How is this different from the spend analysis solution already offered by Emptoris?
Emptoris approached spend analysis via a best of breed rule-based classification engine. This leverages vendor, general ledger, and purchase order information to classify spend data, offering a high-level of accuracy when classifying indirect spending on goods and services. However, with direct and MRO spending, the volume of transactions increases significantly and, often, the information needed for accurate classification is buried within cryptic item descriptions found for example in purchase orders. Intigma brings a machine learning based technology to generate the rules for categorizing this spend automatically. In addition, it supplements information not present in companies’ ERP data to ensure more accurate classification. The combination of Emptoris’ existing rules-based approach, Intigma’s machine-learning approach, Intigma’s automated item enrichment from third party sources, and the automated end-user feedback capability create a formidable solution that enables companies to
