A benchmarking framework for understanding bus performance in the US

Abstract

PurposeThis paper describes a benchmarking framework applied to medium-sized urban public bus agencies in the United States, which has overcome the challenges of data quality, comparability, and understanding.Design/methodology/approachThe benchmarking methodology described in this paper is based on lessons learned through seven years of development of a fixed-route key performance indicator (KPI) system for the American Bus Benchmarking Group (ABBG). Founded in 2011, the ABBG is a group of public medium-sized urban bus agencies that compare performance and share best practices with peers throughout the United States. The methodology is adapted from the process used within international benchmarking groups facilitated by Imperial College and consists of four main elements: peer selection, KPI system development, processes to achieve high-quality data, and processes to understand relative performance and change.FindingsThe four main elements of the ABBG benchmarking methodology consist of 18 subelements, which when applied overcome three main benchmarking challenges: comparability, data quality, and understanding. While serving as examples for the methodology elements, the paper provides specific insights into service characteristics and performance among ABBG agencies.Research limitations/implicationsThe benchmarking approach described in this paper requires time and commitment and thus is most suitably applied to a concise group of agencies.Practical implicationsThis methodology provides transit agencies, authorities, and benchmarking practitioners a framework for effective benchmarking. It will lead to high-quality comparable data and a strong understanding of the performance context to serve as a basis for organizational changes, whether for policy, planning, operations, stakeholder communication, or program development.Originality/valueThe methodology, while consistent with recommendations from literature, is unique in its scale, in-depth validation and analysis, and holistic and multidimensional approach.