Social Innovation development

This week's readings lead me to further reflections on developing and sustaining social innovations. It seems to me that the field is facing a number of challenges to growth: Firstly - Innovation development How to ensure a steady stream of social innovations? Currently it seems to be the lot of governments to do the heavy lifting of backing nascent developments. Secondly - how to grow innovations Or, perhaps, whether they should grow at all: the strength of some innovations is that they are local solutions to local problems. How does anyone know how to back winners? Thirdly - overcoming bureaucratic inertia The reality is that government activity is essential to grow innovations currently. Yet governments can be highly risk averse organisations If these are the challenges, the big picture context is one of governments looking to limit their exposure to social challenges, of the limit of resources. For example, it is a commonplace of policy discussions that health costs of most Australian states are expected to exceed their ability to pay the bills over the next few decades. These challenges have called forth some innovative administrative responses. For example, Mayor Bloomberg decided to bypass city administration entirely when he created the Centre for Economic Opportunity (which seemed to serve as the model for the Administration's Social Innovation Fund). It seems to me that the policy objective is to create an environment that can attract private capital to solve social problems, such as the highly innovative social impact bonds currently being trialled in the UK and Australia. However, the biggest challenge of all is surely going to be: how does one measure social change accurately enough to permit private capital enough information to measure it's return? Social Impact Bonds guarantee a return of 7 - 13% (approx). Whilst it is easy to identify a 0% return - i.e. no social change at all (for example, the UK example is a reduced recidivism trial. Where there is no reduction, the government will return 0% on the SIB), how would a capitalist know where their return sits. At 7%, or at 13%. Such information is highly likely to influence investment decisions. I presume the answer to such problems lies in skilled data analysis techniques such as linear programming and in empirical methods