There’s no question that America’s infrastructure is antiquated and in vital need of modernization. If we want our infrastructure to be more efficient, cost-effective and secure, however, we must prioritize mathematical and analytical insights that enable a smarter and more-innovative infrastructure system to meet myriad complex and evolving demands as well as help secure the nation’s global competitiveness for generations to come.

Infrastructure policy too often is structured around a series of disconnected “projects” and thought of in terms of road miles, tons of concrete, numbers of bridges or quality of repairs. Of course, these all have a practical role within any infrastructure package, but they shouldn’t be the driver of broader policies, especially if we don’t want to be rebuilding the same infrastructure in the near term. Decisions should be driven by data, not historical precedent. Sound infrastructure policy will look to data first.

Evidence-Based Decisions

At Carnegie Mellon, we’re often cited in media and interrogated by peers on our approach to analytical and technology skills education. We always begin from the premise that policy decisions should be grounded in evidence. We then determine the skills required to assemble the types of evidence needed for policymakers to make an informed decision. We launched the Metro21 Smart Cities Institute for this very reason: to develop and deploy technologies that inform better infrastructure decisions.

Our researchers are creating automated and affordable road surveys via a smartphone app, deploying similar technology for early warning of dangerous and road-crippling landslides, and optimizing routes for plows during major winter storms. Our ambition is to leverage operations research (OR) and analytics to inform yet-built infrastructure decisions. Combining usage data from water, electric and communication providers will provide insight into which areas in our region are likely to create demands on infrastructure and which areas will benefit most from future investment.

In an era where we produce continuous streams of data, the challenge for government isn’t to access that information, but rather to understand what the data are revealing and how best to act on them. A variety of mega trends (e.g., changing weather patterns and climate, mass migration to cities, rising sea levels, droughts, etc.) and the time scales during which they’re taking place will have profound implications for infrastructure.

Another major development is the capacity to sense and monitor infrastructure via sensors. Drawing evidence and data-driven insights from all these inputs requires a somewhat different set of skills. Misunderstanding or misapplying mega-trend or infrastructure data has serious repercussions. For any visionary approach to infrastructure policy, it’s imperative that government decision-makers at all levels have the advanced scientific tools necessary to make the right decisions using the right data.

The Power of Analytics

One of the best and proven ways to do this is using OR and analytics: the application of advanced mathematical tools that enable organizations to turn complex challenges into substantial opportunities. These powerful tools don’t merely evaluate existing solutions to problems; they enable novel policy to be designed and evaluated, thereby delivering prescriptive value to decision makers. They do so by structuring data into solutions and insights for making better decisions that offer improved results.

By leveraging large amounts of data at a societal scale, OR and analytics hold near-limitless potential to improve urban design and planning in ways that create greater mobility and connectivity, and are economically and environmentally sustainable.

Consider autonomous transportation. If autonomous vehicles are widely adopted, it will fundamentally transform our thinking about infrastructure. Will we need so much parking? How is space going to be used? Where will people live when they have new mobility options, and how will that affect development? OR and analytics help us ask the correct questions in those respects as well as determine answers based on converting data into information and information into grounded insights.

Applied well, these tools and methods would make all the difference in the long-term decisions essential for evolving our infrastructure and maximizing taxpayer investments. More specifically, a number of core areas stand out in this regard:

1. The gas tax from 1993 pays for our infrastructure, and that dates back to the 1960s. Clearly outdated, we need to reimagine infrastructure needs that are better suited for a modern world with different modes of mobility and transportation, such as electric and autonomous vehicles. This infrastructure package will have to use adaptive technologies that allow it to be resilient to economic and climate-change disruptions.

2. New ways of paying for our infrastructure will likely be needed. OR and analytics can provide traditional and upfront analysis that outlines cost benefits and efficiency gains throughout the package.

3. Improving infrastructure for the near future, while building in adaptive capabilities for the longer term, will ensure our infrastructure stays safe, effective and efficient for decades to come. This requires advanced mathematical models to develop an evidence base for next-generation infrastructure planning, engineering and payment models.

There’s broad, bipartisan agreement that our current ways of infrastructure and infrastructure planning continue to operate under antiquated, politically driven methods and models that accrue excessive costs and perform inefficiently. OR and analytics, however, offer a proven, scientific and powerful alternate pathway forward. The correct application of OR and analytic principles to the infrastructure package would provide robust insights that inform sound, reasonable and bipartisan policymaking and program implementation as well as fundamentally improve the government’s fulfillment of its public-service mission.

For seven decades, OR and analytics have delivered proven and profound value in the private sector with documented savings amounting to many billions of dollars. Now it’s time for OR and analytics to become the driver of a higher level of efficiency for the next generation of America’s infrastructure.