Data Analytics Capabilities and Supply Chain Resilience among Finnish SMEs: A Qualitative Study

Abstract

This study analyzes how data analytics capabilities build supply chain resilience for Finnish Small and Medium-sized Enterprises (SMEs). While data analytics is considered an enabler for large enterprise resilience, there is a limited body of research on how resource limited SMEs encounter and exploit these capabilities in practice, particularly in Finland. A qualitative approach using an interpretivist philosophy and exploratory research design, was employed for this research. The method used consisted of six semi structured interviews with supply chain analytics, business intelligence, logistics, procurement and operations experts working for Finnish SMEs.  Analysis was undertaken on interview data using a six-step process for themed analysis which gave rise to a set of ten interconnected theme: analytics adoption; supply chain visibility; resilience building; data based decision making; business continuity; implementation challenges; organizational capabilities; human capital; enabling technological capabilities and a set of practical suggestions. It is found that data analytics improve SME resilience through increased visibility and faster more informed decision making and in organizational flexibility to adapt during disruptive events. However, there are some important barriers such as the cost of implementation; lack of personnel capable of combining both an analytics and a supply chain focus; and data quality. There is high motivation towards Leadership Engagement, employee training and IT Infrastructure to foster successful analytics application in an enterprise. The research sheds practical lights on how Finnish SMEs build resilience with the support of data analytics, and provides practical recommendations on a phase approach to implementation, staff development, and ongoing future research investigating external knowledge in support of the digitalization for SMEs.