PUBLISHER: Mordor Intelligence | PRODUCT CODE: 2121673
PUBLISHER: Mordor Intelligence | PRODUCT CODE: 2121673
According to Mordor Intelligence, the supply chain big data analytics market size is expected to grow from USD 11.10 billion in 2025 to USD 13.20 billion in 2026 and is forecast to reach USD 31.44 billion by 2031 at 18.95% CAGR over 2026-2031.

This report is Segmented by Component (Solution, Service), End User Industry (Retail, Transportation and Logistics, Manufacturing, Healthcare, Other End-User Industries), Deployment Model (On-Premise, Cloud), and Geography. The Market Forecasts are Provided in Terms of Value (USD).
Retailers manage store, e-commerce, marketplace, and direct-to-consumer flows simultaneously, generating multi-petabyte data volumes that require real-time inventory algorithms. Walmart and Target each process more than 2.5 petabytes of supply data daily, prompting adoption of integrated planning platforms that synchronize demand signals and cut out-of-stock incidents by 30-40% .
Logistics operators deployed more than 1.2 billion IoT devices in 2024, each sending 25-30 data points per minute. Advanced analytics predicts equipment failures, optimizes fuel through live routing, and assures cold-chain integrity, delivering 20-30% maintenance cost cuts and 95% compliance for temperature-sensitive freight.
Enterprises juggle 15-25 legacy systems with incompatible schemas, leading to six-to-twelve-month integration delays and forcing teams to spend up to 60% of analytics budgets on data cleansing before realizing value . Data quality issues, such as duplicate records, missing values, inconsistent naming conventions, and outdated information, can diminish analytics accuracy by 20-30%. This undermines confidence in both predictive models and prescriptive recommendations.
Other drivers and restraints analyzed in the detailed report include:
For complete list of drivers and restraints, kindly check the Table Of Contents.
Solutions captured 61.55% of the supply chain big data analytics market share in 2025 by bundling procurement planning, manufacturing analytics, and transportation optimization into unified suites. Manufacturing analytics modules gain traction as Industry 4.0 initiatives link shop-floor sensors to predictive models. Transportation tools are equally in demand as e-commerce growth multiplies last-mile deliveries.
The services segment grows at a 19.32% CAGR as enterprises call on system integrators for data migration, model calibration, and round-the-clock support. Hybrid cloud and generative-AI workloads amplify complexity, widening the gap between packaged software and client customization needs.
North America led with 42.40% of the supply chain big data analytics market share in 2025, owing to early digital-twin pilots and a mature cloud landscape. US manufacturers extend analytics into nearshored Mexican plants to improve quality yields, while Canadian energy operators optimize pipeline maintenance through predictive models.
Asia Pacific is growing at a 21.15% CAGR. China funds smart-factory roll-outs and cross-border e-commerce corridors that demand high-speed analytics. India accelerates retail and pharma use cases, whereas Japan and South Korea refine automotive and electronics supply chains through AI-powered scheduling. Government incentives and cloud-native startups make adoption cost-effective.
Europe maintains steady uptake under stringent sustainability and data-privacy rules. German auto and machinery exporters rely on plant-level analytics to protect global competitiveness. UK retailers integrate AI demand-planning tools to navigate volatile consumer sentiment, while EU-wide traceability laws spur investment in blockchain-enabled visibility platforms.