Reasonable Sufficiency as a Decision Framework for Resource-Efficient Analysis in Applied Engineering

Applied engineering increasingly relies on high-resolution modelling, extensive measurements, and significant computational resources. While these approaches enhance analytical capacity, they also increase complexity and resource consumption, often without proportional impact on engineering decisions. This paper introduces the concept of reasonable sufficiency as a decision-oriented framework for engineering problem formulation. The framework defines the required level of accuracy based on its influence on decision outcomes, enabling the alignment of analytical effort with practical relevance. A structured application strategy is proposed and demonstrated through case examples from ventilation analysis, Computational Fluid Dynamics modelling, and experimental design. The results show that decision-relevant conclusions can be achieved using reduced model complexity and simplified measurement strategies. The proposed framework supports more efficient use of computational and experimental resources while maintaining decision reliability. It provides a systematic approach for balancing accuracy and efficiency, contributing to more sustainable engineering practices. The framework demonstrates that reduced methodological complexity can lead to faster, resource-efficient, and decision-relevant engineering outcomes without compromising validity.