Industry News

Extreme weather events, labor shortages, international conflict and transport bottlenecks are all part of everyday life for manufacturing companies. They’re also the cause of the current volatility across today's supply networks — so much so that the global supply chain pressure index recently recorded its sharpest monthly increase in four years. Supply chain leaders within the manufacturing industry can’t eliminate these risks, but they must start to significantly improve how quickly they identify, assess and respond to them. 

Despite rapid advances in digital technology, a deluge of operational, supplier and logistics data needed to make supply chain decisions stands in the way. Why? Because these organizations continue to rely on fragmented systems and manual processes. As a result, they struggle to transform these insights into timely intelligence. 

This is where a new dynamic approach to supply chain management can help organizations react in real-time and adapt as conditions evolve.

The Visibility Gap

Industry estimates suggest that around 80% of U.S. manufacturing facilities still operate with little or no automation, limiting their ability to create a real-time view of inventory, supplier performance, logistics movements and production capacity.

When a disruptive event occurs, decision processes often rely on manually compiling information from multiple sources or engaging external consultants to assess changing conditions. By the time mitigation plans are agreed, supplier lead times, freight availability or commodity prices may already have shifted again.

This reactive approach is increasingly difficult to sustain. Transportation alone can account for around 10% of manufacturing revenue, so even modest improvements in visibility, planning and execution can deliver meaningful financial returns while strengthening resilience against future disruption. How, then, can organizations make the shift to continuous supply chain intelligence to stay one step ahead of disruptive events?

A Strong Digital Foundation

Cutting-edge technologies are supporting and enhancing the shift to continuous supply chain intelligence. There’s the renaissance of IoT, accelerated by advances in AI. The global market for manufacturing artificial intelligence of things (AIoT) is expected to reach a value of $211.7 million by 2030, as more organizations experiment with the technology’s ability to transform raw data from connected assets into intelligence that improves machinery performance, processes and safety outcomes. For instance, sensors can continuously track the location and condition of goods in transit, providing real-time visibility. This enables timely intervention if a shipment is delayed or disrupted in the event of supply chain issues.

But let’s not forget digital twin technology, which allows organizations to visualize and simulate any product, plant or factory in its full context, in real-time. North America is expected to dominate the digital twin market with 41% of the share by 2035. Digital twins allow manufacturers to test the impact of supplier changes, routing adjustments or inventory shifts in a controlled environment. 

But technology’s role in enabling the shift to continuous intelligence doesn’t stop there. The aim today is not to predict every disruption, but for manufacturers to understand their available options at any given moment and act decisively when conditions change.

AI has the ability to extract and structure data, making it more coherent and useable, even when it has been created or managed in siloed ways. Yet manufacturers can go one step further by using AI-enabled supply chain modeling and simulation tools, which can use data, even where gaps remain, to build and test scenarios across the supply chain. This allows manufacturers to see which parts of the supply chain are more or less resilient, and how different scenarios are likely to play out.

Say Goodbye to Outsourcing

Manufacturers don’t need to outsource this supply chain intelligence. Rather than relying on third-party or consultant-led, periodic analysis, they can use AI-enabled supply chain intelligence tools internally on a regular basis to explore scenarios, test assumptions and better respond to change.

For example, manufacturers can embed AI-driven transport planning within their enterprise resource planning systems in order to move away from manual, spreadsheet-based decision-making and toward intelligent optimization across trade lanes. Combined with zero-touch automation, this can minimize booking errors, lower operational costs and provide real-time shipment visibility. The integration of freight-audit capabilities can also validate every invoice at the line-item level and highlight billing discrepancies and manage dispute workflows.

When it comes to understanding the continuous supply chain intelligence payoff, research shows 95% of supply chain executives believe their CEO recognizes the supply chain’s impact on profitability. Yet this outlook overlooks the other benefits that continuous supply chain intelligence can bring to the U.S. manufacturing industry.

Not only does an “always-on” approach improve operational resilience by enabling faster responses to disruption, it also supports sustainability goals by identifying more efficient and responsible supply chain choices. 

The manufacturers that succeed in today’s disruptive environment will be those that can adapt faster than change unfolds. Continuous supply chain intelligence enables organizations to anticipate emerging risks, make informed decisions sooner and stay ahead, whatever the source of disruption.

Source: www.supplychainbrain.com/