Service and Service science

In service applications, we observe a trend toward knowledge based services that are delivered by highly educated and well-informed employees. They respond to specifically diagnosed customer demands by offering and delivering customized value-added solutions and maintaining enriching relationships. It is in this area that we expect the most opportunities for the future.

An essential part of knowledge-based services is the use of information and information systems. Often, the new information and communication technologies can substantially improve the service operation. From a business perspective, however, the pure presence of these technologies is not sufficient. The added value will come from the relevant and efficient use of the technology.

In short, a knowledge-based service is the provision of an advice or a solution to a customer, taking into accounts his or her specific context. Standard "ready to use" tools are usually inappropriate since there is often a lack of specifications: the value of the service comes from the closeness of the match between the context and the solution.

Service Science, the science of service provisioning, is the development and efficient use of intellectual and technical tools to analyze and synthesize the human, technological and business contexts of a customer and provide an optimum solution to his or her needs.

Moreover, being a Science means that the quality of the provided service should be, to a large extent, predictable. Therefore, Service Science rests strongly on the development of flexible models able to cope with the complexity of real world situations. These models can borrow tools from a large arsenal of scientific disciplines such as Psychology, Mathematics, Communication, Finance, Economy, Sociology, Information Systems, Risk Management, and so on.

This approach stands in contrast to ad hoc trial and error methods where the convergence to a “sufficiently good” solution cannot be guaranteed within a given timeframe.

With respect to scientific methods and background, in particular, we integrate specific knowledge in the following fields:

Business:

  • Customer perception of value
  • Service valuation and pricing
  • Customer relationship management
  • Risk assessment and management
  • Service quality assessment
  • Design of service level agreements
  • Information systems support to service provision

Engineering:

  • Handling of data: statistical data analysis, statistical modeling, business intelligence and business analytics, data mining
  • Quantitative modeling of products and processes
  • Business process simulation for design and analysis
  • Usability engineering
  • Transformation of business processes to service architecture
  • ICT Operations service development

Human and organizational factors

  • Interaction of customer and service provider, mediated by IT
  • Human control over complex service processes, involving complex technologies
  • Human decision making and risk perception in service processes
  • Customer behaviour in complex service processes