A category manager at a healthcare company recently described a familiar situation. While preparing for upcoming sourcing initiatives, her team reviewed supplier records they assumed were in good shape. Instead, they uncovered duplicate profiles, missing tax IDs, outdated classifications, and conflicting information, which are classic issues of poor supplier data quality. These issues appeared across every category they touched.
Many organizations encountered similar patterns this year. As teams looked more closely at their supplier data quality, they found records that needed updating, attributes that didn’t match across systems, and parent–child hierarchies that no longer reflected current corporate structures. These gaps were symptoms of the environment procurement operated in throughout 2025: limited budgets, aging technology, and priorities that made ongoing data maintenance difficult to sustain.
How 2025 Exposed the Cost of Poor Supplier Data Quality
Procurement entered 2025 with clear constraints. In this report, leaders pointed to:
- Insufficient budgets and resources (29.4%)
- Technology gaps (23.5%)
- Unreliable supplier data as a key challenge (17.6%)
These pressures shaped the year and directly influenced the quality and completeness of supplier records, contributing to declining supplier data quality.
These challenges also mirrored findings from another CPO study, where data quality (43.97%) and governance, security, and compliance risks (35.41%) were identified as the two most pressing internal obstacles.1 Together, they paint a consistent picture across the industry: procurement teams struggle to maintain accurate data.
The Reality of Supplier Data Quality in 2025
According to the report:
- 53% of organizations rated their supplier data quality as poor
- 41.2% struggled to align data across multiple systems
- 29.4% lacked tools to automate cleansing or maintenance
- 23.5% deprioritized data quality amid competing initiatives
The result was a fragmented data landscape: multiple vendor masters, suppliers created differently in each system, missing documentation, inconsistent naming, and outdated hierarchies. As organizations look ahead to 2026, they’re recognizing how these persistent gaps limited their progress in 2025 and what needs to change in the year ahead.
What Poor Supplier Data Quality Signals About Procurement Maturity
1. Structural Weaknesses in Data Foundations
Supplier data quality gaps, such as duplicate records, missing attributes, and unverifiable legal entities, signal fragmentation at the core of procurement operations. These challenges often arise from disconnected tools, inconsistent processes, legacy onboarding practices, and the lack of standardized governance.
Notably, supplier data quality issues and governance concerns were also identified as the top two risks by global procurement leaders, underscoring that these are systemic challenges across industries.1
2. Barriers to Advancing 2025 Priorities
Many of 2025’s strategic initiatives depended on accurate supplier information:
- AI (including GenAI) adoption required structured and complete datasets.
- Sustainability reporting depended on clear classifications and certifications.
- Supplier consolidation efforts needed accurate parent–child relationships.
- Risk teams required dependable identifiers and up-to-date supplier attributes.
- Spend management and contract alignment relied on consistency across systems.
Yet with half of organizations reporting poor supplier data quality, progress in these areas was uneven. As Tim Herrod, CEO and Co-Founder of InTension Inc., noted in the report, high-quality data and the ability to connect data across disparate sources “has never been more needed.”
3. How Disconnected Systems Affect Supplier Data Quality
Data fragmentation was one of the biggest obstacles highlighted, with 41.2% of companies struggling to align information across multiple systems.
Disconnected tools lead to:
- Different versions of the same supplier in ERP, AP, and sourcing platforms
- Diversity data captured but never shared centrally
- Local entities onboarded without visibility into enterprise structures
A CPO captured the challenge clearly:
“Data silos were a huge problem for us. Even with powerful models and computing resources, finding and accessing the right data was incredibly difficult. Centralizing our data strategy under one leader broke down those barriers and eliminated duplicate data, which really accelerated our progress with AI-enabled automation.”1
These issues highlight the need for a single, reliable source of truth for supplier data that every system can draw from in 2026.
Readiness for 2026 Requires Stronger Supplier Data Quality
The report makes one message clear: dependable data is foundational. High-quality supplier data supports risk mitigation, operational efficiency, technology modernization, and strategic decision-making.
To meet 2026 expectations, procurement will need to shift from reactive cleanup to systematic data management supported by better models and automation.
Legal-Entity–Based Models
A legal-entity approach ensures every supplier is tied to:
- A validated and authoritative legal entity record
- Accurate parent–child structures
- Harmonized records across all connected systems
This structure is essential for improving supplier data quality across all connected systems, and reduces duplicates, creates a clearer view of spend, and supports both risk and compliance teams.
Continuous Cleansing and Enrichment
The report emphasizes the need for ongoing updates, not one-time cleanups, focused on:
- Missing tax IDs and certifications
- Outdated classifications
- Additional attributes, such as legal name, business number, registered addresses, company type, branch flag, etc.
- Corporate ownership, mergers, and acquisitions
Regular enrichment improves decision-making, strengthens supplier data quality, and reduces friction across procurement workflows.
Automation and Ongoing Enrichment
Given that many teams lack the resources to manually maintain large vendor masters, automation becomes critical. Automated enrichment, verification, and syncing reduce the operational burden and ensure information stays current across all applications.
What Procurement Should Prioritize Early in 2026
As organizations transition into 2026, leaders can accelerate progress by focusing on four strategic actions:
1. Evaluate the current supplier data landscape
Identify systemic issues, such as duplicates, missing attributes, and inconsistent identifiers to understand where foundational improvements are needed.
2. Strengthen the data model behind all systems
Move toward legal-entity–based frameworks that support both operational and strategic use cases.
3. Implement ongoing data quality processes
Adopt a continuous cycle of cleansing, verification, and enrichment.
4. Improve system connectivity
Close gaps that create conflicting or incomplete supplier records.
Better Supplier Data Quality for 2026
As 2025 wraps up, many teams have a better sense of the state of their supplier data. The past year underscored how much accurate supplier information matters, and how quickly gaps can slow down priority initiatives.
By addressing foundational data limitations now, organizations can enter 2026 with greater confidence, stronger operational capabilities, and the ability to deliver on strategic priorities that depend on accurate, unified supplier information.
Sources
12025 Global Chief Procurement Officer (CPO) survey, “Agents of change: Procurement’s big bet on digital.”
Connie Jensen is the Senior Manager of Content Marketing at TealBook.
