It has been predicted that companies that fail to streamline vendor data management by the end of 2023 could have wrong information for half of their suppliers. This is significant. Relevant supplier master data is critical for procure-to-pay (P2P) automation, analytics, and accuracy. But connecting data to users and solutions at times, gets bumpy.
Leverage these tips in order to optimize the vendor master data for smoother procedures, accurate information, and better business value.
1. Handling Vendor Data Should be Ongoing
Vendor data changes continuously with time. If your company has 9,000 vendors, you would require at least 2,000 updates per year in order to keep supplier data accurate, try to pay constant attention to the data to keep up with the latest contact numbers, names, and much more. Making this an ongoing practice helps to minimize stale data and other issues that occur from neglecting master data management (MDM) that slows down other methods.
2. Streamline by Looking Across the Complete Supplier Lifecycle
Procurement and other internal stakeholders must map out the end-to-end vendor lifecycle to receive the complete view of the master data. Companies should use the right procurement automation software to align procedure ownership with data ownership, or risk rapidly escalating operating expenses and minimized spend visibility. It signifies optimizing in all directions. To amplify the effect of data optimization, extend your view into other areas, which are affected by supplier master data. This cross-functional collaboration minimizes problems downstream.
3. Enroll Vendors to Support Data Maintenance and Minimize Inappropriate Information
A cost-effective approach to receiving vendor data updates into the system entails assigning responsibility to the person who owns the data- the suppliers themselves. They know the details better than anybody else. Hence, engage your vendors in data maintenance by making them accountable for data quality in a new and renewed vendor contract, with penalties for non-performance. This should be done with appropriate approval workflow.
4. Leverage Holistic Data Modelling to Streamline Company Requirements
In order to cover the complete master data requirements, procurement professionals must work with internal stakeholders to monitor the overall vendor lifecycle. Such cross-functional collaboration is crucial for developing a full master data management model with fewer gaps and bumps.
The data modeling method must spot all the tools and systems that use vendor-related data and when and where various systems get involved in the vendor relationship life cycle. The data model does not require to store each piece of information on a vendor, but primarily all the essential data that two or more systems would utilize. The model also must include the best source for every piece of master data, whether it is the vendor, a third-party, or an internal group. This building of the holistic data will show where common data must be captured and routed for downstream methods. Also, don’t miss out on the procedures to handle data creation and maintenance.
5. Optimize Who Needs What Data in Procurement
Generate a governance plan as early as possible in the project in order to organize responsibility for vendor master data. Procurement owns the entire vendor relationship and procedures that you probably don’t interface directly with every vendor, like cleaning services or tax advisors. Plus, procurement also doesn’t need to engage with every bit of master data required to develop your entire data model, such as access to vendors’ banking details. Focus your master data management optimization on the data types that procurement touches.
6. Supplier Management Data Process Can Streamline Vendor Quality
Make vendor data updates an essential part of doing business with you and observe who is on board. Vendors who accept responsibility for maintaining the critical data elements have a huge advantage in winning organizations over the ones who do not. Taking an issue this relatively easy often indicates a vendor’s willingness to work with your company.
7. Streamline by Establishing a Framework for Stewardship and Master Data Governance
Include internal stakeholders in the process of generating the data governance and management model. Leverage a framework in order to specify who is accountable for data and who has decision rights. It establishes clear guidelines for a responsible and informed RACI matrix for data.
Streamlining the vendor master data using a good procurement solution is a worthwhile exercise. It has been observed that 70% of businesses leveraging enterprise information management to align and link their analytics, and data investments will acquire enhanced business outcomes.