Supply chains continue to navigate ongoing disruptions, tighter margins, and rising expectations. APQC research shows that organizations making data management a priority are outperforming their peers. The difference is not access to data. It is how that data is governed, managed, and used.
Getting Governance Right
Strong data governance creates the foundation for effective supply chain analytics and data management.
- Centralized governance models remain the most common approach.
- Hybrid models are gaining traction by balancing enterprise standards with functional flexibility.
- Most organizations keep governance in-house to maintain control and accountability.
- Clear ownership improves data quality, consistency, and trust across teams.
Why Good Data Management Matters
Reliable data turns analytics into a business advantage, not a bottleneck.
- Improves productivity by reducing time spent validating and correcting data
- Enables more accurate forecasting and planning
- Supports faster, more confident decision making
- Reduces costs by eliminating inefficiencies and rework
- Strengthens customer satisfaction through better service and reliability
From Emerging Technology to Strategic Lever
Analytics has moved beyond experimentation and is now a core supply chain capability.
- Leading organizations embed analytics into daily operations
- Data is used proactively to anticipate risk and disruption
- Insights support both short-term execution and long-term strategy
- Analytics maturity directly correlates with stronger supply chain performance
Learn more and explore 3 keys to future success in supply chain analytics in APQC’s Analytics in Action: How Supply Chains are Winning with Data.