Using Business Analytics for SME Business Model Transformation under Pandemic Time Pressure

The COVID-19 pandemic has had an unprecedented impact on many industry sectors, forcing many companies and particularly Small Medium Enterprises (SMEs) to fundamentally change their business models under extreme time pressure. While there are claims that technologies such as analytics can help such rapid transitions, little empirical research exists that shows if or how Business Analytics (BA) supports the adaptation or innovation of SMEs' business models, let alone within the context of extreme time pressure and turbulence. This study addresses this gap through an exemplar case, where the SME actively used location-based business analytics for rapid business model adaptation and innovation during the Covid-19 crisis. The paper contributes to existing theory by providing a set of propositions, an agenda for future research and a guide for SMEs to assess and implement their own use of analytics for business model transformation.

Automated summary

The COVID-19 pandemic has forced many companies, especially Small Medium Enterprises (SMEs), to change their business models under extreme time pressure. However, there is limited empirical research on how Business Analytics (BA) supports SMEs' adaptation or innovation, especially in the context of extreme time pressure and turbulence. This study fills this gap by presenting a case study of an SME that utilized location-based business analytics for rapid business model adaptation and innovation during the COVID-19 crisis. The study contributes by providing propositions, a research agenda, and a guide for SMEs to assess and implement their own use of analytics for business model transformation.