In the open data movement, what is stopping us from data-driven decision making in city and county governments? Before open data was the norm, data analysts and scientists lacked the raw materials; data itself was simply not available. Today new explanations and excuses have emerged. In particular, misconceptions about working alongside private-sector partners have stalled smart, data-driven governance.
As a company that offers to jumpstart city and county data science efforts, we at Open Data Nation feel compelled to not only share what we hear, but debunk these myths, one by one.
1. We don’t know where to turn.
It is truth that governments are cash and resource strapped and don’t have time to discover data scientists and weigh solutions. That said, there are groups convening city administrators -- MetroLab Network, What Works Cities, and Data-Smart City Solutions to name a few -- that could be effective distribution channels for information. The norm, however, is to refuse to recommend, promote, or otherwise even mention relevant vendors and consultants. Each city is out on their own to find their own answer, and barring the resources, end up at the doorstep of incumbent firms.
Cities and counties that align with pro-bono assistance offered by incumbent technology firms end up paying big bucks when their problems are inevitably too difficult and the solutions too complex to resolve for free. What starts out as a well-intentioned effort at public-private-partnerships, pushes out those who are capable of reform and instead, embraces those who are selling woodchips as nutmeg.
2. We want to build this capacity in house.
Newsflash, data scientists get paid an average of $113,436 per year. If budgets are tight, cities and counties certainly do not have the money to pay that salary, plus benefits. Beyond that, it has required the restructuring or creation of entirely new entities within government, in the few US cities (e.g., Chicago) that have started to do data science in government. If your city is starting from scratch, at best they are two years away from any data-driven system of governance. Even then, the best intentions and staffed teams may be too disruptive and painful to stick around very long.
3. We don’t have enough data.
Frankly, if this is your city’s excuse, we challenge you to identify your source. Look deep enough and it is likely a vendor that is selling your city a software that costs more, the more data your city uploads. The fox is in the hen house. Ring the alarm. Our analysis shows that 2/3rds of US cities we surveyed are ready for FIVAR, which predicts the outcomes of restaurant inspections and has been proven to generate an estimated $2 million in savings in the first year, per locale. It is a turn-key smart-city solution that requires only one data set to be opened up – restaurant inspection results – and results in safer, healthier cities.
The misconceptions about working with private-sector data science consultants are not helping to promote smarter, more data-informed decision making in city and county governments. Put simply, with a little bit of money and networking, the private sector can help cities and counties get started, even if they are doing so alongside the growth of internal capacity and the publishing of more open data.