Today’s supply chain is overwhelmingly complex and the “Amazon effect” is putting more pressure on retailers, manufacturers, and 3PLs than ever before. It’s clear that physical scale and buffer stock are no longer the winning formula, and enterprises must utilize data intelligence and AI to transform their supply chains.
For our business, the rapid evolution toward a data intelligent supply chain is fundamental because we started our company to build the AI operating system that the supply chain needs, and we’re equipping shippers and 3PLs with true data intelligence.
We’re talking about utilizing machine learning and AI in two specific ways. First, to solve the industry’s core data problem by ingesting raw EDI data and automatically cleaning, structuring, and canonicalizing data around bookings, container movements, and shipment events. With proprietary machine learning techniques, we’re seeing the “dirty data” problem effectively solved, and shippers are able to achieve a level of visibility they’ve never been able to achieve.
Shippers and 3PLs are utilizing AI-based applications to surface and prioritize which shipments are at highest risk of exception, provide confidence intervals with regard to likelihood of delay, and more easily communicate historical, real-time, and predicted shipment statuses to customers and logistics service providers.
In summary, macro-economic pressures are putting unprecedented pressure on retailers, manufacturers, and 3PLs to digitally transform. And due to the proprietary technology coming out of Silicon Valley, new levels of efficiency, personnel productivity, differentiated service, and profitability are possible and here today. Luckily, as the supply chain becomes increasingly complex, adoption of AI capabilities will enable enterprises to transform instead of being disrupted.