Understanding how Fairmarkit provides vendor recommendations to help automate the sourcing process:
To be able to leverage the data your company has built over the years, Fairmarkit is utilizing Machine Learning. Our software learns from your purchasing history and vendor data in order to provide the best recommendations to fulfill your requests. To make this process possible, our software uses two key factors to search for and rank the vendors within Fairmarkit.
The first aspect is how our system provides the vendor search:
The Manufacturer, Part Number, UNSPSC Code, and the Description of a RFQ are dynamic, they will auto-populate suggested vendors based on purchasing history in your organization. Each vendor will show a color-coded reason why the system suggested it. The more specific you can be, the more accurate the results. For more information on this system, please visit our article on the External Vendor Search.
The second aspect is vendor ranking:
All pre-populated vendors that appear when an item is entered into the description of an RFQ will be ranked according to their previous behavior on the platform. The top recommendations will be taken by vendors who previously were able to deliver the best on metrics within each given sourcing category: competitive pricing, best delivery time, and quickest response time.