soft metrics

I believe strongly that design and thoughtful implementation add value to every project, but social impact work takes place in such a complex and variable environment that tracking outcomes based on specific projects is rare and imperfect. As I mentioned in my last post, we may not even know of the positive or negative ripple effects our work is having. Despite this, I also believe it is the responsibility of social impact designers to make an effort to document metrics associated with their work.

If we want the field of public interest design to grow, and funding to be dedicated to the projects and the jobs we believe make the world a better place, there is no alternative to demonstrating a compelling value proposition.

Rebekah Levine Coley, a professor at Boston College’s Lynch School of Education, and her colleagues from Tufts University make just such a proposition through a six-year long study that tracked the development of 2,400 low-income children within poor families. The research concluded that “the quality of a child’s home predicted academic success and susceptibility to emotional and behavioral issues” more strongly and consistently than any other factor.  As Emily Badger writes in her report on the study, the breadth and depth of the research is important because it indicates causation over correlation. Read an excerpt below or the entire article here.

In retrospect, that study amassed precisely the kind of data you’d need to understand how housing itself – not the social environment of a “family home” – might influence children. The study recorded whether a home was rented or owned, or rented through public housing or subsidies, how affordable it was relative to a family’s income, how often families moved from house to house, and the quality of the property. Researchers looked for working refrigerators, holes in the wall, rodents, functioning heat and hot water, adequate light and fresh air – many of them signs of poor-quality housing outside of a family’s control. All of the families were low-income, but some had considerably more run-down housing than others.12837889-old-and-weathered-grey-barn-wall-with-empty-hole-from-broken-and-missing-barnwood-board-showing-aged

Controlling for other factors like a parent’s employment status and income, Coley and her co-authors concluded that the poor quality of housing more strongly and consistently predicted a child’s well-being than all of those other housing characteristics (including whether the home was considered “affordable” to the parents or not). Children in more derelict housing had lower average reading and math skills. They had more emotional and behavioral problems.

The information presented in this study is important in gaining traction for the broad assertion that where a person lives shapes who they are. As stated above, the breadth of this study is important, but public interest designers, rather than be daunted by the idea of studying 2,400 of anything, should see their own projects as an opportunities to reinforce the study on a case by case basis.

I am new to metrics, and am beginning to delve deeper in two ways. First, by frequently asking myself, “What are the intended outcomes of my work in Mississippi?” I have tasked myself with assigning three specific outcomes to track to the Baptist Town Cottage project by the end of November. I will then measure these outcomes before, during and after construction.  Of those three, I would like one of them to be a “soft metric” – something that is not numerical, hard to measure, and tied to well-being similar to Coley’s study.

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