We need to map whole systems, and not just measure individual nonprofits. And it may surprise us who the real all stars are.
“I am in the process of developing a network of artists, organizations, and corporations where the exchanges will benefit each other. How do I start creating an ecosystem along these lines?”
I like the way this questioner is thinking. Rather than just thinking about what his own nonprofit should do, he is also thinking about what the entire ecosystem should be like. Ecosystem thinking is critical: it factors in the relationships, dependencies, conflicts, and other key dynamics that affect everyone. Taken together, these relationships comprise the ocean in which everyone swims.
And you can save a lot more whales by saving the ocean – versus concentrating on just individual whales.

I also like the reader's question because it also gives me an excuse to go on about a pet topic of mine: namely,
ecosystem mapping.
This is an absolutely critical step in the change process the questioner hopes to initiate.
Before you start trying to create or even change an ecosystem, the first step is always to map the existing ecosystem. And you may discover in the mapping process that the most important creature isn’t the whale.
Let me mash into the aquatic metaphor yet another one drawn from sports.
One of my favorite basketball players is Shane Battier of the Houston Rockets. For the casual fan, this would seem like an odd selection. Measured by the most widely used stats to gauge player performance – points, rebounds, and assists – Battier isn’t found on any leader list.
Even on his own team.
Compared to Battier, nine other Rockets players score more points, four grab more rebounds, and five garner more assists.
This is because the Rockets are fanatical about conceiving of their team as one ecosystem, not as a collection of individual talent. Almost alone in the NBA, the front office captures a whole set of data that map the different roles a player has in contributing to overall team success, and not just to their own individual stats.
It turns out that although Battier doesn’t score many points himself, he routinely guards the opposing team’s best scorer (like Kobe Bryant) and disrupts that player’s scoring efficiency almost more than anyone else can. He doesn’t grab many rebounds but he leads the team in strategically blocking out opponents so his teammates can do so. He doesn’t get assists because he’s regularly setting effective screens so Rockets guards can find the open man. All told, the Rockets believe they can demonstrate how Shane Battier impacts the outcomes of games more than all but a handful of NBA players.
These conclusions aren’t just artful and subjective judgments. The Rockets front office measures and records objectively how well each of their players occupy such team oriented roles. The players are graded, reported on, and financially rewarded accordingly. This statistical emphasis on measuring team contribution probably explains why the Rockets made it to the conference finals, pushing the supposedly much more talented Lakers team to seven games despite losing their two “best” (by standard metrics) players.
Different measurements will favor different types of players, highlighting some realities but also overlooking others. In the philanthropy world, as we evolve towards greater measurement, what we especially must guard against is overlooking the “Shane Battier” type of nonprofits. These are nonprofits that play an indispensable role in the ecosystem, even if their individual stats are pedestrian.
Suppose a funder is evaluating two nonprofits in San Jose (my hometown) that work with the unemployed in the low income population.
Kobe Agency serves 15,000 clients annually at a cost of $9,000 per client and a return of 60% employment achieved.
Shane Agency serves 5,000 clients annually at a cost of $13,000 per client and a return of 30% employment achieved.

Is Kobe Agency the better investment? By conventional metrics, it would seem so.
What if we collected the following ecosystem data:
a. number of referrals from other agencies
b. nonprofit concentration within the area
c. types of funding sources
And suppose we discover that Kobe Agency gets hardly any clients via other agency referrals. But Shane Agency gets referrals from five different other employment agencies, including Kobe Agency. This is because Shane is the only agency in the entire region that has expertise in working with Vietnamese immigrants, and other agencies send such cases their way.
In a related fashion, we find that while Kobe Agency is better known (having a larger geographical reach covering downtown and the east side) there are nevertheless three other lesser known “competitive” agencies in its area. In contrast, Shane Agency is the only employment agency present in the south. In fact, there are very few nonprofits per capita in the Shane's area compared to Kobe’s area.
Finally, Kobe Agency gets 75% of its budget from government contracts, while Shane Agency gets only 20%, meaning it is much more dependent on private giving.
So, where will a philanthropic dollar have greatest impact?
It is of course not clear, even with the new data, that Shane is a better investment. And it certainly doesn't mean the money shouldn’t go to the Kobe Agency.
But the new data does make Shane Agency and those like it a much more plausible candidate than before. Even though it serves less clients with less favorable dollar/client ratios, the agency is nevertheless critical to the whole ecosystem. Take it out of the picture, and suddenly its absence impairs the operations of five other agencies which rely on it as a key referring destination. And the neighborhood also loses a community pillar.
Indeed, when looking at the whole ecosystem, one might even conclude that Kobe Agency is actually more replaceable, given the other agencies present in its geography.
Ultimately, though, it’s not an either-or between all stars or role players, between whales or plankton. On every social need, we’ll need both types for overall success. It really is a team effort. But if it is truly a team effort, we can’t just measure individual performance. We have to map the entire ecosystem.
So this is a call out to creative funders and social entrepreneurs, “Are you ready to get started?”
Telling the (sadly short) history of mapping nonprofit ecosystems will have to await another entry. But here are some initial pointers that are close to my home:
- My firm Consulting Within Reach recently partnered with the largest county government in Northern California and applied for federal stimulus funding to build a comprehensive, web based map of the county's nonprofit ecosystem. Like Kobe going to the hoop against Shane, we were rejected. But if you'd like to read our plan, you can download the ecosystem mapping project proposal here. I'd love your thoughts as to whether it would have been worth Uncle Sam spending .0000005 percent of what it spent on AIG.
- Sara Olsen, who co-authors the Social Edge blog SVT on Impact, has started a similar mapping effort. It's very early stage but definitely bears watching.
- Another good start is the Foundation Center's In/Sight mapping tool. It isn't open source and charges fees that will be prohibitive for many in the sector. Also, it just measures location and funding, not actual relationships with other agencies and service populations. But I'm nitpicking - it's a very impressive first effort.
- The for profit enterprise that I have been most struck by so far is Rhiza Labs. I haven't yet talked to anyone who has used their product but it looks interesting.
Here are some other links to mapping related content by Jill Finlayson and Lucy Bernholz:
Do you have other leads and links to share? Post them below!
More resources
Lucy Bernholz is doing some of the most ambitious and comprehensive info-gathering in this field. Her most recent post:
http://philanthropy.blogspo[…]forms-for-philanthropy.html
A round-up of recent posts from across the nonprofit sector on the kinds of data/information being mapped and the open/transparent culture this movement requires:
http://my.socialactions.com/[…]/social-actions-and-open-data
Christine