Operational alignment, defined as the alignment between business processes (BPs) and information systems (ISs), is essential for ensuring that IS capabilities effectively support organizational operations. Despite extensive efforts, existing approaches to operational alignment remain constrained by a trade-off between simplicity and comprehensiveness. Coarse-grained methods overlook critical details, while fine-grained methods, though more precise, generate overwhelming complexity that impedes practical application. Drawing on complexity theory and systems thinking, this study conceptualizes operational alignment as a complex, nonlinear phenomenon characterized by emergent behaviors and intricate coevolutionary interactions among numerous detailed BP activities and IS tasks. While acknowledging dynamic/process complexity conceptually, this study targets the structural complexity at the BP-IS interface (i.e., the many-to-many mapping between BP activities and IS tasks) and operationalizes it through activity-task matching. To address structural complexity, this research proposes a novel operational alignment technique that balances abstraction and idealization through the logic of recommender systems (RSs). Using the Delphi method, the relationships between BPs and ISs, including the importance and performance of specific BP activities and IS tasks, were identified and used to parameterize an RS-based operational alignment technique. This technique manages structural complexity by defining alignment indicators derived from a fit-as-matching perspective, yielding pairwise BP-IS correspondences. The technique employs collaborative filtering to estimate missing values and prioritize high-impact alignment areas. It was empirically validated at Top Public Universities (TPUs) in the Middle East, where it generated actionable recommendations for aligning ISs with BPs and vice versa. Results from expert evaluations and a practical workshop confirmed the technique’s usefulness, usability, and applicability, emphasizing its effectiveness in reducing structural complexity. By translating structural alignment complexity into actionable empirical solutions, this study contributes to design science research by providing a practical, theoretically grounded artifact that addresses operational alignment challenges, preserves alignment accuracy, and supports informed decision-making in dynamic organizational environments.

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