I'm a data guy. I loved statistics in grad school. I crank through spreadsheets on a daily basis. I've coordinated two national surveys on community land trusts and co-authored an analysis of foreclosure data for the Lincoln Institute. I work with software developers on tracking data for shared equity housing programs.
I'm as data-driven as the next guy.
But just because we can capture data on everything doesn't mean we should do it.
I remember a point I reached in my work a year and a half ago where I felt like I was spending just as much time measuring my performance as I was actually performing. I was filling out elaborately detailed tree structures with measurable performance targets. I was splitting each 15 minutes of my time into 16 different program categories. I was editing “mind maps” that showed how my program was linked to every program and committee in my organization in three or four different ways.
And all the time I was spending measuring my effectiveness—came at the expense of actually being effective. The act of measurement actually served to decrease productivity—reminding me of one of the central principles of quantum mechanics—that the act of observation changes the behavior of the objects being observed.
And I wonder—how did the affordable housing development field come to be in need of so much data collection? It's kind of straightforward, isn't it? Do we build good houses? Is our housing located in neighborhoods where the people we serve want to live? Are we providing housing at an affordable price? Is it accessible to people with disabilities? Do we stand behind our housing and our residents?
Doesn't that really cover it?
We already know that a stable housing situation improves educational outcomes for kids. We already know that paying no more than a third of your income for housing-related expenses is a good idea (and a quarter is that much better). We know that owning builds wealth better than renting, all things being equal. And we know that low to moderate income homeowners are less likely to fall into foreclosure if they live in housing that incorporates a strong stewardship component, such as a community land trust or a limited equity cooperative.
It's hard enough to develop affordable housing in a climate of decreased federal, state and local subsidy funding, increased competition for foundation support, and tightened mortgage underwriting standards. It seems to me that funders should be looking for ways to decrease our administrative burdens during tough times, in recognition of our having fewer staff to do an increasingly difficult job.
It isn't rocket science people.
I just read the “HUDSTAT” Web page where there is a sample analysis of veterans housing in California. After an elaborate process of data analysis, and drilling down into increasingly fine grains of data, two startling discoveries were made: (1) homeless veterans prefer to live close to full service VA centers, and (2) areas with the greatest affordable housing availability are far from the locations where veterans want to live.
Of course, this isn't stunning. Any VA caseworker who has been on the job for more than 15 minutes could have provided that information. But talking to a caseworker doesn't give you a series of nifty graphs. And because it is merely “anecdotal” information and not the result of a multiple-regression analysis, it just isn't worth that much any more.
And guess what? No amount of data is going to convince upscale neighborhoods to provide their fair share of housing for homeless vets. And until your local CDBG office starts providing you with extra funding to cover the cost of developing housing in more expensive neighborhoods, you're going to continue to develop housing in the lower cost, less desirable neighborhoods that your subsidy dollars will gain you entry to.
Our quest—is toward an illusory goal.
Everyone knows what the problems are—we have documented them all in 14 gazillion different ways. The issue is whether there is the political will to try to address the problem. And there simply isn't. Let's face it—we'd much rather throw money at privatizing the space program than solving the affordable housing crisis.
But hey—if we can't solve it—then maybe we can do a high-tech job of studying it. Let's turn affordable housing into rocket science! Where's that Wernher Von Braun quote when you need it?
Maybe someday, there will only be one staff person at HUD—the Secretary—who will read his or her morning report, and then fill out a Survey Monkey form guided by a cheat sheet of 12 key performance indicators. Oh yeah, and then there will be a 10,000 person IT department, charged with shaking down every affordable housing developer in the U.S. for their daily delivery of data.
Seriously folks—we'll just get hit with more and more requests for data about our programs—and as long as we say yes to it, they'll keep asking for more and more of it. Just like how Jake the Iceman kept asking for ever increasing amounts of protection money until my Grandpa Rosenberg finally threw him out of his bar.
Let's do it like Congress, where if you want to spend more money, you need to identify what costs to cut in order to cover it. So if you want me to track one new piece of data, tell me which piece I don't need to track anymore. You think I'm joking, but I'm deadly serious. I'll track 20 pieces of data for you—but that's it—I've got affordable housing to develop after all.
Maybe—it's time—to start pushing back against the tyranny of measurement.
Photo by puntxote, CC BY-NC-SA
Excellent. Data and a whole slew of measuring and rating systems, and numerous studies that end up on the shelves, many are a waste of time that can be better use to research, design and build better housing.
Thank you Mr. Rosenberg. I thought I was the only skeptic about data that is often both meaningless or incomprehensible, in addition to being difficult to provide.