Jed Emerson is probably emailing me a paper he wrote 10 years ago outlining this aspect of exchanges as I write this!

This is surprising, since in the interest of full disclosure, I should say that I am co-founder of socialmarkets.org, where donors “invest” in nonprofit projects based on their SROI (Social Return On Investment.) This sounds like pretty hard science, but there is actually quite a lot of room for art to soften the edges.

The stock market analogy already seen in this thread is spot on. Apple’s stock price is *informed* rather than *defined* by the financial science that slices and dices its cash flows. The beauty of a market is the marvelous job it does boiling down a large, complex set of valuation inputs into a single output called price. This number is useful on both an absolute scale and relative to other offerings in the market.

In a testament to the wisdom (or lunacy) of crowds, Apple’s stock price reflects the collective opinion of financial analysts, status-conscious teens and everyone in between. The potential to harness the same power to “price” The Red Cross or your local community foundation seems both possible and useful to me.

There are plenty of donors looking for a “best-bang-for-the-buck” (i.e. most SROI) approach to nonprofit investment, and right now there is not much useful data out there for them. The success of sites like Charity Navigator are a testament to the need for metrics, but they only tell potential donors about what nonprofits spend, rather than what they accomplish. Surely we can do better than that.

Those with a less scientific approach may not find metrics like SROI as compelling, but still potentially useful. Consider Albert Ruesga’s story of the high-risk, low-return homelessness project that he presents as an argument against metrics. This is where the difference between the sectors becomes significant.

For starters, unlike the for-profit model, there are often donors willing to invest in hard-luck nonprofit cases - as they ultimately did in Mr. Ruesga’s example. More importantly, since nonprofit metrics is still a new field, we can - and should - redefine the notion of *return* to more accurately capture the total social value being added. That would be the most constructive cross-product of art and science in this space: a more artistic approach to the science of metrics.

The cost per client for this program was on the high side, and only a small fraction of the clients (20%? 30%?) were able to make the transition to steady employment or permanent housing.

By the standards of traditional metrics, this program should not have attracted many donors. It nonetheless did. Donors could see with their own eyes the quality of the care delivered to people who otherwise might simply have fallen off the earth. That these women received some care, now — whatever the impacts might ultimately be — was important to donors.

What kinds of values are we measuring here?

Aspects of quality are very hard (though not always impossible) to measure. It’s hard to attach a number to the fulfillment of a social responsibility, to extending a hand to someone who might be least able to benefit from our help. Social networking theory enables us to calculate measures like closeness and flow in a group of advocates, say, but will it tell us when we’ve got all the right people lined up for all the right tasks for a given campaign?

I appreciate it that you advocate a middle path on the metrics issue. That’s the wisest course, in my view.

My point with financial markets is not that they value things perfectly, but that they allow capital to flow to the best companies and deny capital to weak companies. The Bear Sterns event is complicated, but it is also an example of how quickly financial markets can absolutely turn off access to capital to companies that fail to satisfy investors. Imagine if it was found that the Red Cross was operating in a way that was intolerable to investors and that by the end of the week donations had fallen to zero.

As I said, Bear Sterns is a very complicated event. In no way am I pointing to it as favorable outcome in financial markets. But it is an interesting example of the speed with which financial markets can turn on and off the flow of capital.

Disclosure: Nothing in this post should be construed as investment advice.

But I do think Albert is on to something when he says the bigger question that donors have to answer is “is this worth $25,000 to you?” Sometimes factors such as the cost to society for not investing in programs that reduce truancy or raise test scores — to stay with Albert’s example — provide useful guidance on whether that $25,000 investment is warranted. Also, comparative data that shows the difference between one program’s results and another is also helpful in choosing which competing program merits investment, especially when the program that does a better job than the other costs more. The better results might justify the higher cost of the alternative model.