Designing a Self-Service Analytics System for Transportation Supplier Selection

Today, the selection of suppliers is expanded from a pure cost-oriented view to consider multiple criteria such as delivery time, quality, and risks. Buyers in the business analyst’s role (BA) in global logistic de-partments are responsible for covering transportation demands. For supplier selection, they must allocate hundreds of items to an optimal set of suppli-ers. In interviews, we examined a high dependency on Data Scientists and Data Engineers. Currently, BAs achieve only non-optimal solutions be-cause they lack the required knowledge and adequate tools to perform this analytical process independently. Against this backdrop, we present the de-sign and evaluation of a self-service analytics (SSA) system that helps BAs to select suppliers for transportation demands considering multiple deci-sion criteria. We formulate a linear optimization problem that BAs can par-ametrize and analyze with our SSA system. Our proposed SSA system ena-bles BAs to improve the supplier selection process and showcases the po-tential of SSA systems to utilize optimization models.