When I moderated a panel recently at Cisco’s Executive Panel on real world implementations of the Internet of Things, panelist Bryson Koehler, who is the CIO at The Weather Company, noted that in addition to the over 20 terabytes a days of data that his organization looks at, he’s equally interested in available data sets that aren’t internally generated. For example, it’s not just what could be learned from all of the weather station sensor data but what else could prove valuable, like geological data or pollution data that could be leveraged.

I mentioned this because I think Koehler represents a type of thinking in IoT that sees the value of deploying sensors and upping connectivity but also sees the other side of the equation which relates to analytics and what data scientists can do with all the available data, much of which could be public. Because as the analytics tools improve, the data itself has increasing amounts of value because business outcomes can be produced from crunching larger and larger data sets. All of this raises the specter of companies warehousing and selling access to their data.

My colleague Kate Fehrenbacher reported recently on a startup called Urban Engines, being launched by Stanford computer science professer Balaji Prabhakar and Google exec Shiva Shivakumar. Urban Engines uses a systems for modeling how commuters and transportation flows are behaving but does so not through the placement of sensors but through using algorithms to crunch data left behind by transit cards. The startup is a classic example of generating value from the available data, a concept familiar to startups in the smart grid analytics space where third parties have been eagerly building business models from the flow of smart meter data.

Urban Engines is interested in using incentives to help shape commuter behavior so that transportation flows more efficiently. The company’s branding so far has been built around saving the individual commuter 10 or 20 minutes in their day. And this question of end value and end market is one that analytics firms invariably must grapple with, because for a startup like Urban Engines the sale typically comes from working with a public agency like a city department of transportation.

Because as the population swells, so is mass urbanization. In China alone, the government is pushing a plan that would make 91 million Chinese citizens city dwellers in the next seven years. Cities will increasingly grapple with how to make core infrastructure like public transit more efficient and startups like Urban Engine are betting that for desperate cities, their solution of using existing data pools instead of widespread deployment of new connected sensors, could prove to be the most accessible option.

Transportation is an area where significant opportunities exist for using better access to data, particularly geolocation data being generated by smartphones, to improve transport. I authored a recent report on how the ride app market is disrupting the transportation sector that examines the heated competition in ride sharing as well as a look at how the broader transportation market is facing disruption (To read the full report, see “The risks and rewards for the ride-sharing market in 2014.”) Because the likes of Uber and Sidecar are likely just the tip of the iceberg in terms of how your smart phone will start to impact how people move about cities. Urban Engine is yet another angle for improving transportation efficiency, a trend that will become a cornerstone of the smart city.

In the end what I think will offer the most value to consumers is a broad integration of multiple tools, meaning a meta-app might help provide incentives and commuter flow information in the vein of Urban Engine, combined with public transit options, ride sharing options, car sharing and perhaps even public-private van partnerships as has been tested in Helsinki.

Yes, this is a bold and ambitious app, probably best suited for a platform like Apple or Google, and there are many conflicting interests here. But the underlying trend is the same: as data becomes more available and we each become more connected, smartphones have a larger and larger role to play in increasing the number of transportation options and improving transportation efficiency. And many businesses can be built on existing data, freeing startups from the more capital heavy burdens of implementing sensor infrastructure.