Effective Use of Data Analytics and Its Impact on Business Performance Within Small-to-Medium-Sized Businesses

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Business use of data analytics and its potential impact on firm performance have become topics of deep interest within both the business practitioner and academic communities. While previous research has demonstrated relationships between data analytics and firm performance in larger firms, there is limited research on whether and how data analytics is used within and impacts Small-to-Medium-sized Business (SMB) settings. Given the preponderance of SMBs within the US economy, and their contribution to employment and economic activity, it is important for SMB owners to understand what management practices lead to effective use of data analytics that in turn impacts SMB performance. Drawing upon the Resource-Based View (RBV) of the firm and prior empirical research on practices within large firms, this dissertation identifies the resources that are needed to form a Data Analytics Capability (DAC) and examines the relationship between the maturity of DACs and the extent of business value realized. The research model was tested using Partial Least Squares-Structural Equation Modelling (PLS- SEM) analysis of survey data gathered from a sample of 300 SMB firms in the US, complemented with qualitative interviews of SMB owners. The results provide evidence that a more developed DAC can lead to higher Data Analytics Business Value across business functions.