Using Machine Learning to Bridge the Buyer-Supplier Divide
“Technology has always played an important role in enabling world-class performance, but procurement is now at an inflection point.”— The Hackett Group, Raising the World-Class Bar in Procurement Through Digital Transformation (2017)
One of the most compelling cases for centralized procurement technology is its ability to connect buyer and supplier data in real time. As procurement becomes an increasingly digital function, technology will also bridge the disconnect between supplier business development and the enterprise buyer decision making.
The problematic ROI of Business Development
Suppliers spend enormous amounts of money to increase their visibility into existing and potential buyers. A 2014 report from The Center for Exhibition Industry Research titled Exhibitor Direct Spend Estimate found that exhibitors spend almost $25 billion annually at business-to-business tradeshows in the U.S. Suppliers also allocate significant budget to advertising in directories. Businesses spend close to $7 billion per year on advertisements in the Yellow Pages, in addition to an average of $18,000 for a national display advertisement. Many suppliers purchase these ads in the hopes that enterprise procurement teams will see them in these static directories and connect.
While suppliers invest extensive resources in traditional advertising methods, procurement has moved on, mitigating the ROI of tradeshow and directory costs. According to a 2015 ProcureCon Pharma Survey, 73 percent of procurement and sourcing professionals cite internal partners as their most trusted source of supplier information. Other frequently used sources of supplier knowledge were peers, both within and outside of the enterprise.
This clear disconnect—between where suppliers are expending efforts and where buyers are searching for qualified suppliers—is frustrating for both sides. Suppliers want to be recognized for their unique capabilities and appear in front of their target audience at the right point on the decision-making timeline. Buyers seek trusted supplier recommendations and intelligence from their internal and industry peers. When suppliers feel the investments they make to be noticed are unfruitful, and procurement lacks an aggregated source of reliable supplier intelligence, the mutually beneficial process of connecting remains costly and inefficient.
Technology that leverages and enhances rich buy-side knowledge while empowering suppliers to efficiently increase visibility can bridge this disconnect for suppliers and buyers.
tealbook solves this common challenge by providing centralized supplier intelligence. By using machine learning, we optimize the rich supplier knowledge that exists across enterprises and industries. tealbook also enhances visibility for suppliers while eliminating the need to update multiple, static directories or spend valuable resources on efforts that fail to yield productive exposure. tealbook’s solution to this disconnect delivers empowerment, efficiency, and improved business outcomes for both buyers and suppliers.