In recent years, the use of self-assistance tools in stations has accelerated – driven by technological development, staff shortages, and reduced face-to-face contact during COVID-19. Considering emerging financial challenges, many metros are now reviewing station staffing models with the aim of improving operational efficiency while maintaining a good customer experience. Changing customer behaviours and staff shortages are key drivers of staff reductions, but there are also other drivers affecting station staffing models such as external policies and levels of crime.
This study included responses from 31 metros reviewing factors impacting staffing level decisions, customer service challenges in low staff stations, station staffing models, and opportunities to reduce staff. Examples of innovations to reduce staffing requirements across key areas of station staff responsibilities e.g. ticketing and customer information, were also presented, along with best practices carried out by metros and the most impactful tools used by both customers and staff in low staff stations.