CPG Supply Chains Are Shifting
Specific forces are reshaping how CPG supply chains operate, compete, and create value, according to a recent analysis from Kearney. These trends reveal that "supply chain strategy must evolve to support growth, resilience, and enterprise-wide performance."
Here are a few (excerpted from the article).
Fast-changing consumer demands require supply chains built for speed
The explosion of choice across all product categories, combined with economic uncertainty, has sharpened consumer focus on price and quality. In the United States alone, roughly 30,000 new products launch each year, intensifying competition across categories. When paired with tariff-related cost increases and inflation, price and quality emerge as the defining factors in consumers’ purchase decisions.
Supply chains are adapting by employing a customer-centric mindset, linking supply chain strategy to product design and innovation. A collaborative approach that brings supply chain into the design process early can unlock cost efficiencies and better meet consumer expectations, especially as CPGs move toward rationalized portfolios. The result is a supply chain built to effectively leverage product platforming and other design choices to dramatically increase speed to market.
AI and digital technologies are helping make this integration more intelligent. For example, digital twin technologies can create a virtual replica of a product or system, which can enable design teams to see downstream constraints (for example, manufacturability, cost, sourcing risk) earlier in the process.
Global instability demands building resilient networks
The list of variables driving macro instability continues to grow: trade tensions and shifting tariffs, rising nationalism/anti-globalism, political instability, and ongoing market volatility as GDP growth slows globally.
In response, supply chain leaders are reinforcing network and supplier resilience. This includes expanding supplier bases with greater geographic diversity or qualified substitutes in case of single country sources; actively monitoring risk exposure across the full value chain, including nth-tier suppliers; and identifying where nearshoring or regional sourcing can reduce disruption risk. Resilience also depends on transportation alternatives, backup routes, and elastic production capacity that can scale with demand.
Real-time scenario planning, predictive risk scoring, and continuous monitoring paired with early warning systems are helping CPG companies shift supplier risk management from a largely reactive, periodic process to a more proactive, dynamic, and intelligence-driven activity.
A global CPG company recently implemented an advanced supply chain risk management system that integrates P&L data with external market signals. By shifting to continuous monitoring, the company can now surface emerging supplier risks in real time and act before they escalate.
Smart tech is quickly becoming table stakes
AI-powered sensors and analytics, IoT, and robotics are already enhancing manufacturing and supply chains in 30 percent of organizations, according to a 2025 COO survey by Kearney. Cybersecurity requirements ramp up with increasing digitization.
Let’s look at the planning function as an example. In particular, the availability of advanced technology for planning and forecasting means zero tolerance for losses driven by inaccurate forecasts and manual planning errors. As adoption accelerates, the opportunity to gain advantage narrows. Many companies are now moving to build robust data ecosystems that support more accurate planning, better forecasting, and faster decision-making. Investments in cloud-based data platforms, advanced data management practices, and cross-functional collaboration are helping reduce losses tied to fragmented information, poor planning, and manual error.
More broadly, adjusting to this new baseline of performance requires a fit-for-purpose AI strategy and operating model, but many organizations struggle to move beyond isolated pilots or narrow use cases. Challenges often include fragmented or disconnected data and ownership, unclear ROI, and talent and skill gaps. Overcoming those barriers starts with a focused road map and cross-functional alignment on where AI can create real business value. Critical elements of this road map include:
- Analytics aligned to business objectives, not isolated use cases
- Automation of basic workflows
- AI integration with ERP, BOM, etc., to drive decisions
- A skilled, AI-ready workforce