key: cord-1012825-yg4ses4r authors: Tien, James M. title: On integration and adaptation in complex service systems date: 2008-09-03 journal: J Syst Sci Syst Eng DOI: 10.1007/s11518-008-5087-5 sha: a95d0b900f53eb77dd655e717cd1787b73e8c822 doc_id: 1012825 cord_uid: yg4ses4r The services sector employs a large and growing proportion of workers in the industrialized nations, and it is increasingly dependent on information and communication technologies. While the interdependences, similarities and complementarities of manufacturing and services are significant, there are considerable differences between goods and services, including the shift in focus from mass production to mass customization (whereby a service is produced and delivered in response to a customer’s stated or imputed needs). In general, services can be considered to be knowledge-intensive agents or components which work together as providers and consumers to create or co-produce value. Like manufacturing systems, an efficient service system must be an integrated system of systems, leading to greater connectivity and interdependence. Integration must occur over the physical, temporal, organizational and functional dimensions, and must include methods concerned with the component, the management, and the system. Moreover, an effective service system must also be an adaptable system, leading to greater value and responsiveness. Adaptation must occur over the dimensions of monitoring, feedback, cybernetics and learning, and must include methods concerned with space, time, and system. In sum, service systems are indeed complex, especially due to the uncertainties associated with the human-centered aspects of such systems. Moreover, the system complexities can only be dealt with methods that enhance system integration and adaptation. The paper concludes with several insights, including a plea to shift the current misplaced focus on developing a science or discipline for services to further developing a systems engineering approach to services, an approach based on the integration and adaptation of a host of sciences or disciplines (e.g., physics, mathematics, statistics, psychology, sociology, etc.). In fact, what is required is a services-related transdisciplinary - beyond a single disciplinary - ontology or taxonomy as a basis for disciplinary integration and adaptation. Before viewing a service system as an integrated system in Section 2, an adaptive system in Section 3, and a complex system in Section 4, it is helpful to define services -and their uniqueness, especially in contrast to goods -in this beginning section. Some concluding insights are provided in Section 5. The purpose J Syst Sci Syst Eng of this paper, then, is to highlight the critical importance of integration and adaptation when designing, operating or refining a complex service system. In order to provide a context for considering services, it is instructive to review the critical stages in a nation's economic evolution. As summarized in Table 1 As detailed in Tien and Berg (1995 , 2003 , 2006 , the importance of the services sector cannot be overstated; it employs a large and growing proportion of workers in the industrialized nations. As reflected in Table 2 Extending the three economic stages in Table 1 , Exhibit 6 predicts -in italics -a fourth stage in a nation's economic evolution; that is, as Second, when mass customization occurs, it is difficult to say whether a service or a good is being delivered; that is, a uniquely fitted jacket A service system is actually an integration or combination of three essential elements -people, processes and products. Moreover, integration can occur over the physical, temporal, organizational and functional dimensions, and J Syst Sci Syst Eng can include methods concerned with the component, the management, and the system. People, processes and products are the essential elements of an As detailed in Table 7 singled it out as the most critical infrastructure to protect following 9/11. Thus, while the U. S. is considered a superpower because of its military strength and economic prowess, As summarized in Exhibit 8, service system integration methods span the component, the management, and the system, so as to achieve primarily system efficiency and secondarily system effectiveness. The system integration methods include its foci (e.g., goals, objectives), models (e.g., simulation, optimization), and entities (e.g., connectivity, system of systems). The Because a service system is, by definition, a co-producing system, it must be adaptive. Adaption is a uniquely human characteristic, based on a combination of three essential elements -decision making, decision informatics, and human interface. Moreover, adaptation can occur over the monitoring, feedback, cybernetic and learning dimensions, and can include methods concerned with space, time and system. Decision making, decision informatics, and human interface are essential elements of an adaptive service system. The systems engineering methods alluded to in Figure 2 concern the integration of people, processes, and products from a systems perspective; they include electrical engineering, human-machine systems, systems performance and systems biology. Again, the real-time nature of co-producing services -especially human- As detailed in Table 9 , service system adaptation can occur over the monitoring, feedback, cybernetics and learning dimensions. Monitoring adaptation can be defined by the degree of sensed actions in regard to data collection (e.g., sensors, agents, swarms), data analysis (e.g., structuring, processing, mining), and information abstraction (e.g., derivations, In developing real-time, adaptive data processors, one must consider several critical issues. First, as depicted in Figure 2 , these data processors must be able to combine (i.e., fuse and analyze) streaming data from sensors and other appropriate input from knowledge bases (including output from tactical and strategic databases) in order to generate information that could serve as input to operational decision support models and/or provide the basis for making informed decisions. Second, as also shown in Figure 2 , the type of data to collect and As summarized in Table 10 , service system adaptation methods span space, time, and system, so as to achieve primarily system effectiveness and secondarily system efficiency. Space adaptation methods include people (e.g., providers, consumers), processes (e.g., procedural, algorithmic), and products (e.g., J Syst Sci Syst Eng Service systems are indeed complex, There are a number of ways of identifying the complexity of a system, especially a service system. were lodged and the program had to be severely scaled back (Urstadt 2008) . Furthermore, as has been indicated many times, customization which is a form of adaptation -has benefited greatly from advances in computation; however, customizing or targeting at the individual level does raise issues of privacy and confidentiality. In this regard, it is critical that every user of any online -or offline -site must be offered the choice of "opting out", whereby their personal data, activities or actions could not be used for any other purpose than its intended purpose. Fourth, as a critical aspect of complexity, modern systems of systems are also becoming increasingly more human-centered, if not human-focused; thus, products and services are becoming more personalized or customized. Certainly, services co-production implies the existence of a human customer, if not a human service provider. 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