Supplier Entity Resolution: Optimize Sourcing Strategies and Reduce Costs

High-quality supplier master data management is at the heart of modern procurement, enabling companies to make better decisions, reduce risk, and drive greater efficiency across the supply chain. But too often, supplier records are duplicated, inconsistent, or scattered across systems, making it nearly impossible to gain a clear picture of spend, risk, or supplier performance. 

To capitalize on the true value of their supplier data—and use it to drive better decisions—businesses need to accurately identify, link, and unify their suppliers across systems and sources. And to do so, they must solve the hard problem of supplier entity resolution. But what is it, exactly, and why is it so challenging? 

What is Supplier Entity Resolution?

Supplier entity resolution is a data management process that identifies and links supplier records across multiple data sources and datasets to create a unified view, or “golden record,” that represents the best version of a company’s suppliers. It addresses the challenge in supplier master data management: reconciling supplier records across and within datasets by detecting and matching records that are the same, despite differences in spelling, formatting, associated attributes, and more. Then, by assigning a unique ID to these matched records, entity resolution processes ensure that these records are treated as one unique entity going forward. 

When done well, entity resolution enhances supply chain visibility by improving the quality, accuracy, and consistency of supplier data, ultimately increasing its value and usability across the business.

Why is Resolving Supplier Entities so Hard?

Poor quality supplier data often leads to operational bottlenecks, inefficient sourcing strategies, and compliance risks. But keeping supplier data accurate and up-to-date isn’t easy. Factors that impact a company’s ability to quickly and easily resolve supplier entities include: 

1. Heterogeneity of data quality. Abbreviations, misspellings, missing information, or inconsistent formats are common in supplier datasets, making it difficult to resolve entities across a multitude of sources. 

2. The problem of scale. If there are n supplier records in total, then companies need to compare n-squared pairs to reconcile the data. However, because supplier data is diverse, rules-based matching and manual reconciliation do not scale across all records, even when the number of supplier datasets is relatively small.

3. Changing business context. Each use case requires specific data sources and has different requirements around the precision and recall trade-offs.That’s why it’s essential to have multiple views of entities for different requirements.
4. Missing external context. In supplier data management, organizations often find that supplier records don’t tell the full story. For example, a supplier may be listed under an acronym in one system and its full name in another. Or, it may have changed its name, address, or gone through a merger or acquisition. Without external data, it can be impossible to know if two supplier entities are the same. 

5. Lack of clarity on corporate structure. Without a clear understanding of corporate hierarchies, companies fail to identify relationships between parent entities and their subsidiaries. Absent this insight, companies miss opportunities to negotiate better terms, avoid overreliance on a limited set of suppliers, and reduce supplier risk exposure. 

The Importance of Entity Resolution in Supplier Master Data Management

Entity resolution plays a critical role in providing the golden records companies need for efficient and effective sourcing and spend management. Furthermore, when procurement teams have clear, complete golden records for their suppliers, they can more confidently manage, negotiate, and consolidate spend across their supplier network. 

Additional benefits of supplier entity resolution include: 

• Minimizing redundant supplier data: Duplicate records result from data entry errors, inconsistencies, or slightly different representations of the same entity. Using entity resolution, companies can improve data integrity and accuracy by identifying and merging redundant entities into a golden record.
• Breaking down data silos: Integrating supplier records across sources is challenging because each system captures data attributes differently. With entity resolution, companies can easily reconcile these differences and consolidate multiple supplier entities into a single, golden record that spans datasets.
• Gaining unified supplier views: Fragmented supplier data, trapped in data silos, prevents companies from having clear visibility into their supplier relationships. Entity resolution delivers the 360-degree supplier view procurement teams need to optimize sourcing strategies and reduce costs. 
• Enhancing data accuracy: Poor-quality data leads to misguided decisions. By resolving supplier entities, companies can improve data quality by spotting inconsistencies, standardizing inconsistent data, and filling in missing values to make the golden record as complete and useful as possible.
• Boosting productivity: Matching and reconciling supplier records manually is tedious, time-consuming, and expensive. Entity resolution enables organizations to save time and reduce costs by quickly and easily revealing matches and reconciling them in real time.
• Reducing risks: Accurate, consistent, and complete supplier records are essential for identifying high-risk relationships and ensuring regulatory compliance. Supplier entity resolution helps organizations deliver cleaner, more reliable data that strengthens oversight and supports compliance efforts.

How AI-native MDM Supports Supplier Entity Resolution

AI-native MDM makes it easy for companies to resolve entities and gain holistic, 360-degree views of their suppliers across systems and sources. With a fast time-to-value (days or weeks, not months or years) and clean, trustworthy data that’s ready for consumption, companies can improve visibility into vendor spending data, reveal new opportunities to refine sourcing strategies, and optimize supply chains. 

Further, using real-time capabilities, AI-native MDM enables companies to onboard new suppliers confidently while preserving data integrity. Powerful “search before create” workflows check for matches in existing supplier data sets while the data is still in motion. If the system detects a match, it updates the existing golden record instead of creating a new, duplicate one. 

With AI-native MDM, companies can confidently deliver trustworthy golden records that unlock the insights needed to make smarter decisions, reduce risk, and gain control over their supplier ecosystem. To learn more, download our ebook “Guide to Entity Resolution with AI-native MDM.”