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How IoT and Artificial Intelligence Drive Smarter Decision-Making in Supply Chain Optimization?

Rapid decision-making, streamlined cycle times, efficient operations, and continuous enhancements define the modern supply chain landscape. All of this is being facilitated by technology-backed processes, especially those that constitute the convergence of IoT and AI.

Dwight Klappich, VP Analyst at Gartner, says that “supply chain organizations must become more flexible, and the solution is digitalization.” This explains why the global Industrial Internet of Things (IIoT) market is expected to grow to $3.3 trillion by 2030, up from $544 billion in 2022. 

The burgeoning landscape of IoT and AI is set to optimize supply chain functions, and for all the good reasons. In this article, let’s look at their impact in isolation as well as their synergistic influence.

The IoT Influence on Supply Chain Optimization

IoT’s impact on smart decision-making within supply chain optimization is multi-faceted. Consider this:

  • IoT-enabled sensors embedded in various nodes of the supply chain capture a wealth of data related to inventory levels, temperature, humidity, location, and more. 
  • This data is seamlessly transmitted to a central platform where it is processed and analyzed.
  • The extracted insights allow supply chain managers to proactively identify bottlenecks, foresee potential disruptions, and optimize routes, thereby minimizing delays and enhancing overall efficiency.

Real-time IoT monitoring offers actionable insights during goods transit. Vital for sensitive or perishable goods, monitoring parameters like temperature, humidity, etc., ensure product quality across the supply chain.

Furthermore, IoT integration enhances transparency and collaboration. Real-time data sharing among stakeholders—suppliers, manufacturers, distributors, and retailers—encourages joint efforts. This shared visibility guarantees consistent, accurate information, reducing errors and delays.

How Does AI Help?

The utilization of AI-powered solutions within the supply chain and logistics ecosystem is centered around problem-solving. Consider this; an IoT-enabled and AI-powered opportunity transpires when these technologies are leveraged for predictive analytics. By leveraging historical data and advanced analytics programs, organizations anticipate demand, supply gaps, and maintenance needs. These predictive models enable proactive actions associated with:

  • Adjusting schedules
  • Reallocating resources
  • Optimizing inventory to match market shifts

That said, here’s how the combination of IoT and AI helps drive informed decision-making across the supply chain:

Remote Asset Tracking

IoT devices installed across assets ensure that timely data flows into the enterprise systems (like a centralized cloud network) for enhanced asset visibility. AI capabilities come to the fore for making sense of this data. How does this pan out? Well, AI algorithms help:

  • Identify if there are any anomalies in the performance or perhaps certain deviations from the usual operational patterns of the assets.
  • Inform the operators about the possible issues so that they can take proactive action.

Also Read: How to Future-Proof Your AI Adoption Strategy

Warehouse Efficiency

An efficient warehouse is integral to a successful supply chain operation. But with so many moving parts, it might prove difficult for organizations to streamline end-to-end operations — precisely where AI-powered robotics becomes a key enabler of:

  • Optimizing picking routes
  • Coordinating the workflows and movements of robots and humans across the establishment
  • Automating repetitive tasks
  • Keeping workers safe via the implementation of technologies like computer vision

All these applications are powered by real-time data that enterprise systems receive from various IoT sensors and cameras installed throughout the warehouse.

Accurate Inventory Management

Accurate inventory management is critical for ensuring the proper flow of items in the supply chain and preventing inventory costs from soaring. Cisco has previously predicted that IoT can save about £1 trillion in productivity costs. Another study has outlined how inventory costs can be cut down by 15% through the efficient use of IoT.

What does this efficient use look like? In concrete terms, IoT devices help keep track of product location and automate data generation. This data is fed to AI algorithms which help provide a comprehensive insight into the inventory levels and how inventory management can be influenced by market changes. 

Predictive Asset Maintenance

Studies outline that manufacturers have to cover the high costs of unplanned downtime, which turns out to be $50 billion a year.

Predictive maintenance can reduce equipment downtime, and improve the quality of products, while at the same time cutting costs. IoT-enabled predictive asset maintenance solutions can help enterprises with real-time monitoring of assets. This not only helps ensure that the equipment is being monitored 24/7 but also reduces the chances of human errors seeping in.

Optimize Your Supply Chain with Ascentt

From automating tasks to amplify worker productivity to reducing machine downtime and maintenance costs, the convergence of AI and IoT proves pivotal in allowing enterprises to streamline their supply chain operations and make proactive decisions, especially during challenging times.

At Ascentt, we help enterprises achieve smart decision-making across the supply chain by creating a robust technology infrastructure that’s capable of drawing the most pertinent data and making sense of it for democratized and end-to-end stakeholder visibility.

Our expertise in AI, ML, data science, and IoT equips us to lay the foundation of informed decision-making across the entire supply chain. Interested in learning more about how the convergence of AI and IoT can ensure the success of your supply chain initiatives? Get in touch today!

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