Developing data enabled service innovations for customer segments of a manufacturing company

Abstract

With the emerge of cloud solutions and data analytics tools new opportunities arise in the context of data collection and analysis. This data and these technologies can be used to build new service offerings or enhance current processes. However, no research exists connecting the aspects of digital service innovation with customer segmentation. Questions, such as what the correct customer for a specific data enables service is, remain open. Within the field of service innovation, first theoretical models exist combining the requirements and dimensions of service innovation. However, those models are lacking empirical evidence.

Designed as a single case study within the manufacturing industry, this study explores the development of data enabled service innovations for customer segments within a manufacturing company. Drawing on the intersection of data and digital technologies, requirements for development and customer segmentation, the research addresses three key questions. First, suitable service innovations for a company in the manufacturing industry enabled by data and recent digital developments are investigated. Second, essential requirements for successful service innovation development are examined. Third, strategies for segmenting customers for the digital offerings of a manufacturing company are explored.

To answer these questions, a qualitative case study was conducted with a Finnish company in the manufacturing industry. First, a theoretical framework was built to describe the level of service innovations combining the requirements of service innovation, their dimensions and customer segmentation. Data was collected during a workshop and though semi-structured interviews. These interviews were conducted with internal stakeholder of the case company as well as customers. This research was conducted in Finland, Germany, Sweden and Switzerland. The data analysis process followed the principle of a grounded theory.

The focus for data enabled service innovations lies in the areas of predictive maintenance and enhancing customer value. Therefore, service offerings that combine base, intermediate and advanced services in these areas should be developed. The findings of the thesis are used to create a service innovation canvas. This canvas will first incorporate the seven pillars of service innovations as a foundation for successful service innovation development. Second, each service innovation requires targeted customers segments, which will be described using macro and micro labels. These labels will characterize the targeted customers based on aspects such as their service strategy or digital maturity. The service innovation will be defined with six dimensions. Further research should focus on testing the generalizability of these findings by applying the framework to other companies and industries. Moreover, the micro-segmentation approach within the context of a company’s installed base promises to yield interesting insights.