State and local governments are firmly in the midst of massive IT modernization efforts and striving to harness the power of data analytics to better accomplish the mission at hand: helping government to operate more smoothly and efficiently via better technology. And data that the government could use to complete that mission grows with every passing minute.

A driving force in this data increase is mobility and the reliance on smartphones. Smartphones are woven into our daily lives and provide access to anything you could ever need with a few quick thumb strokes. All of the data garnered through mobile devices, among other methods, is already proving useful to several industries, but how can state and local government leverage this information to address day-to-day constituent concerns, namely infrastructure improvement?

Laura Schewel, StreetLight Data CEO, knows that analyzing that data from consumer smartphones and elsewhere has an important role in shaping how state and local government tackle infrastructure strategy, especially because it has the power to efficiently utilize precious government resources. In fact, we’ve seen these efforts manifest into concepts like SmartCities, “an urban development vision to integrate information and communication technology and Internet of Things technology in a secure fashion to manage a city’s assets,” according to Wikipedia.

In a recent conversation with FTI, Schewel explained how big data helps government entities approach the problem of lagging infrastructure improvements through coveted traveler data. By reducing the cost of data collection and moving away from traditional road sensors or surveys which can be time-consuming and expensive to synthesize, leaders can glean insights from big data much faster at a lower price point. “Instead of spending $10 million on sensors, you can spend a million dollars on big data, a million dollars on sensors and save that other $8 million for something else.”

Not only would big data analytics assist with infrastructure costs, but it could also better educate decision makers about project prioritization. Schewel elaborated, “Building things in the right order so you can get the biggest bang for your buck earlier, that’s where big data really comes in…Data can help you ‘triage’ where your biggest problems are and where the solutions that you can afford will be most effective.” By more thoroughly understanding what makes sense for a city based on its residents’ travel data, projects that matter most to the community can be moved forward, resulting in happier constituents.

A recent case study from StreetLight Data about the city of Lafayette, CA exemplifies exactly how this technology is being applied at a local level. This use case looked specifically at traffic congestion in Lafayette, where StreetLight Data provided a thorough overview of the traffic patterns and transportation landscape of the city. The data for this particular project revealed that improving the flow of “through-travelers” on S-24 would significantly mitigate traffic. That knowledge empowers Lafayette to make educated decisions about resolving their traffic pain points and put forth infrastructure improvement policy that actually gets to the root of the problem.

However, the largest hurdle that innovators will likely face in integrating a big data analytics program for something like infrastructure purposes is a less than open-minded staff that might not feel as motivated to adopt yet another change to the system. “Our biggest challenge is that energy of activation where we get people to take the time to integrate the new [program]…you have a lot of inertia with people who already know the old [way] and you need pressure from either a really forward-looking mid-level employee at the agency or a progressive top-down leader to help get people excited and take the steps to adopt newer technology,” explained Schewel.

While that dynamic still exists and creates obstacles for private technology vendors, Schewel emphasized the importance of private and public sector partnerships in addressing everyday citizen concerns like traffic and infrastructure. In order to truly innovate, she urged government agencies to better embrace “soft assets” like software and data, as opposed to almost exclusively relying on costly and, arguably, ineffective “hard assets.”

She stated, “Infrastructure has been overlooked in a lot of the conversation about public/private transportation collaboration because so much of it has been on consumer-facing things like Uber, Lyft, and apps that show you when the bus is coming, all of which are wonderful for transportation. But all of them need a road and the roads are falling apart.”

At the end of the day, the partnership between public and private sectors, at least with regards to infrastructure decision making are imperative. And that means implementing data analytics tools and welcoming the knowledge and benefits that come with it.