Productivity – Community of Metros Benchmarking Group

Research: Managing and Reducing Absenteeism

March 16, 2021November 4, 2019

Absenteeism presents widespread impacts of loss of productivity, delays and reduced morale that would affect metros’ efficiency and reliability. Currently CoMET and Nova have an average staff absenteeism rate of 4.7% (based on 2018 data), creating significant challenges for managing service provision. This study investigated levels of absenteeism at CoMET and Nova metros, identified and explored underlying causes of absenteeism, and discussed best practices to manage and/or reduce absenteeism. In discussing the factors that metros have identified that lead to absence, it is clear that absenteeism does not have one single cause and is influenced by multiple internal and external factors. It therefore requires a comprehensive set of solutions to manage and reduce.

Approaches and actions to manage and reduce absenteeism focus on measurement and management of absence data and positive approaches to employee relations. Initiatives within these categories help ensure that metros understand the scale of the issue across different organisational parameters (such as absenteeism rates by team) as well as developing an overall culture of care and trust between management and labour.

Research: Multifunctional Staff

November 4, 2015

Nova members have identified a need to innovate to increase staff productivity levels, and asked RTSC to investigate how metros around the world have used multifunctional staff. A wide variety of multifunctional roles were identified, classified into six broad types as shown below.

The best multifunctional staff roles fill in what would otherwise be unproductive time, with productive activity. This is often accomplished by matching functions that need to be done at separate times of day or functions that can be slotted in between other activities in a single location, such as light maintenance within stations.

Multifunctional working also has an important role at increasing staff satisfaction. By combining tasks, staff have the opportunity to work in a more varied and interesting role. This can improve the attractiveness of the metro as an employer and improve staff motivation. For example, one metro recorded reduced absenteeism among their most multifunctional staff. Multifunctional roles can also create a career progression – especially for staff who are technically excellent but do not necessarily want to manage other people.

Research: Unattended Train Operation

August 6, 2015March 4, 2014

RTSC’s recent research into unattended train operations (UTO) has investigated the role of human operational support on UTO lines. In doing so, a key finding relates to the use of attendants or train captains – metro staff members who are based in the passenger car, rather than in a separate driver’s cab. Formal definitions of Grades of Automation as in IEC-62290 assume that if a staff member is onboard, they are fulfilling a necessary role, in operating the train, as in London’s Docklands Light Railway where attendants close the doors. The assumption is therefore that lines capable of being operated unattended (Grade of Automation 4) are operated unattended. This research study has found that in fact some metros with GoA4 lines actually use attendants on all trains for other reasons, for example to provide customer service. This has led RTSC to describe this type of line as ‘Attended GoA4,’ reflecting the fact that it fits the specification for a GoA4 line as described in IEC-62290, but is not being operated unattended. The diagram below illustrates how ‘Attended GoA4’ automation fits in with the grades of automation.

Adapted from IEC-62290 for the purposes of demonstrating differences in the real-world operational application of the formal Grades of Automation (GoA1-4) defined in the standard.

The case study explored in more detail the actual staffing levels used or planned on participating metros’ automatic lines. The total number of operational staff was compared with the number of assets (stations and trains) in service, providing metros with a useful benchmarking metric that normalised for differences in line length and service level. A typology of staffing models was also developed and linked with associated staffing levels. This work on staffing was complemented by investigation into the technologies required to enable automation; their costs; and metros experiences with their reliability.

This research was presented as a poster at the 94th Transportation Research Board of the National Academies Annual Meeting in Washington DC, in 2015.

Research: Train Driver Productivity

March 26, 2014July 20, 2013

A Nova research study on train driver productivity aimed to identify the most important factors that influence driver efficiency, understand what methods operators have successfully used to modernise restrictions to working arrangements and identify the scope for metros to modify the most important constraints, rules and parameters that have a negative effect on both driver productivity and costs.

The study found that metros need to have sufficiently flexible labour rules to achieve higher levels of driver productivity. Correlating the level of working time flexibility with driver productivity showed that less restricted metros were more productive than metros that face stricter constraints. Organisations with part time drivers and / or the ability to utilise split shifts were associated with higher levels of driver productivity and increased effectiveness of driver time at work (better able to cover ‘peaks and troughs’ in service). Moreover, it was found that variable shift lengths were arguably more effective than split shifts for metros with a flatter service profile, allowing metro managers to adjust shift schedules as necessary and to avoid the build up (unproductive time) of staff during less busy and off peak periods. In the long term, savings from increased flexibility could more than offset the higher driver wages associated with greater flexibility. Increasing automation of train services through automatic train turnaround, remote booking-on for drivers and driverless trains can positively influence driver productivity and allow driver roles to be deployed more effectively through more customer facing roles.

It is hoped that the information contained within this study can be used to support negotiations with labour unions, government and other key stakeholders by showing evidence of how “imposed” restrictions may impact an organisation’s ability to improve and manage productivity.