Investigating challenges to SME deployment of operational business intelligence: A case study in the New Zealand retail sector

Abstract

Advances in machine learning and big data are leading to the employment of data analytics management systems in many organisations and industries. Generally, large organisations are able to put more resources towards this deployment, and the software used is more suited to larger entities. However, increasing business pressures are now driving small and medium-sized enterprises (SMEs) to deploy data analytics. This study examines the challenges faced by small retail businesses in New Zealand when deploying a self-service business intelligence (BI) system. The study applied qualitative methods including in-depth interviews with managers and staff of four retail stores, and observed that while respondents consistently agreed on the benefits and drawbacks of the new system, their levels of engagement with the system were uneven. It was discovered that users’ real-time responses to dilemmas arising from the novelty of the new analytics management system compared to the existing system, significantly influenced the smooth adoption and implementation of the system. Analysis of a representative dilemma using the Theory of Constraints (TOC) and Evaporating Cloud (EC) method, leads to a possible resolution of the dilemma through TOC injections.