A proactive supply chain risk posture is increasingly necessary — and finally possible

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There has been a steady stream of supply chain crises in the news this spring, from shipping delays in the Middle East due to regional conflict to the halting of semiconductor production in Taiwan and the upending of imports and exports out of Baltimore. 

Each unexpected event serves as a reminder to stakeholders across the supply chain that disruption is inevitable — but it doesn’t have to be unpredictable. 

Advanced technological capabilities powered by artificial intelligence and cognitive computing have unlocked the ability to proactively forecast when and where disaster and disruption are likely to strike. 

Having been responsible for global operations, overseeing tens of thousands of suppliers at Fortune 500 companies, it has become increasingly clear to me that organizations need to be able to predict and get ahead of disruption if they want to continue to grow and thrive in this risk landscape. 

There’s simply too much complexity and risk to remain reactive. 

A rapidly proliferating global regulatory regime that includes the US Uyghur Forced Labor Prevention Act, Canada’s Forced and Child Labour in Supply Chains Act, and the German Supply Chain Act further implicates supply chains and creates even more urgency around the need for a fundamental shift in the way compliance, risk, procurement and supply chain professionals think about risk management. 

There are three key gaps that organizations and governments need to bridge to modernize their risk posture.

From incomplete data aggregation to real-time data creation

Regarding supply chain data, many organizations are still completely reliant on third-party data aggregators, registries or supplier surveys. But this kind of data provides an incomplete and dated risk picture at best — and an inaccurate risk picture at worst. Risk, procurement and compliance professionals then make serious and consequential decisions for their organizations using this data. 

In order to make the kind of decisions that move the needle for their organizations — whether that’s shoring up alternative suppliers, avoiding a parts crunch, steering clear of regulatory violations, or illuminating human rights abuses — supply chain professionals need dynamic, real-time and comprehensive supplier data. 

From static information to informed insight

With a complete picture of risk, organizations can then make the jump further down the decision curve — moving from static data that needs to be verified, validated, and analyzed to insights that can be quickly converted into action and impact. 

This jump can be achieved using generative AI that’s capable of digesting unstructured data in addition to structured data. With advanced cognitive computing, the validation process can also be automated and then fed into mapping tools. When combined, this kind of informed insight surfaces risks that are real and relevant. It also allows organizations to see where chokepoints are forming, where shortages are hiding, and where the risk of future disruption is high. 

From supplier analysis to value chain intelligence

Many legacy risk management programs and technology vendors remain narrowly focused on suppliers, but the most sophisticated organizations understand that today, it’s really about value chains. Many organizations have an ecosystem of suppliers that provide parts and rely on a set of materials. However, across entire industries, many organizations are consuming the same critical materials — be it gallium, cobalt, or lithium — at the base.

This makes it much harder for companies to assess and predict how larger market fluctuations will affect them with a traditional, solely supplier-focused approach to risk management. However, AI solutions that incorporate regulatory mapping, firmographic data and holistic associations across organizations and their value chains unlock the ability to predict and prepare for supply chain events.

While the mandate for risk, compliance, procurement and supply chain professionals is broader than ever, new advancements in capabilities, analysis and automation are expediting decision-making in a way that wouldn’t have been possible just a few years ago. This new generation of AI solutions is also uniquely scalable in terms of deployment, cost and, most importantly, their ability to rise to the challenge of an immeasurably complex risk landscape.

FEATURED COMPANY

Exiger

Mary Luciano, VP, Head of North America Delivery and Proactive Intelligence

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