Martin Tombs, Field CTO for the EMEA region at Qlik, says the ability to anticipate disruptions has become a defining factor in organisational success
In an era defined by volatility and unprecedented challenges, supply chains face mounting pressures from all directions.

The ability to anticipate and mitigate disruptions has become a defining factor in organisational success.

“Supply chains are more critical — and vulnerable — than ever,” asserts Martin Tombs, Field CTO for the EMEA region at Qlik. “From raw material shortages to geopolitical instability, shifting consumer demands and even natural disasters, disruptions can derail operations and damage trust.”

Yet amidst these challenges lie significant opportunities to revolutionise supply chain management through advanced technologies, as Martin explains: “The solution lies in using AI and predictive analytics to more intelligently manage supply changes and mitigate disruption.”

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The growing complexity of supply chains
Today’s supply chains have evolved into intricate networks spanning numerous continents, involving numerous stakeholders and touchpoints — making traditional management approaches increasingly inadequate.

“Supply chains today are increasingly complex and hard to manage,” Martin notes.

This complexity creates vulnerabilities that can quickly cascade through operations when disruptions occur.

The response, Martin claims, is emerging in the form of advanced AI applications.

“AI is becoming essential to access data across entire supply chains in real-time and identify risks long before they escalate,” he continues. “For example, machine learning algorithms can flag early warning signs, like raw material shortages or port congestion, and give companies a chance to intervene before bottlenecks arise.”

Beyond reaction: The predictive revolution
What truly distinguishes next-generation supply chain management is the shift from reactive to proactive approaches.

This transformation is being driven by predictive capabilities that allow organisations to anticipate challenges before they materialise.

Martin Tombs, Field CTO for the EMEA region at Qlik
“AI also allows companies to model scenarios, simulate potential risks and pre-emptively design response strategies,” Martin says.

“Predictive analytics takes companies beyond merely reacting to disruptions. By analysing historical and real-time data, it’s possible to forecast future demand patterns and streamline operations.”

This predictive capacity extends beyond known challenges to emerging threats.

Martin adds: “To go one step further, predictive AI can help to combat net-new challenges, which are emerging as climate impact becomes more unpredictable – or as we saw with the COVID-19 pandemic.”

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