Every organization talks about automation: invoice workflows, touchless payments, AI-driven approvals. But few talk about the data these systems depend on. Automation works by following patterns and rules, and it executes them at scale and with speed. But if the data feeding those processes is flawed, the system doesn’t just repeat the error: it replicates and amplifies it across every transaction, supplier, or approval flow it touches.
Think of it as a “garbage in, garbage multiplied” situation.
Manual processes might catch inconsistencies because humans notice when something looks off. Automation removes that checkpoint, so mistakes travel faster and further. Yes, automation improves efficiency, and AI can now even spot inconsistencies humans might miss (mismatched VAT details, duplicate records, or anomalies in vendor payments). But here’s the catch: while AI detects more issues, it also creates more exceptions. And when the underlying vendor master data is incomplete or unreliable, those exceptions can’t be resolved automatically. The system flags problems faster than teams can fix them, leaving automation running at full speed on unstable ground.
In other words, AI can highlight what’s wrong, but it can’t clean it up. When vendor data is incomplete, duplicated, or outdated, even the smartest technology can’t deliver reliable results.
Benchmarking the Reality: The State of Vendor Master Data in 2025
Transparent’s database of 9.6 million vendor records, representing €656 billion in spend, paints a clear picture of the state of vendor master data across global enterprises. These figures illustrate a persistent truth: even organizations equipped with sophisticated ERP platforms and advanced procure-to-pay (P2P) automation struggle with maintaining accurate, complete, and up-to-date vendor information.
These are not small or inexperienced companies. They are multinational corporations with integrated SAP, Oracle, or Coupa environments, multi-tiered approval structures, and strong governance frameworks. Yet, their vendor data shows alarming gaps, up to 94% inactive vendors, 54% with missing VAT numbers, and 43% with missing bank account details on average.
So how do these gaps happen, and why do they matter so much?
ERP systems are designed to process and store data, not to validate or cleanse it. Once a vendor record is created, it remains in the system indefinitely unless someone manually updates or deactivates it. Over time, mergers, reorganizations, and ownership changes make old data obsolete, and automation continues to use it without question.
For example, a global enterprise using SAP might have multiple vendor codes for the same supplier across regional systems. Even with a unified platform, inconsistent naming conventions or missing identifiers prevent full data harmonization, creating duplicates that distort spend analytics and payment accuracy.
Also, vendor creation and maintenance often span multiple departments (procurement, finance, and shared services) and sometimes multiple regions. Each uses slightly different processes or data standards. Without a centralized governance model, local variations lead to inconsistent data structures.
Why Vendor Data Quality Matters More Than Ever
The gaps shown in these benchmarks aren’t just operational oversights; they’re strategic vulnerabilities. As organizations accelerate automation, AI adoption, and digital procurement transformation, data has become the foundation for every decision, workflow, and control mechanism. Poor vendor master data doesn’t just slow process, it compromises the integrity of automation itself.
When critical vendor data points are missing, entire purchase-to-pay workflows start to break down. From delayed payments and failed compliance checks to broken communication channels, each missing detail (whether it’s a bank account, VAT number, or even an email address) has a direct operational and financial impact.
Below is a closer look at what goes wrong when vendor master data is incomplete:
- Missing Bank Account Numbers (43%)
When vendor records lack bank account details, payments can’t be processed or verified securely. Invoices may be approved but never reach the payment stage, and the risk of fraud or non-compliance increases, especially in cross-border transactions.
- Missing VAT Numbers (54%)
Without valid VAT numbers, reclaiming tax and ensuring compliance become impossible. Audits and regulatory reports fail, exposing companies to penalties and financial losses that could have been avoided with complete, validated data.
- Missing Email Addresses (60%)
A missing email address can bring entire PO and invoice workflows to a halt. Communication with suppliers breaks down, delays accumulate, and processing times increase, driving up administrative costs and cutting efficiency.
- Missing Phone Numbers (43%)
When vendors have no listed phone number, AP teams lose one of the fastest ways to verify invoices or resolve disputes. Vendor due diligence becomes manual and slow, leading to late payments and strained supplier relationships.
- Duplicate Vendors (1%)
Even a small percentage of duplicate vendor records can have big financial consequences. Double payments, inconsistent spend visibility, and weakened negotiation leverage are common outcomes when duplicates slip through.
- Inactive Vendors (73%)
Outdated or inactive vendors clutter systems and create confusion across procurement and finance. Worse, old accounts can be exploited for fraudulent activity, turning poor data hygiene into a real business risk.
Why So Many Companies Struggle
The problem isn’t a lack of tools, it’s how vendor data is managed.
Most organizations have already invested in advanced ERP systems, automation platforms, and digital procurement suites. Yet the data running through them is often incomplete or even incorrect. The reason is structural, not technical. Vendor master data sits at the intersection of procurement and finance, but no function fully owns it.
As a result, responsibility becomes fragmented, standards vary across regions, and accountability disappears into the gaps.
What Best-in-Class Organizations Do Differently
The top performers in our benchmark (those achieving single-digit error rates) treat vendor master data as a strategic asset, not an administrative task.
Here’s what we found sets them apart:
1. Continuous Data Validation
They don’t wait for periodic cleanups. They apply ongoing data quality checks using both automated tools and human verification to ensure accuracy over time.
2. Strong Governance and Ownership
They define clear data ownership models across procurement, finance, and compliance. Everyone knows who is accountable for each stage of the vendor lifecycle.
3. Integrated Vendor Onboarding
They prevent errors at the source by embedding validation rules, tax ID checks, and duplicate detection directly in the onboarding process.
4. Periodic Data Cleansing Campaigns
Best-in-class organizations run structured data cleansing projects, retiring inactive vendors and merging duplicates before they create downstream problems.
5. Measurable KPIs for Data Health
They monitor data quality the same way they track KPIs for cost savings or efficiency, because poor data is a cost driver too.
The Cost and Value of Vendor Data Quality
Every missing tax ID, outdated supplier, or duplicate record adds friction across purchase-to-pay. Invoices get delayed, payments go astray, and finance teams spend hours chasing information that should have been right the first time.
The cost is rarely visible on a balance sheet, but it’s felt everywhere: lost working capital when invoices are blocked or paid twice, wasted time spent reconciling mismatched records, compliance risks triggered by missing VAT details, and strained supplier relationships caused by late or incorrect payments. In the end, automation and analytics can’t deliver value when the data foundation is unstable.
But here’s the opportunity: cleaning vendor data pays back quickly.
A complete and reliable vendor master unlocks faster invoice processing, more accurate reporting, and genuine end-to-end automation. Finance and procurement teams can finally shift from fixing issues to optimizing performance.
Clean data may not be glamorous work but it’s what makes every digital transformation succeed.
The Future of Automation Starts with Data Integrity
As organizations push toward touchless processing, predictive analytics, and AI-driven decision-making, data integrity becomes the real differentiator between automation that simply runs and automation that transforms. The future of P2P performance will belong to the companies that treat vendor data quality not as a maintenance task, but as a strategic advantage.
READY TO BUILD A RELIABLE P2P PROCESS?
Transparent helps global organizations clean, validate, and maintain their vendor master data through a combination of technology and expert verification.
Before automating more, make sure your data is ready.
