieve this is by leveraging AI and machine learning to ultimately reach a level of automation where decisions are made, based on data by machines, in a split second,” said Resilinc CPO and co-founder, Sumit Vakil. “Our Predictive PO On-Time Delivery solution is a big first step to achieving hyperautomation, freeing up supply chain pros to focus on developing more proactive supply strategies, versus taking a reactive approach.”
In a typical supply chain disruption scenario, all mitigation activity happens after the disruption occurs; the chances of recovery are significantly reduced even though this is where most companies focus their efforts. The first-of-its-kind prediction tool leverages AI, historical data, and machine learning to: send alerts about a new, potentially disruptive event anywhere in the world; predict impact likelihood; predict which suppliers are most at risk of delivering late, and by how long; and identify how affected suppliers will perform and propose a risk-mitigation action plan.
“Predictive PO On-Time Delivery uses Resilinc’s EventWatch AI and Multi-tier Mapping capabilities to scan millions of news sources to identify disruptive events and from there identify the region or suppliers that could potentially be impacted,” said Yogesh Akolkar, Resilinc’s Vice President of Engineering. “It then uses new PO delay predictor AI to look at currently open purchase orders and the on-time delivery metrics of those suppliers over the past 10 years, when faced with the same disruptive event. Users are then informed of the potential delay that could be caused for each PO, due to this event.”
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