Using Advanced Analytics to Rationalize Tail Spend Suppliers at Verizon
Verizon Global Supply Chain organization currently governs thousands of active supplier contracts. These contracts account for several billions of annualized Verizon spend. Managing thousands of suppliers, controlling spend and achieving the best price per unit (PPU) through negotiations are costly and labor intensive tasks within Verizon strategic sourcing teams. Large organizations often engage a plethora of supplier for many reasons – best price, diversity, short term requirements, etc. While managing a few larger spend suppliers can be done manually by dedicated sourcing managers, managing thousands of smaller suppliers at the tail spend is challenging, can often introduce risk, and can be expensive. At Verizon, we leveraged a unique blend of descriptive, predictive and prescriptive analytics as well as Verizon specific sourcing acumen to tackle this problem and rationalize tail spend suppliers. Through the creative application of Operations Research, Machine Learning, Text Mining, Natural Language Processing and Artificial Intelligence, Verizon reduced multiple millions of dollars of spend and acquired lowest price per unit (PPU) of the sourced products and services. Other benefits realized are centralized and transparent contract and supplier relationship management, overhead cost reduction, decreased contract execution lead time, and service quality improvement of Verizon’s strategic sourcing teams.