Persistent inefficiencies in water treatment infrastructure undermine public health and economic development across many regions. In Tanzania, despite significant investment, a robust analytical framework for diagnosing the drivers of efficiency gains at a systemic level has been lacking, hindering targeted policy interventions. This policy analysis develops and applies a novel multilevel regression diagnostics framework to measure and attribute efficiency gains in Tanzanian water treatment facilities. It aims to identify the relative contribution of facility-level operational factors versus regional policy environments. A longitudinal, facility-level dataset was constructed from operational records. The core analytical model is a three-level hierarchical linear model: $y_{ijt} = \beta_{0} + \beta_{1}X_{ijt} + u_{j} + v_{k} + \epsilon_{ijt}$, where $i$, $j$, and $k$ index facilities, districts, and regions, respectively. Inference is based on robust standard errors clustered at the district level. District-level governance factors accounted for approximately 40% of the observed variation in efficiency gains, a proportion twice that attributable to facility-level capital investment. A one-standard-deviation improvement in regional regulatory quality was associated with a 15% increase in treatment efficiency, significant at the 95% confidence level. The diagnostics framework reveals that systemic inefficiencies are predominantly driven by supra-facility governance disparities, not merely technical or financial inputs at the plant level. Policy must shift from a uniform, capital-focused investment strategy to one that prioritises strengthening district-level regulatory capacity and performance monitoring. A pilot programme for integrated regional water governance hubs is proposed. multilevel modelling, infrastructure diagnostics, water treatment efficiency, policy evaluation, hierarchical linear model This article provides a novel diagnostic methodology that disentangles nested sources of variance in engineering performance, offering policymakers a tool for spatially targeted interventions.