Could Computer Vision Fuel a Revolution in Holistic Supply Chain Management?

Businesses throughout many different sectors have spent much of the past year attempting to adapt to a new age of supply chain management that has challenged decision-makers to overcome significant challenges and new risks at scale. 

At a recent panel discussion on the latest annual State of Logistics Report from the Council of Supply Chain Management Professionals, Doug Cantriel, head of North American transportation and modernization at Ford, claimed that ‘normalcy’ won’t be returning to US supply chains. 

With more companies having to adjust rapidly to geopolitical uncertainty, from the war in Iran to an increasingly complex tariff environment, we’re seeing a greater emphasis than ever before on building innovative and flexible logistics networks. 

Worryingly, there’s plenty of evidence that companies are struggling to out-innovate their supply chain challenges. According to a survey from BSI, as many as 81% of companies claim that they’re currently or about to warn customers that shortages, delays, or dependency risks could impact their supply chains. 

More than a third (36%) are actively planning to increase their prices to offset costs over the next six months, according to the findings. 

For firms that are based in highly competitive markets, the prospect of price hikes on products and services could be fatal at an operational level. But growing use cases in computer vision could be the breakthrough that many have been hoping for. 

As a subset of AI, computer vision is already transforming supply chain management by replacing manual workflows with real-time, automated visual processing. 

Working alongside AI-powered cameras throughout warehouses, loading docks, and transit networks, businesses have the ability to close the gap between recorded digital inventory and physical reality in a way that could create a 20% boost to cost savings while reducing picking errors by 30%. 

With these figures in mind, let’s take a deeper look at how computer vision is already making its mark in supply chain management: 

Real-Time Inventory Monitoring

While traditional cycle counting is dependent on manual scans that can only ever represent a single snapshot in time, computer vision is paving the way for a continuous and dynamic view of warehouse inventory. 

This is made possible by the autonomous qualities of AI. With the use of fixed cameras and overhead drones, barcodes and OCR labels can be automatically scanned in a way that immediately addresses inventory drift. As a result, potential issues can be rapidly identified, improving forecasting accuracy and allowing for rapid responses to disruptions. 

Obtaining a more holistic real-time overview of supply chains also means that computer vision can quickly flag misplaced or lost pallets, stamping out the threat of stockouts or double-counting errors. 

The technology also helps to analyze your physical storage footprint, guiding teams on how to maximize rack utilization for better capacity levels. 

Autonomous Compliance

Computer vision also ensures that businesses maintain a level of compliance without requiring constant human oversight, which can be a significant asset throughout industries where regulatory requirements can mean keeping track of many different locations. 

Thanks to innovations like AI Photo Insights, compliance no longer has to rely on the hunches of individuals, and large teams can maintain the same safety standards that are laid out by regulators in every relevant jurisdiction throughout the chain, preventing unwanted disruptions

In compliance checks, the same analysis criteria can be applied across every image captured, making findings more consistent from one inspector to the next, which can be critical in keeping documentation standards from drifting across teams, shifts, or warehouses. 

The technology can not only manage PPE requirements across supply chains, but cameras can also map out surroundings to assist forklifts and yard trucks in navigating their surroundings without obstacles or pedestrians. 

Should any near-miss incidents or layout bottlenecks emerge, they can be automatically recorded with visual evidence to help optimize floor layouts and safety protocols. 

Rapid Sorting

Speed plays a major role in supply chain efficiency, and manual scanning can lead to significant bottlenecks during peak hours. However, advanced vision infrastructure can eliminate human lag from conveyor systems, allowing for a far more efficient process throughout. 

One of the most impactful computer vision applications is scan tunnels, where high-speed cameras capture data from moving packages at multiple angles, achieving high read rates even on damaged labels. 

Artificial intelligence applications can also recognize package dimensions and weight attributes instantly to route shipments to the correct dispatch bays. Additionally, dock door verification scanners can lean on computer vision to confirm that the correct item is entering the right trailer, eliminating costly downstream shipping errors for all parties. 

The Future of Supply Chains

While it’s fair to say that the challenges facing supply chain management have become increasingly complex in recent years, the technology that’s helping to support businesses has evolved at such a rapid pace that new efficiencies are helping to drive down costs while scaling up output and safety throughout global chains. 

The future of supply chain management may still be prone to external pressures, but with the assistance of computer vision, there are more ways for businesses to out-innovate these growing challenges. 

Looking ahead, the widespread adoption of AI can pave the way for a far more holistic approach to overseeing supply chains, with logistics set to benefit across the board.