Service Data Quality Management Framework to Enable Through-life Engineering Services

Abstract

With the growth of the product-service system (PSS) in recent years, how to better manage the service data to improve the informed decision-making capability has become an on-going aim among the Through-life Engineering Services (TES) firms. This scenario has led managers, more and more, to turn their attention to the quality of data and information created, gathered and used within the company. Encouraged by this background, a service data quality framework has been developed aiming to provide companies with a set of methods and tools to prioritise relevant service data and assess its quality levels. The process involves four main steps that go through: (1) Mapping out important data for Through-life Support available within the company and its internal and external flows; (2) Application of a multiple criteria decision-making technique to prioritise the relevant data set considering its costs for being collected and maintained, business impact, frequency of use and ease of obtainability; (3) Quality assessment of the prioritised dataset, based on a capability maturity model; (4) Defining strategies to address data quality issues. Validation on an industrial case study demonstrates potential benefits of the process and further work opportunities.