Bridging the perception-reality gap in manufacturing complexity: A dual-perspective configurator for digital transformation

Digital transformation amplifies manufacturing complexity, yet managers systematically misperceive its magnitude, a perception-reality gap that undermines strategic responsiveness. Existing diagnostic tools measure either subjective perception or objective structure, never both simultaneously, preventing organizations from identifying dangerous cognitive-operational misalignments during technology adoption. This study develops and validates a dual-perspective configurator integrating entropy-based objective metrics (static (Cs) and dynamic (Cd) entropic complexity across 40 managerial variables) with psychometric scales capturing cognitive load, using data from 18 manufacturing companies from six industrial sectors in Cartagena (Colombia) across discrete and process industries spanning small, medium, and large enterprise categories. Advanced statistical analyses, including hierarchical ANOVA, mixed-effects modeling, and psychometric validation, were conducted using Python. Results reveal a paradoxical size-dependent divergence. Large firms exhibit high objective complexity yet low perceived complexity, suggesting organizational routines and technological familiarity mask underlying systemic disorder. Conversely, medium-sized enterprises demonstrate strong perception-reality alignment, indicating transparent operational visibility, while small firms show moderate concordance with lower absolute complexity levels. Firm size and stage emerged as primary determinants with negligible sectoral effects. The configurator demonstrated excellent reliability, validating complexity as a systemically interdependent construct. The dual-entropy framework enables early detection of cognitive-operational mismatches invisible through conventional strategic planning, transforming abstract complexity discourse into actionable diagnostic intelligence for managing the perception-reality gap during Industry 4.0 transitions.