Craig M. Richmond, Clemens Kielhauser and Bryan T. Adey
A key difficulty that plagues benchmarking in the public sector is heterogeneity in the production process. The purpose of this paper is to present a strategy for overcoming that…
Abstract
Purpose
A key difficulty that plagues benchmarking in the public sector is heterogeneity in the production process. The purpose of this paper is to present a strategy for overcoming that difficulty using physical production models and demonstrate it using road renewal management as an example.
Design/methodology/approach
A physical production model is used to linking required prices, inputs and exposures to environmental factors to the desired services to be delivered. A measure is derived from this that adjusts for the additional expected costs from operating in a more difficult environments. A case study is used to present methods for addressing specific parameterization issues that arise in an empirical application.
Findings
The method was found to be implementable and empirically better than naïve ratio measures commonly found in practice.
Research limitations/implications
Data and modeling issues were identified that can be addressed by public supervisors that are expected to greatly improve the quality of the measures.
Social implications
According to the raw data and simple ratios, a very large degree of inefficiency can potentially be eliminated by applying the recommended measures. In all likelihood the real potential is much smaller, but still significant.
Originality/value
Most applied benchmarking exercises use simple ratios as KPI’s. These are easily dismissed where environments are heterogeneous. Data envelopment analysis and stochastic frontier analysis are generally difficult to relate to KPI’s. The use of an explicit and specific process model with an engineering content is therefore exceptional.