Moving towards a predictive analytics approach for railroad safety and compliance with an intelligent operational testing system (iOTS)

Freight railroads, regardless of size, are always working towards the goal of zero accidents. Through consistent, effective operational testing, rail employees are held accountable to safety procedures that comply with Federal Railroad Administration (FRA) safety rules and regulations.

But while the road to safety may be paved with good intentions, it can also be complicated by a lack of visibility into how safety standards are enforced enterprise-wide, or how effective your operational testing program is.

What’s causing this?

The state of ops testing

Operational testing (also known as ops-testing) is nothing new for Class I, II, and short line and regional railroads in North America. Mandated by the FRA, railroads must ensure that their employees are complying with safety procedures that, at the end of the day, keep them safe, and create a safe work environment.

But over time, accidents and incidents occur. They pile up—to the point that 39% of accidents and incidents from 2013-2017 were due to human error. There may be a higher rate of accidents in one geographic location or due to conductor errors, but how do you know? Since the operational tests are conducted and captured on paper spreadsheets, the task of shifting through file after file and try to make sense of all the data without a tool to facilitate insights is daunting. It’s hard to tell if testing officers are meeting test quotas, and you may suspect that testing is more reactive to upcoming audits or following accidents, as opposed to empowering your employees to predict and stay prepared for the next inspection.

Is there an alternative approach to operational testing that ensures that good intentions align with measurable, trackable results?

Adding intelligence to ops testing

With intelligent operational testing, leveraging BI and data analytics, testing optimization, and artificial intelligence (AI) and machine learning (ML), freight railroads can identify and respond to trends to ensure more effective, efficient, and compliant operational testing.

Intelligence takes your ops testing program farther than a series of checklists and to-do’s conducted on a—hopefully—regularly basis. For example, business intelligence (BI) and analytics dashboards help you monitor safety parameters in a way that is hard to accomplish manually, scanning through paper sheets containing rows and rows of data. There’s a shift from responsive, time-consuming testing to repeatable, trigger-based test plan creation.

No matter if you’re a short line or Class I railroad, there are several ways that you can add intelligence to your operational testing:

1. Set up a strong data management process. Gather and store measurable and measured ops testing data in a cloud environment for cross-department visibility, quick accessibility, and future data analysis.

2. Conduct trend analysis: Once you’ve migrated your data to the cloud, you can leverage data analysis to identify trends and patterns, and then respond to trends in your ops testing. You’re using your data to make smart business decisions, not just safety decisions. Where are you allocating your resources, be they money or manpower? You’ll be able to see where test failures are periodically occurring by location, role, time of day, weather conditions or employee. With trend analysis, you can harness the power of analytics to optimize your inspection allocations, increasing inspection frequency where the risks are highest.

4. Respond to AI/ML recommendations: This takes your intelligence a step farther. AI and ML capabilities can enable reporting for senior leadership, making the story of your safety clearer. You can also get recommendations so you can focus on departments or territories and see where compliance breaches are happening more often historically, and then predict where and when safety incidents are likely to occur, based on causal factor correlations as well as historical trends.

Where intelligent operational field testing can take you

Bringing together what-if scenarios that help you optimize your testing and AI/ML algorithms to provide intelligent recommendations, railroads can move from minimum to intelligent ops testing, resulting in comprehensive test plans, better test schedules, and enhanced employee and department tracking. Applying this approach to your operational field testing leads to higher enforcement and efficiency (thus, cost savings) of ops testing and safety procedures, reduced penalties, and increased safety.

The operational field testing journey with Kansas City Southern

Kansas City Southern (KCS) is one of today’s innovative, visionary railroads. Recognizing the value of applying leading-edge, innovative technologies such as cloud, big data analytics, and machine learning, they partnered with us to leverage these technologies to drive improved efficiency of operational testing.

Rules rule the day in the life of a railroader

The journey started with the basic recognition that rules and railroads move hand in hand. They are so enmeshed in railroad culture that it’s almost cliché to say that rules are there for a reason—but they are! For a railroader working in the yard or on a train, surrounded by big giant equipment around them, one small slip can cause a damaging swipe of the big machines. This can pose a huge safety risk not just for humans, but also for equipment.

Either way, the cost of a slipup or error is extremely high!

Because of this, the FRA has mandated operational testing and safety enforcement rules that railroad employees need to follow in order to ensure that a railroad can run securely and safely. Operational testing, also known as ‘ops testing’, acts as a daily tool that helps ensure all that railroad employees are aware of the rules applicable to their duties. This ensures compliance for the enterprise and helps them avoid the penalties associated with any violations.

KCS made it a top priority to start their ops testing digitalization with centralized record-keeping and easy retrieval of historical records. They wanted to make sure that the data needed for audits and regulatory compliance was available without chasing multiple repositories of test execution data across a complex maze of hierarchies and locations—which is no easy or quick task by any means.

This would also ensure all the employees are regularly certified and able to work in compliance with FRA regulations, adhering to the General Code of Operating Rules (GCOR), and any other territory-specific rules or guidelines, all by directly importing the test libraries into their master test programs. By having the data in a central cloud, it could also enable better planning of tests, testing frequency, quota planning, and, lastly, account for regionalization of test plans for different locations.

Deriving test data trends and insights

Once we had all the data in a centralized location, slicing and dicing the operational test data—including analyzing it across the various dimensions of employee, role, locations, time of day, and even studying the data by test type, top failures, and seasonality—was a low hanging fruit. We worked with the KCS team to create insights using dynamic dashboards, giving them near-real-time viewing of the various parameters associated with the test programs. The trend analysis helped them understand the current situation and supported the decision-making process for planning test programs as well, responding to the data by, for example, increasing the frequency of tests where the failures were higher.

Because the OTS solution was integrated with other enterprise applications like SAP and HR systems, we have assured consistency across relevant platforms which among other things helped enhance compliance, recordkeeping and overall effectiveness of the Program of Operational Testing.

The user interface of the OTS tool was specifically designed to speed up the onboarding of new testers. It delivered a guided interface so that the testers could complete their tests by simply following the intuitive prompts and workflows the system generated and complete the work in the field itself using mobile devices, tablets, and laptops. The advance notifications capability that was programmed to alert testers about upcoming tests, schedules, and approaching deadlines was very well received by the testers.

Envisioning the predictive world of intelligent ops testing

As we look ahead into the future of modern rail transportation, we can apply predictive analytics algorithms to the piles of safety testing, big data and go beyond the FRA mandates to intelligently identify causal factor correlations. The goal would be to predict which employees will have the tendency to not wear their safety glasses on a dark wintry evening in December or which unprotected railroad crossing will likely experience the next accident or a near-miss due to train conductor negligence. Operational testing moves from a reactive position to a predictive process that takes your railroad’s safety initiatives to the next level.

Get on the (rail) road to safety—start the journey towards an intelligent OTS!