How am I doing for the data driven age

How am I Doing?

The city of Boston’s Chief of Staff Daniel Koh announced a data-driven effort called City Score to measure how well the city of Boston is doing - in a Ted X talk called “What Government Can Learn From Baseball”. Uses of analytics to better quantify a city’s varying needs gets a thumb’s up from me.

(Hat tip to Next City blog for writing on this.)

There is the hope that other cities will follow Boston’s tech lead and want to adopt City Score or improve upon its ideas. This is the open source/ data accessibility revolution in government, coming to life, coming down to an accessible level. This is government, reaching back to the iconic New York Mayor Ed Koch, asking “how’m i doing”?

The first thing: I’m surprised that the idea of coming up with a score for a city isn’t more common.

Managing a complex city, or even a city agency is a binary game at its pulsing heart – did we fail and get voted out? Did we succeed and stay in office? Given the smarts and success of community–focused policy wonks who help win elections for both major parties, I would think that they would have a sense of what needs to be done to maintain a tolerable level of competence in the city leadership.

“It literally started with the conversation around the government batting average,” Mr. Koh said. NY Times

The second thing: this idea sounds sexy, and Koh’s speech indicates that this is about more than just the one-number score. But by leaning on one score leads to questions about just how granular the Mayor’s attentions will be able to be with an aggregated score - especially on that mixes issues that could be more immediately affected (like traffic) and long-term issues (education, income mobility).

The description talks about Mayor Walsh being able to see key performance indicators on a dashboard… Which seems a touch outmoded in this era of sensors and available data. (Why?) Especially for a city, depending on what the leader of a city sees as his charge.

Is it to maximize the happiness of an influential sector? Is it to appease another sector? Is it to make very section happy, and down to what level?

Which begs the question of weighting. Will the heavily trafficked entertainment districts see more attention? Will crime in the areas with more arrests get more attention? Will the areas with higher levels of engagement/ complaints see more attention? Will the area with more influential Walsh loyalists see more attention?

Can a city be as data-driven as a private sector company when the bottom lines are so varied, so amorphous? When the analogue to the profit/ loss statement doesn’t translate into dollars that can be aggregated?

The batting average analogy gives a hint to where the mindset is here – coming up with a single number that some will find very useful – say, investors or news reporters – without digging into the nitty-gritty. In this way, “big data” can give the security of an answer, without dealing with the small potatoes, the nuances of what that number means. We know from baseball that a .300 hitter is pretty effective, but a .300 hitter who can post a .500 slugging percentage is better than one who posted a .300 slugging percentage.

The aggregation, in particular, is a difficult process. How does a city know how much weight to give crime or traffic? How to judge the irreversible but long-term effects of pollution w/r/t “How’m I doing”?

We have the quantitative chops to evaluate where the problem points are in a city other than from complaints. How does a city know where it is excelling, where people are impressed? How does a city know, the day it happens, whether it is paying attention to the things that the electorate really gets cheesed off about – like shoveling snow promptly? Is crime affecting people personally? The benefit could be to make the city more generally responsive - or more locally responsive.

This process is a positive, far better than swaying only to whims and media-ready initiatives, it’s being responsive, a servant to the people as government should be.

Many questions, and kudos to Boston for becoming a lab for the question of how we can use data to define what the city looks like, shiny glints and dusty blemishes and all.