How Do You Manage a Massive Vendor Master?
A vendor master is the starting point for all procurement activities within a business. The more business grows, the more its vendor list will grow. Each department will begin to require specialized suppliers for their niche needs, and suddenly, supplier datasets are siloed, information isn’t being regularly updated, and the procurement function begins to crumble at the hands of bad data.
A common hurdle for many organizations is the inability to handle the volume of information associated with a vendor master. Your business may have tens of thousands of supplier records, and with datasets that large, it can become a real challenge to identify outdated or duplicate records.
The Need for Clean Vendor Data
Despite the challenge, the need for clean vendor data is vital. Every procurement professional has experienced severe business consequences that have stemmed from bad supplier data, like duplicate or fraudulent payments, missed deadlines, or an inability to pivot after a supply chain disruption. Not to mention, bad supplier data leaves you at a disadvantage when it comes to measuring compliance, reporting on spend targets, and negotiating contract terms.
So, the need for a well-managed vendor master is clear, but how is it achieved? There are three typical routes you can take: doing a manual data cleanse, outsourcing a one-time data enrichments, or employing a cloud-based data layer to autonomously enrich your data, all the time.
Manual Data Cleansing
If you decide to undertake the chore of cleansing and maintaining your supplier data yourself, you’ll need stringent organization standards and buy-in from your entire organization to make sure your work doesn’t get undone in a matter of months. These 6 vendor management best practices can help you begin to develop your manual data cleansing processes.
Gather all your vendor data across all your systems and departments. Consolidate all of this data into a single source of truth that should be referenceable by every arm of your business. Identify exactly what types of supplier data are critical to your business functions, and note any outstanding gaps in information.
Standardize data input across company names, addresses, tax identification numbers, banking information, your relationship and spend. Remove duplicates and outdated information. This is a good step to develop a system of internal category codes.
Ensure the information you have is verifiable by an external source, like government or regulatory agencies. Determine a monthly, quarterly, or annual schedule to re-verify information. Vet suppliers for risk and ensure none are fraudulent or sanctioned.
Seek out more granular information like: contact names and information for key persons, company size and parent/child relationships, annual revenue, DUNS numbers and NAICS codes, similar suppliers that could be leveraged in an emergency situation, etc.
Determine how the breakdown of your vendors and your spend with those vendors can help you meet corporate spend initiatives and other goals. Develop a spend reporting method that works for your reporting schedule and requirements, taking into consideration any spend targets for small, diverse, or sustainable businesses. You may also consider including a method for Tier 2 spend reporting.
Much like you will need to develop a method for re-validating your supplier data on a regular basis, you should also consider repeating this entire process regularly as well, in order to keep your data fresh and accurate. However, many procurement teams do not have the resources and manpower to repeat these steps manually, and they turn to innovative solutions on the market.
One-Time Data Cleanse
Of course, you can hire companies to do a one-time data cleanse or data enrichment. These enrichment programs usually cost thousands of dollars, and the deflating fact is that as soon as the enrichment is done, the data becomes stale again. The issue with these costly one-time data cleanups is that without and ongoing plan to maintain the rigorous standard of data completeness, they struggle to provide ROI, and leave you in the same place you started in.
Cloud-Based Data Layer
TealBook is an example of a data foundation that sits beneath your existing tech stack to provide ongoing, effortless vendor data management. Using AI and ML, it can autonomously complete all the steps listed above and more, freeing up your team to take on more strategic initiatives and unlock the next level of value in your procurement activities.
When it comes to vendor management, it is possible to manually cleanse, enrich, and maintain your supplier data. However, doing so will eat up precious manpower, time, and resources. The best practices above can provide a guide, but if your organization values efficiency and optimization, consider automating your vendor management processes so that you can focus on the bigger picture.