“All of a sudden it is cool to be a data geek.”
Spoken enthusiastically by Tim Paydos of IBM, these words perfectly encapsulated the mood of Thursday’s 2014 Data Innovation Day. The conference, now in its second year, is a product of the Center for Data Innovation, a non-partisan think tank that researches the growing influence of information on our economy and society. This year’s conference featured a daylong series of talks and expert panels focused on the past, present, and future of big data analytics.
On a day jam-packed full of highlights, the ‘Smart Cities’ panel featured a particularly lively discussion on the topic of utilizing data to help cities operate more effectively and efficiently. According to the panel, ‘smart city innovations’ hold opportunities for both public and private sector actors to better deliver services, dialogue with citizens and customers, and ‘listen’ to city through the colossal amount of data it produces every day.
The panel was moderated by Paul Barbagallo of Bloomberg BNA. It featured the following speakers:
- Michael Flowers, Former Director of Analytics, Office of Policy and Strategic Planning, New York City
- Ian Kalin, Director of Open Data at Socrata
- Timothy Paydos, Worldwide Director of the Government Big Data Team at IBM
One of the most startling assertions from the panel is that big data analytics is not a novel development. Rather it is an inevitable step in the evolution of everyday business operations.
Paydos argued that we won’t even be talking about big data analytics in 4-5 years the way we are now. Just as we no longer hold seminars and produce white papers on the merits of e-commerce, the utilization of large, open data sources for public and private benefit will just be something we do. In fact, those institutions that fail to leverage their data will find themselves rapidly falling behind the curve.
These assertions may not come as a surprise to early adopters, but for many it is a clear wake-up call that we can, and should, do more to utilize the large quantities of data produced by our built environment. As the panel mentioned, cities are the perfect laboratory for this type of data innovation. Kalin rightly observes that unlike countries, cities are very similar. More specifically, they almost all provide a comparable suite of services – like sanitation and a police force – and have host of shared concerns. If a pilot innovation takes place in one city, it is much easier to export that development to another city, and then another. More importantly, cities all produce an incredible amount of data, from the issuance of permits to crime statistics, which have the ability to tell a very detailed story about what is going on. This is equally as true for smaller cities as it is for mega-cities like Los Angeles and New York City.
Given these developments, the panel identified a number of key lessons for any city looking join the ‘smart city’ revolution.
Executive support is vital to launch.
Michael Flowers was the most emphatic about this lesson, as he credits the much-lauded success of his office to the unequivocal support of his previous bosses, former Mayor Michael R. Bloomberg and his Chief Policy Advisor John Feinblatt. This is evidenced by some of the public statements made by Bloomberg in the later stages of his tenure:
“Since day one, we’ve empowered everyone in our Administration to try new and bold approaches to tackling old problems and base solutions on hard data, not ideology or partisan philosophy.”
“Michael Flowers and his team have exemplified our approach and taken it to new levels of success. From creating powerful assessment models for identifying high-risk illegal housing conversions, to using the latest data and technology to combat property fraud and prescription drug abuse, the Policy and Strategic Planning Analytics Team has been at the forefront of our innovative problem-solving strategies.”
Ian Kalin agreed by stating that the simple act of a mayor asking about big data signals a major cultural shift – and the passage through a significant hurtle. Rather than a policy or a piece of legislation to spur data-driven decision-making, Kalin added, you need a leader to make things happen.
“Don’t fall for the technology head fake.”
These words were spoken by Tim Paydos to knowing nods of approval from the audience. In essence, his warning was for city leaders and planners who seek out big data without asking why they need it in the first place. This can lead to wasting valuable time and resources, and can ultimately end up in frustration rather than transformation.
Instead, you should seek to find out how others are using big data, identify your business requirements and potential use cases, and then see if you can apply one to the other. This is often an iterative process. However, the key motivator should be the burning question that requires a novel approach. “Why are there so many structure fires in the northern part of the city this year?” “How can we continue to provide the same trash service with a much smaller budget?” The key to providing a good answer is formulating a great question.
Smart Cities require a smart adoption strategy.
From his experience in New York City, Flowers found that policy decisions can have upriver and downriver impacts, which is why cities need to be smart about adoption. He emphasized that cities must start with very specific problems. The key here is to start small, engage with your citizen customers, and iterate. Flowers especially highlighted the need to create innovation ecosystems. In other words, cities must create an environment in which city officials, private industry, and citizens can exchange ideas and provide meaningful feedback. We’re all in this together, and it is up to governments to ensure that they evolve with their localities. This starts with effective engagement.
The overarching message here is that big data has arrived. Municipalities and businesses that choose to ignore this revolution will find themselves relegated to the corners in the larger discussion of how to make cities more effective, efficient, and yes – smarter. Hopefully these steps will help the next wave of adopters understand that the real hurtles to smart innovation revolve around leadership and not technology.
For a good article about Michal Flowers’ “geek squad,” check out this article from the New York Times.
For a look at open data at work, click here for New York City’s open data hub, powered by Socrata.