The New York Times Magazine dedicated the entire issue yesterday (Sunday, 9 March 2008) to "Giving it Away" -- about the "new business" of philanthropy in the 21st Century. The issue covered Google.org, Public Education, the "Celebrity-Philantrophy Complex," and, most interestingly to us, "Can Good Works Be Measured?"

The article quotes Judith Rodin, head of the Rockefeller Foundation, who asks, "Has [our giving] really made a difference? And how would you know?" Legitimate questions, especially in the face of grants that span over a 10-30 year period. She continues, "And if you really do it well, you don't only want to know what works, you want to know how it works."

The article describes a reasonably complex approach (investment portfolio analysis) that the Rockefeller Foundation is using to ensure the efficiacy of their foundation spending. And for a foundation like Rockefeller, the portfolio approach probably does make sense (since they are trying to efficiently their funds.)

However, for most non-profits, simply using a "cost-benefit" or "investment" model just doesn't make sense. It's like a private sector organization just looking to optimize profits -- something that sacrifices long-term strategic gains in favor of short term profits.

I'd like to argue that the Balanced Scorecard is a perfect way for non-profit organizations to embrace metrics and to understand "what works and why." The strategy map defines, in a simple cause and effect manner, how the organization will accomplish its strategy, the measures show how well it is doing against its strategy, and the set of initiatives and projects show what you the organization is doing.

Right now, the measurement movement for non-profits is in its relative infancy -- in my mind, we're still in the "Taylor Period," but we have the opportunity to leapfrog the 50+ years of evolution that the corporate sector went through and go right to the current practice of balanced and effective measurement.

• Telescope or a Microscope: How do you focus on a problem? (August 18, 2010)
• Data, Data, Everywhere (February 2, 2009)