Barriers to the Development of Data-Driven Services: An ISM Approach for SMEs

Data is nowadays considered as a key resource and represents the most valuable asset of our technology-driven world. However, the ability to use this resource in a value-adding way requires a holistic perspective. Small- and medium-sized enterprises in particular face major challenges in the innovation and development process. Despite preliminary research in the area of data-driven services (DDS), there is a lack of methodological analysis of the key barriers for SMEs in the context of DDS development. To address this shortcoming, we have developed an interpretive structural model based on a two-stage mixed-method approach by combining a structured literature review with practice-oriented focus group interviews to identify key barriers and their interdependencies and interactions. Our paper strengthens the knowledge of DDS development through a methodological barrier analysis and provides a guide for practitioners to eliminate the most relevant barriers to DSS development

Towards Design Principles for Data-Driven Services in Industrial Environments

The ever-growing amounts of data offer companies many opportunities to exploit them. Resulting data-driven services hold great potential for creating unique value for customers and the achievement of competitive advantages. Nevertheless, especially companies in the industrial environment struggle to implement successful data-driven service innovations. Surprisingly, there is a lack of scientific research addressing this issue. Thus, our research generates design principles for data-driven services to aid in their development. For this purpose, we present a qualitative interview study with experts in different lines of businesses among the industry sector, holding varying positions and roles in service systems. Through practical examples, we show which challenges exist in the development and use of data-driven services. On this basis, we derive design principles to help understanding data-driven services and to overcome difficulties identified in practice, notably, that allows practitioners to develop new services or re-design existing ones

A Taxonomy for Data-Driven Services in Manufacturing Industries

Data are a new resource to generate novel value for customers and to extend existing traditional services with a digital component. The manufacturing industry, usually, is characterized by analog service offerings built around product sales and therefore misses new market opportunities. One reason for that is the lack of assistance in innovating new data-driven services. Thus, to address that issue, this research paper generates a taxonomy of data-driven services in manufacturing industries. We use the established theoretical framework Service-Dominant Logic (SDL) to conceptualize the role and nature of data in new service offerings. The taxonomy is grounded both theoretically through its link to the existing knowledge base and empirically through the analysis of 100 data-driven services drawn from Crunchbase. It serves as a scientific instrument to profoundly and explicitly describe data-driven services in manufacturing and gives companies significant insight to incorporate value creation through goal-oriented data utilization and service design