Increasing service productivity by characteristics-driven recommendations for action

Increasing service productivity by characteristics-driven recommendations for action

Autor_innen: Michael Becker, Stephan Klingner, Martin Böttcher

XXI. International RESER Conference


Services today are characterised by both increasing macroeconomic relevance and rising competitive environment. Therefore, challenges for service providers are twofold. First, they have to handle increasing complexity of services due to necessary new innovative business to business services. Second, productivity of services must be increased to be successful in today’s economic environment.

Due to the diversity of services no single approach exists to tackle productivity of all possible service types. Different types of services require different management strategies. This situation has already been identified in service literature resulting in a great amount of service classifications with specific strategic recommendations. However, today’s service economy is characterised by highly complex and interdependent services.

As existing classification usually consider only two or three service characteristics they are often not applicable in the context of complex services. Therefore, our approach is to extract common service characteristics used in classifications. Based on specific characteristic values interdependencies between these values can be assessed resulting in more precise service delivery recommendations.

We conducted an extensive literature survey over more than 70 existing approaches for the classification of services spanning the period of nearly 100 years of service research. A great amount of analysed classifications focuses the aspect of service marketing. These sources study the customer impact on service design. A smaller amount of classifications focuses operations management and the service provision process. Since analysed classifications target various aspects of service development and provision, different characteristics are used to classify services.

Based on the extraction of used service characteristics we constituted three groups. Characteristics of the customer interface describe the interaction between service customers and providers. Process characteristics allow for a provider view on services and affect temporal and local service constraints. Finally, characteristics of the service result facilitate the description of the service output.

Using these three groups allows for the analysis of interdependencies between specific characteristics. This will be used as a basis for the development of a catalogue containing precise strategic recommendations. For this purpose, we will develop a metamodel for linking service characteristics with recommendations.
Expected Results

So far we have constituted relevant characteristics for classification of services referenced in academic literature. Using this we contribute to the discussion of service characteristics by conceptualising characteristics of classifications. This can be used as a starting point for further research in services in general. For example, it is possible to develop tailored service classifications based on the catalogue of characteristics.

However, real benefit will be achieved by linking service characteristics with productivity. Since existing classifications only target general groups of service types and abstract from specific characteristics they often do not meet the requirements of today’s complex and highly interactive service environment. Opposing to this, using our catalogue it is possible to assess the impacts of specific characteristic values on productivity. This allows for an identification of optimisation potentials in service delivery. Additionally, the metamodel can be used as a formalisation for representing interdependencies between different types of characteristics.

Furthermore, to facilitate productivity-driven service delivery the catalogue of characteristics enables grouping of service types according to their productivity. Based on analysed literature we are also able to propose best practices to increase service productivity and thereby support management.