To find the right way to measure the performance of an operator needs some efforts to achieve. Performance of operators has several levels. One is output-related in terms of figures on reliability and punctuality compared to the assignments and timetables the LPTA is demanding.
In general service quality parameters need to be defined monitored and controlled with effective fines or bonuses for aims. These parameters are important and can be calculated in an objective way, if data from coordination centre and operation system are monitored and vehicles are connected. But the most important level is often left behind: Customer satisfaction is not monitored.
Customer satisfaction is influenced not only by operational data but by external incidents like the traffic situation and through service quality and customer care of the staff. Most important should be to improve and hold a certain quality of service, while operation has to be ensured. Quality of service can be improved if customer data is surveyed and if available data from a strong constraints management can be used to analyse and evaluate the quality and the service level by operator.
The performance needs to be monitored and controlled by a quality management that is considering not only operational data but also the view of the customer. This should include available data on operational figures (cost/Km, punctuality, regularity etc.) AND on customer satisfaction (overall, punctuality, cleanliness, friendly service gained by surveys) as well as data from complaints management to improve the service. General quality parameters need to be defined, contracted and controlled in agreement with the operators with effective fines or bonus for aims on base of existing data and values .The crucial point is to contract the need of improvements and operational figures that cannot be underrun and to monitor and control them. Aims can orientate on basis of a percentage that could be reached or that has to be kept. External effects (traffic incidents) can be soften if the figures are discussed quarterly and the average is causing bonus or fines at the end of the year that are explained clearly and covered by the contracts.
At the end there are all kind of reasons and constraints and handicaps why the a service from the operator fails and the bus is not at the stop when the customer expects it to be. The customer can follow most of the reasons if they are communicated adequately. Sometimes a friendly driver is sufficient, welcoming the PT users, getting them informed about his state of knowledge, when there is a delay, giving an explanation what happened on the streets in the network, during operations, expressing an apology and a motivation to make up leeway by reaching the final destination. Staff that is focusing on service quality and is able to manage customer communication needs education and adequate payment. Monitoring is necessary but to get customer orientation into operation subjective criterions need to be considered in the contracts with the operators either by adequate bonus or malus otherwise operators will benefit from providing low quality and bad service at low costs."
Comparability is limited and local context matters. Beginning by the set of bus lines / bus bundles the operator is running with its specific traffic (e.g. congestions) and geographical (e. g. hilly) situations, socio-economic backgrounds in city quarters and urban agglomerations, regions etc. can have influence either on objective data (no operation because of frequent incidents and congestions) as on subjective data (e.g. holiday time, empty vehicles, much construction works and deviations). That prevent figures to be comparable and benchmark with other operators/systems/cities but on a local level figures do show in general where problems occur and which operators manage better.
For both: operational data (objective approach) as-well as customer satisfaction and customer complaints data (subjective approach) there is no easy way to transfer and compare the data in detail. There is a lack of homogeneous and consistent modalities to calculate the service performances. This may be a problem when you need to compare the performance between different operators on a large scale working under different conditions not respecting local conditions. It has a minor relevance if you stay on a local level in the same system and nearly no effects if you can compare directly the same service in the following year when the operator changed trough tendering. A solution to enable comparability is to launch on existing values (comparable or not) and agree on aims on basis of an percentage that could be reached or that has to be kept.
Compliance management sets the frame to bring the inputs together. It makes transparent in which extend the operator is performing by the book and the contract and is considering agreed standards and rules and quality parameter. By integrating available data on bad services (operational, survey and complaints data) it is enabling that the data takes an effect to improve the service. It can monitor the efforts and bad service/fines of the operator make it transparent and benchmark the performance.
To manage that available data on bad services (operational, survey and complaints data) takes an effect to improve the service a compliance management can monitor the efforts and bad service/fines of the operator can make it transparent and benchmark the performance of the compliance. This should be respected in future tenders. It must be ensured that consequences if the compliance of an operator is strongly underperforming should take an effect on existing and future operations. The possibility to resign the existing contract and to exclude the operator for the next/coming tenders should be given and made aware before operation starts.