{ "background": "Ageing infrastructure and operational inefficiencies in electrical distribution networks present significant challenges for utilities in many regions. There is a pressing need for robust, field-validated methodologies to evaluate asset performance and identify efficiency interventions.", "purpose and objectives": "This study aimed to conduct a comparative methodological evaluation of two prevalent approaches for assessing distribution network equipment efficiency. The primary objective was to determine which method yields more reliable and actionable data for informing maintenance and capital replacement strategies.", "methodology": "A randomised field trial was implemented across multiple municipal service areas. Network segments were randomly assigned to either a traditional time-based maintenance audit or a novel condition- and risk-based assessment protocol. Performance was modelled using a generalised linear mixed model: $\\log(E(Y{ij})) = \\beta0 + \\beta1 X{1ij} + \\beta2 X{2ij} + uj$, where $Y{ij}$ is the efficiency metric for asset $i$ in area $j$, $X1$ and $X2$ denote methodological and load covariates, and $u_j$ are random intercepts for area.", "findings": "The condition-based methodology identified 34% more latent critical failures in transformers and switchgear compared to the time-based approach. The estimated efficiency gain from targeted interventions guided by the new method was 7.2 percentage points (95% CI: 5.1, 9.3) higher.", "conclusion": "The condition- and risk-based methodological framework provides a substantively superior evidence base for efficiency-driven asset management decisions compared to conventional scheduled maintenance audits.", "recommendations": "Utilities should prioritise the adoption of the evaluated condition-based assessment protocol. Further research should investigate the integration of continuous monitoring data into the model to enhance predictive accuracy.", "key words": "asset management, distribution networks, field trial, randomised evaluation, efficiency, condition-based maintenance", "contribution statement": "This paper provides the first randomised field comparison of asset