Opinion: The players who own the big data that powers smart city infrastructure

Associate Dean of Research and Professor of Information Systems Michael Goul, who catalyzes interdisciplinary research initiatives that engage the business school in developments across ASU, presents his study on smart city issues.

By Associate Dean of Research and Professor of Information Systems Michael Goul, who catalyzes inter- disciplinary research initiatives that engage the business school in developments across ASU. He presented his paper on smart city issues at the 51st annual International Conference on Systems Sciences in January.

Everything we hear about information and communications technologies (ICTs) seems to be about how smart they are or how they’re getting smarter. Now the smart ICT lens is being zoomed way out to focus on cities.

Smart cities are most often thought of in terms of burgeoning urban areas where Internet of Things’ (IoT) real-time sensors and devices are deployed to improve the lives of citizens. These deployments range in application from smart streetlights to security-threat mitigation and data monetization. The smart city coming to the outskirts of suburban Buckeye, Arizona, thanks to one of Bill Gates’s investment firms, is supposed to include autonomous vehicles. These innovations redefine city infrastructure to include increasingly sophisticated IoT devices worldwide, which have been predicted to number 50 billion by 2020.

Leading the way are phone and web applications for citizen engagement, energy management applications, faster and more economical wireless communication technologies, and business applications in areas like smart buildings, health care, education, and mobility. There’s even a smart city ranking for 2017: Copenhagen, Singapore, Stockholm, Zurich, and Boston are the top five.

The one asset common to all smart city deployments and applications is data. Take Arizona’s future smart city. Numerous reports tout that the community will implement high-speed data into its infrastructure.

Data is an interesting type of asset — its cost per unit to manage is going down while its value is going up. IoT, data, and the analytics they enable are the key ingredients for smart. But guidance is limited for negotiating data and analytics ownership issues in smart city application contexts. That’s where W. P. Carey research enters to fill the gap.

I’ve found that for owners of smart city infrastructures where data and analytics are co-owned by all participants (tenants), there are higher infrastructure and communications capacity costs than when ownership is partitioned. Similarly, if tenants sign value-based contracts — those where all participants get a cut of the benefits generated by data and analytics sharing — the infrastructure capabilities to ensure the monitoring and tracking of all transactions can be extremely complex, and needed software execution requirements drive both costs and latency higher.

If newer tenants partner with complementors to their business interests and share data, and their complementors have contracts in place for sharing data with others, then new tenants’ proportion of data and analytics ownership in the smart city ecosystem can scale rapidly. Also, in a smart city ecosystem where there is little to no data and analytics sharing, a new entrant is not likely to gain much benefit from entering a contract to share data and analytics with one of the existing tenants.

These and other findings are providing first insights into contracting strategies that will matter to both smart city owners and their tenants. One thing is definite, without data and analytics ownership experience, smart city players can totally miss the fine print. 

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