DATA-DRIVEN DECISION SUPPORT IN INFORMATION SYSTEMS: STRATEGIC APPLICATIONS IN ENTERPRISES

Abstract

This systematic review synthesizes contemporary evidence on data-driven decision support tools in Information Systems with a focus on strategic applications in service-oriented enterprises and enterprise planning. Following a registered protocol aligned to PRISMA, we searched major scholarly databases and screened studies using prespecified inclusion, exclusion, and quality appraisal criteria suited to quantitative, qualitative, and design-science designs. In total, 115 peer-reviewed papers were included, spanning budgeting, forecasting, sales and operations planning, capacity and portfolio planning across service-intensive contexts. We map the field along three layers data architecture and integration, analytics capabilities from descriptive and diagnostic to predictive and prescriptive, and presentation and governance mechanisms that embed outputs into organizational routines. The corpus shows that predictive analytics improves planning accuracy and bias when evaluated with time-aware procedures and hierarchical reconciliation, while prescriptive optimization and decision automation deliver disproportionate gains in service-level attainment, cost-to-serve, and decision latency when coupled with governed, service-oriented or microservices architectures. Event-driven dataflows and explicit stewardship, lineage, and policy controls are consistently associated with faster, more auditable plan changes and higher acceptance of model recommendations. Organizational scaffolds effective-use practices, peer support, and structured reconciliation forums amplify technical benefits by converting insights into shared commitments on a reliable cadence. The review integrates quantitative estimates with thematic synthesis to produce a taxonomy of tools, an evidence map of outcomes, and configuration paths that explain why multiple coherent capability bundles can achieve strong planning performance. Practical guidance prioritizes sequencing investments in governance, predictive reliability, prescriptive services, and workflow embedding to align analytics with enterprise planning cadence.