While the use of big data tends to add value for business throughout the entire value chain, the integration of big data analytics (BDA) to the decision-making process remains a challenge. This study, based on a systematic literature review, thematic analysis and qualitative interview findings, proposes a set of six-steps to establish both rigor and relevance in the process of analytics-driven decision-making. Our findings illuminate the key steps in this decision process including problem definition, review of past findings, model development, data collection, data analysis as well as actions on insights in the context of service systems. Although findings have been discussed in a sequence of steps, the study identifies them as interdependent and iterative. The proposed six-step analytics-driven decision-making process, practical evidence from service systems, and future research agenda, provide altogether the foundation for future scholarly research and can serve as a step-wise guide for industry practitioners.