Hard numbers can be hard to come by for some social innovators. In a recent Fast Company article, Kim Syman presents the case for how an innovative approach to data can enhance the quality of your work.
Kim Syman, Managing Partner at New Profit, feels it is “fair to say that data is among the most powerful, under-utilized, and incompletely understood forces in social problem solving.” However, in her latest piece in Fast Company she argues that the “complexity and dynamism of social problems and related human decisions are tremendous, so data can’t be used to ‘solve’ these issues.” It requires an innovative approach to using data to enhance current solutions and develop new tactics.
Syman has one particularly innovative example of data usage from the Family Independence Initiative (FII), which she explains in full in the original article. FII “leverage the power of information to support economic and social mobility for families in small collaborative groups” in Boston, Detroit, and New Orleans. What we find particularly fascinating is that rather than simply building data fields that link directly to the programme, they have “created a way to measure and propel people’s initiative and capacity.” Syman explains that “participants input data points on a monthly basis in an FII dashboard that tracks assets, housing, education, and other factors.” The remarkable response to packaging data this way is that it “allows participants to make their own decisions about priorities and opportunities.” Off the back of this data, FII then develop products to enhance beneficiaries’ well being, such as small loans. Syman believes that “none of this would have been possible if the organization hadn’t developed an innovative feedback loop with its constituents.”
To build on her case for innovation, Syman encourages you to learn what Great Schools, Child Mind Institute, Mission Measurement, LinkedIn’s Economic Graph are all up to, and how their models and approaches are shifting the status quo.
Ultimately, Syman believes that solving complex, dynamic problems requires evolutionary approaches, which “rest on rigorous data collection and analysis that is connected to on-the-ground understanding of what is working and why.” Innovation is required for success, and we must not forget that “numbers mean little outside the context of leaders, culture, and communication.”