By Martin Tombs, VP of Move to Cloud, at Qlik
In today’s hyperconnected and unpredictable world, supply chains are more critical—and vulnerable—than ever. From raw material shortages to geopolitical instability, shifting consumer demands and even natural disasters, disruptions can derail operations and damage trust.
But there are also opportunities to rethink how we manage and mitigate risk. The solution lies in using AI and predictive analytics to more intelligently manage supply changes and mitigate disruption.
Supply chains today are increasingly complex, and hard to manage. AI is becoming essential to access data across entire supply chains in real-time and identify risks long before they escalate. 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.
AI also allows companies to model scenario, simulate potential risks and pre-emptively design response strategies. 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.
To go one step further, predictive AI can help to combat net-new challenges, such as the impact of climate as it becomes more unpredictable – or as seen with the Covid-19 pandemic.
Penske, a leader in logistics and supply chain management, is a great example of how data analytics can support supply chain management. Penske faced the challenge of integrating data from disparate sources—fleet management systems, logistics platforms, and customer demand data—to improve decision-making. With Qlik’s analytics platform, Penske has consolidated all its data into a single, actionable view.
AI-driven predictive analytics helped Penske anticipate issues before they occurred, whether it was flagging vehicles in need of maintenance, predicting delivery delays, or preparing for demand spikes. These insights enabled Penske to optimise routes, reduce operational costs, and improve delivery times—which helped the business to become more resilient and keep customers happy.
Whitworth’s, a major UK supplier of dried fruit and nuts, has also used data analytics to manage its supply chain and mitigate risk. With Qlik, real-time insights have helped to respond proactively to disruptions, pool inventory to meet demand during peak times, and decided the most effective manufacturing locations. Whitworths has added features like inventory alerts and real time shipping updates, which can be accessed by everyone from factory workers to executives so everyone has a better understanding of the supply chain status. Now, Whitworth’s has enhanced relationships with both customers and suppliers and can better manage an unpredictable supply chain landscape.
Being able to understand and respond to events that impact supply chains is no longer a luxury; it’s a business imperative. Companies that embrace AI and predictive analytics now will be better equipped to weather future storms – some literal – while those that rely on outdated, reactive methods risk being left behind.
The future of supply chain management is one of anticipation, not reaction. So my advice to leaders is this: Start small but think big. Identify a critical pain point in your supply chain where predictive insights could make a tangible difference. Build from there, ensuring that your team has the tools and training they need to fully leverage these capabilities.
