Information Buried in Information Technology Service Contracts: Extracting Process–Performance Interrelationships

Abstract

Service-level agreements (SLAs) for multiservice information technology (IT) outsourcing contracts contain voluminous text that often makes it difficult for the customer organization to appreciate the complex interplay of various process elements (e.g., activities, resources, events) with key performance indicators (KPIs). We employ an ontology-based information extraction approach combined with a rule base in developing a decision support framework that derives analytic insights about hidden process–performance relationships from SLAs. The framework is instantiated in a prototype system, SLA-Miner. The system aids in decision making by encapsulating formal and semiformal domain knowledge through an IT service ontology and associated rule base. Advantages of the system include compact knowledge representation, maintainability, and adaptability to changing business environment. Sets of real life SLAs are analyzed to demonstrate the feasibility of SLA-Miner. Results demonstrate the utility of the decision support framework to empower service analysts/managers in the customer organization in identifying KPI interrelationships as well as deficiencies and potential conflicts in the current contract. This knowledge is useful to both the service provider and customer organizations in contract formulation and process management, and incentive decisions.