Digital transformations in SMEs: A low-tech perspective : Common pitfalls for low-tech SMEs and how to mitigate them

Sammanfattning: Purpose - The aim of this study is to bridge the gap regarding digital transformation challenges and common pitfalls for low-tech SMEs. In doing so, we provide a framework presenting common pitfalls in digital transformations for low-tech SMEs and five mitigation strategies to aid in avoiding them and thus, enabling a higher success rate of digital transformations. Method - To answer the research questions, a thematic analysis was conducted based on data collected through three waves of semi-structured interviews. In total, 17 interviews were held with informants such as industry experts, the case company, and low-tech SMEs that had already successfully performed a digital transformation. Findings - The analysis resulted in 22 common pitfalls within four areas: Strategy, digital maturity, resources, and resistance to change. These built the foundation of the five mitigating strategies: Create mutual goals, break down changes into steps, spread the competence, change to improvement, and prioritize business development. Theoretical contribution - This study adds to existing literature by identifying the low-tech perspective of a digital transformation and presenting that SMEs’ difficulties are closely related to their size, lacking digital maturity, and an absence of transformational strategies. Furthermore, our findings enhance previous studies in suggesting a shift in perspective where digital transformation should be viewed as a business development method rather than only a change of the daily processes. Practical implications - This study maps out key risks and common pitfalls for managers in low-tech SMEs about to perform a digital transformation. Moreover, five mitigation strategies are presented aiming to aid organizations in their strategic work. Limitations of the study - The research has focused on one low-tech SME in the automotive industry. Data collection focused on gathering depth rather than quantifying findings, and thus, the generalizability might be limited. Future studies could benefit from validating the findings in another industrial context.