Funding smarter cities the hard way

There’s money to be saved by the public sector and money to be made by the private sector from mining big data to build next generation cities. But who’s going to pay for it?

What happens when you put an American government bureaucrat, an academic, a venture capitalist and an IT executive together to talk about using big data to make our big, bad cities smarter?

The answer is furious agreement that there’s money to be saved by the public sector and money to be made by the private sector from mining big data to build next generation cities. But who’s going to pay for it?

The United States has $US16 trillion in federal debt, about $US3.7 trillion in municipal debt and an unemployment rate kept down largely by poor workforce participation.

The mind-bendingly stupid sequestration is still ringing in the average American’s ears; Washington has made it abundantly clear that smarter cities are not a priority in that town. Even though 82 per cent of America’s spending is on Medicare/Medicaid, Social Security and Defence, it’s only spending outside these policy areas that’s under any real pressure right now.

When we talk about smarter cities, we’re talking scalable solutions for increasing energy efficiency, reducing traffic congestion, improving public transport, streamlining delivery of government services and even mapping and predicting crime levels for allocating police resources. That’s to name a mere few from literally thousands of ideas that either save public money, create job or both.

But Washington doesn’t build cities; cities largely build themselves. So why aren’t more of these proposals getting off the ground in the land of the free?

A four-pronged debate

This four-pronged discussion unfolded late last week at the 174-year old Boston University in the northeast state of Massachusetts for an IBM ‘Smarter Cities’ conference. Not only did the session highlight the sometimes matching and sometimes conflicting agendas of each of these four stakeholders – a problem for all cities hoping to smarten up, not just those in the US – but a demonstration of why the American federal debt debate is so shallow.

The players involved were City of Boston performance manager Devin Quirk, Boston University head of systems engineering professor Christos Cassandras, Black Coral Capital senior associate Michael Bishop and IBM smarter cities executive Jurij Paraszczak.

Quirk, the bureaucrat, has the data, but he hardly knows what to do with it. “Government can’t do this kind of analysis on its own; we need a lot of support and a lot of help,” says the earnest City of Boston official.

Prof Cassandras, the private university academic, has some impressive analytical capacity but has run out of patience after providing PhD students for no cost to the government for projects that often don’t go anywhere.

“Good faith and volunteer spirit are at limit,” says the engineer, in one of many moments of obvious frustration.

The US economy is still sputtering out of its breakdown, keeping tax revenue low and demand for social services high on federal and municipal governments. Smarter city savings are much needed, but public spending is a political liability.

Bishop, the venture capitalist, is ready to roll. The Federal Reserve has encouraged enough investors out of the bond market and into riskier plays. The Dow Jones is hitting all-time highs, along with US government debt. He sees opportunities for scalable projects to be brought to life by the solutions born from analysis of the data emerging from big city problems. Not all of them, but some definitely.

But even if you prove the value proposition to a US government – federal, state or local – there’s a bottleneck for projects that need to be scaled up. Without scale, there’s no financing and without financing there’s no project.

Paraszczak, the IT executive, sits circumspect in the middle of all this. “We talked about data today, as if data was an easy thing to acquire, as if data was clean, as if data was available, as if data could make money. None of those things are true.”

A viable funding model

That speaks to part of the problem, but it wasn’t the bureaucrat, the academic, the venture capitalist or the IT exec on stage that started this funding model conversation. It was a 40-year planning and development veteran John Connery from Melrose, Massachusetts sitting in the audience that illustrated why this is conceptually tricky.

Connery made the point to the panel that if we’re to imagine the path towards creating the city of the future, it might be instructive to look at how we ended up with the cities we’ve got now.

Water and sewer systems, both of which are the subject of smarter city ideas, are two of the smarter city projects of generations past that still serve the public.

“If we come eventually to a handoff to a public necessity, then it needs to be publicly funded in some way,” says Connery, who pays water and sewerage fees on his developments to this day. “Some people don’t like government and don’t want those people involved, but it is a public service and it becomes a public necessity.”

He proposes a small fee on permits and licences – we’re talking single digits dollars on the thousands spent for each piece of development paper – that could go to an independent body charged with greenlighting proposals of public priority that need public and private money to work together, as well as approving ideas where venture capital money needs only scale to be unleashed.

Like the clean data, this body, which has a smell of Infrastructure Australia about it, doesn’t really exist.

Both sides of US politics, from federal down to local, claim to speak for sole proprietors like Connery. But the benefits of big data might not be realised on any meaningful scale until the US comes to grip with when it’s appropriate for public and private dollars to work separately on infrastructure and service delivery, and when they need to work together.