The modern supply chain is more than a cost center—it is a critical driver of competitive advantage. Yet, business leaders face a complex and volatile environment where geopolitical instability, supply disruptions and shifting consumer demands challenge traditional supply chain models. In fact, industry reports suggest that 70% of supply chain professionals expect risks to escalate in the coming years.
Chief supply chain officers (CSCOs) must go beyond cost-cutting and logistics management. They need to design resilient supply networks, integrate real-time data for smarter decision-making and embrace intelligent technologies to navigate uncertainty. The challenge is twofold: first, balancing diversification and localization to reduce risk while maintaining efficiency; and second, overcoming data fragmentation and decision overload in an era where more data doesn’t always mean better insights.
This article explores three strategic levers—diversification, data integration and decision intelligence—that supply chain leaders should embrace to turn challenges into opportunities and build a future-ready supply chain.
1. Derisk complexity with diversification.
Businesses today must balance diversification and localization to manage risks and optimize operations. According to The Economist Impact Trade in Transition 2025 report, businesses are balancing dual priorities of diversification and localization. In fact, nearly 46% of businesses are diversifying to enter new markets and hedge against disruptions, while 42% are localizing for reduced transportation costs and greater oversight. When it comes to choosing suppliers, 75% of businesses are spreading risk and increasing resilience across more partners.
Resilience can also be built by additional buffers of inventory or diversified materials to be used as inputs. Delivering enhanced customer experience could also mean customized products and channels.
As cited in an EY case study, a leading electronics supplier, overly reliant on Asian manufacturing, faced shortfalls that disrupted operations. With most of its customers in the US, the company near-shored production, optimizing its supply chain. This move cut delivery times, lowered carbon emissions and reduced excess inventory, enhancing both efficiency and sustainability.
2. Integrate organizational capabilities with data.
In their 2025 report, Gartner recommends that CSCOs consider five supply chain characteristics to deliver business value: agility, resilience, strategic alignment, regionalization and ecosystem collaboration. Achieving this requires investments in technology, sustainability, talent and business models to enhance customer satisfaction, revenue, and performance.
These investments align with four strategic paths:
• Design Path: Innovates on business models and simplifies products.
• Decision Path: Uses advanced technologies to optimize supply chain tasks.
• Deferment Path: Delays new capabilities to maintain stability and control costs.
• Durability Path: Focuses on sustainability and risk management for long-term resilience.
Technology is the key enabler, and data powers decision-making. CSCOs play a vital role in:
• Understanding supply chain data sources
• Ensuring data accuracy
• Integrating data flows across teams
• Designing feedback loops for smarter decision-making
A robust DataOps system in the supply chain refines MLOps for AI-driven operations, enabling probabilistic planning, real-time sustainability tracking and advanced analytics to balance trade-offs effectively.
As cited in a DHL case study, a multinational company with a significant number of vending machine outlets needed to manage brand assortment within the machines more efficiently. The company needed to balance its target sales volume and gain market share of brands. Another priority was to avoid “out of stocks” and “dead slots” within the vending machine.
Additionally, it was dealing with complexity within contractual obligations with different manufacturers. The company consolidated its data from vending machines to design a data model to get visibility on the hundreds of brand assortments and interactions between different data pools. Web-based technologies leveraged data in simulations and predicted outcomes. Benefits included getting insights into consumer buying preferences, developing targeted assortments and predicting logistic costs. Data integrated from vending machines thus helped with decision-making across different disciplines within the organization.
3. Leverage intelligence platforms for real-time decision-making.
While organizations invest in AI for supply chain efficiencies, they also need to plan for the explosion of data, predicted to reach more than 2,000 zettabytes by 2035. One of the consequences of data overload is indecision paralysis. According to Oracle, more data means that business leaders face a 10-times increase in the number of decisions that need to be made, leading to alert fatigue, manual analysis and indecision, all contributing to operational inefficiency.
To address these issues, Gartner experts believe that supply chain planners will prioritize technologies such as decision intelligence platforms (DIPs) to deliver advanced decision intelligence and automated decision-making. DIPs are AI-driven systems that integrate data analytics, automation and predictive modelling to enhance decision-making. Unlike traditional business intelligence tools, DIPs enable supply chain leaders to simulate and anticipate disruptions and optimize operations dynamically.
Aboitiz, one techglomerate we worked with that has 44 business units across South East Asia, spanning a variety of industries from power generation, banking, food and land, is transforming its century-old traditional infrastructure to an AI-powered tech enterprise. The scale of change creates technical challenges of maintaining security and operations across legacy systems and new digital systems. Continuous monitoring of data movement, across the enterprise, identifying patterns and detecting anomalies is critical. An integrated monitoring system that flags potential security implications immediately is a must-have.
It's time to build a resilient, data-driven supply chain.
In a volatile landscape, supply chain leaders must go beyond cost-cutting to build resilient, data-driven operations. While diversification is a priority, true resilience requires balancing supplier networks, integrating data and leveraging AI-driven decision intelligence platforms to turn data overload into actionable insights.
The challenge is no longer just adapting to short-term shocks but embedding long-term resilience through smarter strategies and scalable technology adoption. Businesses that embrace this shift won’t just survive—they will thrive with a competitive edge.
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This article was originally published on Forbes on April 11, 2025