West Midlands Trains: A new era in competence management
We’re using information from on-train data recorders in promising new ways, says Adrian Champion, Head of Operational Standards at West Midlands Trains
For Adrian Champion, Head of Operational Standards at West Midlands Trains, automated driver competence indicators hold a lot of promise. Among other things, they supply the operator with incredibly detailed information. Here’s how, in his words, they can make a powerful difference to driver training and competence management.
On-train data recorders (OTDRs) record information about the operational controls of a train and how the train performs when those controls are operated. They’re similar to black boxes on aircraft. They're not new technology. We’ve been using them as a method of assessing drivers and doing investigations into train performance for many years.
But with the help of a piece of software called TrainServ, we now have the ability to analyse and compare this data over longer periods of time and across multiple trains, rather than just looking at one train on one journey. This gives us the ability to automate driver competence indicators.
The industry’s approach to competence management has been relatively static for the past 30 years and largely involves a manual process of gathering data. But I’ve always been interested in finding the next era of competence management.
When I saw RSSB’s research project on automated driver competency indicators (ADCIs), I knew the TrainServ software would provide competence evidence over a longer period of time, which would give us an opportunity to better understand consistency in human performance.
Another benefit is the ability to see more positive indicators of driving performance. That interests me as well. These positive indicators highlight consistent, skilled, competent drivers, which demonstrates how infrequently incidents occur when compared with driving hours and helps us better understand how to prevent incidents. Current methods largely rely on the absence of incidents as a positive indication, which is a weak form of evidence.
We wanted to understand whether we could gain assessment or competence evidence differently.
In particular, we wanted to enhance the way we train our drivers, as well as the way our drivers understand error management. Being armed with so much more evidence—including the positive evidence I mentioned—allows us to balance our understanding of how errors can occur. We can feed that information back into our training and management programmes.
Once we began the trial, we realised there was a lot more potential. We knew there was more that we could invest back into the operational railway. We’re only one operator, with a relatively small amount of data. Imagine what could happen if we scale this up to lots of different operators.
This trial has reminded us that we should be expecting our drivers to make mistakes. They’re human. Traditionally, our response to an incident or when someone’s made a mistake is to look at that particular journey on that particular day and try to understand what caused it. But as I said earlier, we can now use the positive indicators—across the hundreds of journeys—to balance our understanding of what happened.
If a driver has made an error, say, once in 300 journeys, we have a lot of positive evidence of skilful driving to use as a balance, rather than focussing on any incident that may have occurred as a result. We can help the driver process what’s happened, and we can learn how system changes can help prevent incidents and even start to predict when human error or system failures are more likely to occur.
Having access to data over longer periods has been eye-opening and will allow us to look at incidents, human performance, and competence management with a perspective that’s more in line with the fair culture we strive for.
Because the positive indicators have revealed that we have a lot of skilled drivers, we can move away from focusing on an absence of incidents or taking a microscopic approach following an adverse event.
We don’t want to be saying to drivers, ‘You need to change because you’re not driving in line with the policies’. Instead, we want to recognise that they’re the experts, and we should be learning from them to inform our future training programmes, policies, and driving styles.
We’d also like to give drivers access to this information directly so that they can see for themselves how they’re driving and where they can make changes, if necessary. Everybody wants to do the best they can, and we’d like to give them the opportunity to adjust their style themselves.
We’re already looking at how we can use these principles to develop our existing processes to foster a more transparent safety culture.
This article was first published in the April 2025 edition of Horizon, RSSB’s magazine for rail leaders.
