Challenges and approaches with data-driven services for SMEs : insights from a field study
Year: 2019
Type: article
Abstract: Purpose: This paper investigates the status and evolution of data-driven services specifically in SMEs and compares them with the situation of large enterprises. For both, increasing the proportion of total business accounted for by services is considered essential to build up and maintain competitive advantages. Thereby, the pattern of services shifts towards advanced services, for which the capability to manage, process, and analyse data is relevant. This represents a challenge in particular for SMEs in terms of knowledge, organisation, and culture. A more advanced understanding of the specific characteristics of this gap and of the possibilities of closing it is required. Design/Methodology/Approach: Therefore, a literature review followed by a field study was conducted to analyse this challenge. The field study incorporates (1) a series of in-depth interviews with more than ten SMEs and (2) a quantitative survey with more than one hundred replies. Findings: Our findings suggest that for SMEs building services on data has a big potential and it is expected to have higher priority in the future. In contrast to large enterprises, the share of revenue accounted for by services is still subcritical for SMEs, and it is expected to grow. Getting data from the installed base of products is a significantly higher hurdle for SMEs than for large enterprises, which represents a major challenge. There is a lack of data science knowledge and competences in SMEs. However, SMEs’ willingness to participate in shared competence centres increases. Originality/Value: This paper provides a new perspective on the challenges of servitization of manufacturing SMEs by a focus on applying data and analytics for the provision of services. The research is relevant in order to address the challenges and solution approaches which are specific for manufacturing SMEs.
Authors: Jürg Meierhofer, Petra Kugler, Roman Etschmann
Language: English
Subfield: Marketing
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3003024438