Analyzing vendor data is an essential component to maintaining the integrity of an organization’s service and product offerings.
Vendor data ages quickly. Businesses may be renamed, relocated, acquired, or face a change in procurement staff. These changes affect an estimated 30 to 40% of the data in your vendor database each year (1). To prevent incomplete, inaccurate, and duplicate records, it’s important to create procedural outlines for maintaining your supplier database. There are many reasons why you should validate your data.
Diversity Reporting Needs
In recent years, procurement and supplier management professionals have faced an increasing need for diversity reporting. Those in the public sector face small business set-asides, which require sourcing from a certain percentage of diverse suppliers. Private companies may also face diverse spend requirements set by federal contracts. Beyond government mandates, leading private companies have created their own supplier diversity programs, aware of the benefits of working with diverse suppliers. Data validation and analysis of Tier 1 suppliers and beyond can reveal the economic impact of local sourcing, and inform buyers on future purchasing decisions (2).
Many organizations boast analytics as the groundwork for competitive advantage, but may overlook the importance of data readiness and cleansing. Analytic output is only as good as data input. Access to the correct data is vital for category management. Preparing data in the context of supply chain management requires distinct processes, the initial steps of which are data cleansing and spend analytics (3). Raw vendor data can be aggregated, checked for completeness and accuracy, and enriched. There has been growing interest in flexibility and visibility surrounding spend analytics, which only a robust database can support.
Increased Efficiency; Decreased Costs
Research indicates that the average large and mid-market company is losing millions in potential savings because of inaccurate supplier data (4). Beyond sourcing, bad vendor data also affects supply chain users in procurement, accounts payable, legal, and other areas. Functional silos within a larger organization can lead to duplicate effort, which is associated with higher cost. Data sources can be located in multiple internal and external systems, which provides limited insights and fails to leverage a firm’s buying power (5). By aggregating data in a standardized way, an organization can improve operation efficiency and positively impact bottom line.
How to Validate Vendor Data
The first step to validating vendor data is preparing a list of suppliers that your organization has done business with over the past year. This information must then be cleansed and compared with trusted external databases, a service that some competing firms offer. Once updated, your procurement IT department can incorporate spend information associated with suppliers at the reporting level unique to your organization (6). Internal stakeholders must have access to this data with consistent procedures across the organization. Once created, rekeying data should be minimized. Scrubbing data creates a baseline but should be revisited yearly to track supplier performance. An organization can invest in a supplier management platform where data is summarized but actionable (7).
At ConnXus, we have powerful tools for your vendor spend and diversity data analysis needs. Our most popular software, SmartScrub®, is a data enrichment and validation tool that cleans and visualizes supplier classification data with an industry-leading turnaround time of 5-7 business days. International vendor data enrichment is also available. Our platform cross-references internal and external databases for the most up-to-date vendor information. Please visit our product page to learn more and download a free product guide here.