Optimizing the catalog search process for e-procurement platforms

Abstract

Many e-procurement platforms support XML-based e-catalogs combined with standardized feature descriptions. Beyond the usual keyword search this opens the arena for attribute-based search engines, including parametric search and preference search. We analyze the impact of different search techniques for such e-catalogs on the overall search process costs. It turns out that preference search has a high potential to significantly reduce the process costs. A large-scale use case with the MAN2B e-procurement platform supports our claim. We identify improvements achievable by using preference search, in particular less navigation steps during the product search and better search results due to the BMO query model. Expensive cases, where frustrated users accept bad search results or phone up the company's purchasing department, should decrease significantly. This in turn will enable the purchasing department to focus more on strategic issues like supplier relationship management than on operative issues as it still happens widely today.