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There’s a Problem With Technology Integration When It Comes to Public Transit in the U.S., and It’s Not the Tech

There’s a Problem With Technology Integration When It Comes to Public Transit in the U.S., and It’s Not the Tech

Insights & Perspectives
Problem With Technology Integration US Public Transit

If you had to assign a letter grade to the United States transportation industry, what would it be?

You might be surprised to learn that America’s transportation infrastructure has failed to score higher than a C-minus for several years, but if you look closer, the reason becomes clearer. In the transit sector alone, about 19% of vehicles are in poor condition, and most railways are made up of legacy infrastructure. Even if more Americans decided to take public transportation, 45% don’t have any access, according to the American Society of Civil Engineers.

Government officials realize this, which is why a $1 trillion infrastructure bill secured a bipartisan win in Congress this year. The deal will expand and modernize roadways, bridges, public transportation, and digital infrastructure — all of which are pillars of an efficient, connected society.

Modernizing transportation infrastructure is a massive undertaking that involves large-scale technology integration. Luckily, the technology is available, but enormous volumes of data are still trapped in silos. Breaking down those silos and utilizing the data to fuel change management will improve the customer journey and drive operational efficiency.

This blog post will specifically look at U.S. railroads and what transit organizations can do to bring them up to speed, but know that these problems extend across all modes of transportation. The entire U.S. transportation industry needs to realize its vision of a smarter system — one where all modes are integrated with each other and additional pieces of city infrastructure (electric, water, trash collection, etc.). Only then will a region truly be able to function in real-time and move its citizens where they want to go, all while minimizing congestion and pollution.

Improving the Customer Journey

It’s possible to build smarter rail infrastructure; technology is not the issue. What’s really preventing transit organizations from closing gaps is siloed people and processes. Data analytics that are integrated across an entire organization’s assets and mined for insights through artificial intelligence can be incredibly powerful. Siloed data and teams, on the other hand, promote deficiencies in the customer experience. In the latter case, the result is a bloated, inefficient transit service.

Think about a hypothetical transit agency in a large city that offers regional rail and light rail options. The agency has implemented operational systems and hired staff for each of these modes of transportation. But it’s rare for them to share actionable, timely data on passenger journeys — even though many people use multiple modes in a single trip. As a result, passengers are subject to lengthy wait times at some transfer stations while the rail lines duplicate each other’s routes in other areas. All that translates to wasted time and money and disincentivizes people to regularly use public transportation.

By breaking down silos and encouraging technology integration, agencies can better understand the customer journey and improve the design of the transit experience. But technology itself won’t solve the problem; it’s only an enabler. Agencies need to thoroughly invest in change management. Even if an agency pledges $100 million to collect and analyze more transportation data analytics, nothing will change if it doesn’t use the data to drive behavioral changes across the entire organization. That’s a people problem that must be addressed through strategic thinking and cooperation.

Achieving Operational Efficiency

Data silos also have an enormous impact on operational efficiency. Consider how complex public transit is in the U.S. Agencies must manage the flow of passengers in and out of their stations, the maintenance of their equipment and infrastructure, and the logistics of getting equipment out — all on top of day-to-day operations. Not only are these systems siloed off from one another, but they also often have silos within them.

Without an environment driven by connected data, it’s difficult to determine what maintenance work needs to be done, where that work should be concentrated, and when it should be performed, among other factors. For instance, let’s say a public transit agency needs to temporarily take a rail out of service to repair a portion of the track. Unbeknownst to the team in charge of the physical track layout, the rail also needs signal repairs. But because the two systems are siloed from one another, the repairs are completed one at a time. This means that the rail is out of service for more time than it needs to be.

If the agency had technology integration, it could have performed both repairs at once to improve operational efficiency. And with real-time data collection and advanced pattern analysis, the agency might be able to predict when elements of the system needed routine maintenance before breaking down and interrupting service. Considering all the technology available, modern railway systems should function more efficiently — not less.

What’s Next for Public Transit in the U.S.?

Transit currently has the lowest grade on America’s infrastructure report card. There’s currently a $176 billion public transit backlog in the U.S., and that deficit threatens to balloon to more than $250 billion by 2029. Considering the work that needs to be done, the transit sector is a great place to start solving this problem with technology integration.

The Congress-approved infrastructure bill will devote countless dollars to the modernization of infrastructure. However, the country won’t be able to truly ease the transportation industry’s issues without breaking down organizational silos and embracing change. Although we only explored transit in this blog post, all transportation sectors can encourage collaboration and use data to facilitate change management.

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