Procurement during early product development using adaptive AHP decision-making

Research & Development organizations often employ cross-functional teams to tackle New Product Development (NPD), where procurement professionals assist with early supplier integration activities for all key components. Due to the criticality of component interfaces along with overall long lead times, it becomes imperative for the team to make supplier selection decisions while the product design continues to evolve, and new customer requirements are identified. Traditionally, once the team chooses a supplier and begins working with the selected supplier, they try to enforce changes resulting from identifying new conditions on to the supplier, rather than re-evaluating supplier selection strategy to bring in another supplier who can minimize cost or lead-time impact. This research paper proposes a collaborative framework involving Bayesian network to predict emerging customer needs and Analytic Hierarchy Process (AHP) and Adaptive Policy Making (APM) for making procurement decisions which adapts as emerging customer needs are incorporated into the product design prior to design freeze. Following the overview of literature, we present the proposed framework and demonstrate its effectiveness through an example from the Oil & Gas industry.