A new loss function-based method for multiresponse optimization is presented. The proposed method introduces predicted future responses in a loss function, which accommodates robustness and quality of predictions as well as bias in a single framework. Properties of the proposed method are illustrated with two examples. We show that the proposed method gives more reasonable results than the existing methods when both robustness and quality of predictions are important issues.

Purpose: The proliferation of (big) data provides numerous opportunities for service advances in practice, yet research on using data to advance service is at a nascent stage in the literature. Many studies have discussed phenomenological benefits of data to service. However, limited research describes managerial issues behind such benefits, although a holistic understanding of the issues is essential in using data to advance service in practice and provides a basis for future research. The purpose of this paper is to address this research gap. Design/methodology/approach: “Using data to advance service” is about change in organizations. Thus, this study uses action research methods of creating real change in organizations together with practitioners, thereby adding to scientific knowledge about practice. The authors participated in five service design projects with industry and government that used different data sets to design new services. Findings: Drawing on lessons learned from the five projects, this study empirically identifies 11 managerial issues that should be considered in data-use for advancing service. In addition, by integrating the issues and relevant literature, this study offers theoretical implications for future research. Originality/value: “Using data to advance service” is a research topic that emerged originally from practice. Action research or case studies on this topic are valuable in understanding practice and in identifying research priorities by discovering the gap between theory and practice. This study used action research over many years to observe real-world challenges and to make academic research relevant to the challenges. The authors believe that the empirical findings will help improve service practices of data-use and stimulate future research.

A common problem encountered in product or process design is the selection of optimal parameter levels that involves the simultaneous consideration of multiple response characteristics, called a multi-response surface problem. Notwithstanding the importance of multi-response surface problems in practice, the development of an optimization scheme has received little attention. In this paper, we note that Multi-Response surface Optimization (MRO) can be viewed as a Multi-Objective Optimization (MOO) and that various techniques developed in MOO can be successfully utilized to deal with MRO problems. We also show that some of the existing desirability function approaches can, in fact, be characterized as special forms of MOO. We then demonstrate some MOO principles and methods in order to illustrate how these approaches can be employed to obtain more desirable solutions to MRO problems.

Purpose: The proliferation of customer-related data provides companies with numerous service opportunities to create customer value. The purpose of this study is to develop a framework to use this data to provide services.Design/methodology/approach: This study conducted four action research projects on the use of customer-related data for service design with industry and government. Based on these projects, a practical framework was designed, applied, and validated, and was further refined by analyzing relevant service cases and incorporating the service and operations management literature.Findings: The proposed customer process management (CPM) framework suggests steps a service provider can take when providing information to its customers to improve their processes and create more value-in-use by using data related to their processes. The applicability of this framework is illustrated using real examples from the action research projects and relevant literature.Originality/value: “Using data to advance service” is a critical and timely research topic in the service literature. This study develops an original, specific framework for a company’s use of customer-related data to advance its services and create customer value. Moreover, the four projects with industry and government are early CPM case studies with real data.