Abstract
In an editorial that appeared in the March issue of Service Science, Alexandra Medina-Borja described potential research opportunities in the area of smart service systems, which focused mainly on automation and decision-support for complex service systems (Medina-Borja 2015). She argued that future service innovation will depend largely on effective understanding and use of data and technology to transform service systems into smart service systems, substituting information for interaction and human capabilities (see also Glushko and Nomorosa 2013), and blurring the boundaries between physical objects and the services that objects can provide (see also Normann 2001), resulting in new markets and disruptive business models (see also Ng 2014). Capturing and using data and technology in service systems to create smart service systems requires sensing human behavior, analyzing data to develop models of human behavior or models of human skill, and applying the models to support or automate the actions of service systems. In a commentary that also appeared in the March issue of Service Science, Steve Kwan, Jim Spohrer and I described some of the outcomes of a workshop we organized last year on a future research agenda for service, which focused mainly on the human-centered-ness of complex service systems (Maglio et al. 2015). We argued that innovation in service does not lie on the same trajectory as innovation in other sectors because service necessarily involves coordinated action among people and technologies, creating human-centered service systems that resist traditional optimization and automation. It was no accident that these two pieces appeared together, as both outlined consistent directions and opportunities for scientific and engineering research in service. I think that, taken together, these two pieces demonstrate the need for interdisciplinarity, for new theories and new methods. Service depends on people, human behavior, human cognition, human emotions, and human needs. Service systems are getting larger and larger, incorporating global enterprises, global industries, and world governments. Data is getting bigger and bigger, capturing both human actions and economic transactions on an almost unimaginable scale. Technology (and computational technology in particular) is getting more and more powerful, for instance, enabling the effective use of data to support and automate service interactions and service operations. In the end, service is about people working together and with technology to create mutual value. The more value created, the better the service. And yet value is a slippery thing, depending on human judgment and a thousand other factors. The fundamental scientific and engineering problems lie at the intersection of people and technology, how to create and operate large-scale service systems that are human-centered and technology-enabled, in which people and technology work as teams to create value for all involved.
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