Implementation methodologies and socio-technical dynamics as drivers of analytics adoption in ERP systems

Enterprise Resource Planning (ERP) systems increasingly embed Business Intelligence and Analytics (BI&A) capabilities, including real-time dashboards, key performance indicators, and predictive and artificial intelligence (AI) functions. These capabilities often remain underused in implementation projects that prioritize transactional stabilization. Prior studies have explained ERP and analytics adoption mainly through the Technology, Organization, and Environment (TOE) framework and Diffusion of Innovation (DOI) theory, with limited attention to how implementation processes shape analytical activation. This study examines how implementation methodologies and socio-technical dynamics influence BI&A adoption in ERP systems. Drawing on TOE, DOI, and Actor-Network Theory (ANT), it uses a qualitative multiple-case design based on 43 semi-structured interviews with ERP partners, client organizations, vendors, and industry association representatives in Colombia, combining thematic analysis, theory-based pattern matching, and exploratory network modeling of two partner cases (15 and 14 nodes). The findings suggest that agile and hybrid methodologies, as enacted by implementation partners, are associated with earlier BI&A integration, whereas waterfall-oriented sequencing tends to defer analytical activation. Analytical roles showed limited brokerage over key implementation decisions. The study extends ERP adoption research by showing how methodological sequencing and actor positioning shape whether embedded analytics are activated or remain dormant.