PHILANTHROPY 2173

Measuring success

Several thoughts in the last few days have come together to prompt this post. I was thrilled to see that Disrupting Philanthropy was recommended as summer reading, along with Monitor's report What's Next for Philanthropy. What a nice shout out from Phil Buchanan and great company to be in - "What's Next" is a wonderfully well-written set of recommendations for foundations.

Phil's blog post was flattering and it made me think about how we decide what matters. It came on the heels of my being asked to tell one of the nation's largest foundations about the impact of my work - some of which was once done under contract to that foundation. In other words, I've been called to measure my impact.

I've been asked many times over the years to advise efforts on measuring social impact and I've served on countless advisory boards to all kinds of efforts from commercial software firms to nonprofit alliances to government selection committees to who knows what all. Most recently I've been brainstorming with an odd bunch of tech entrepreneurs, web developers, and social businesses on precisely these kinds of questions of meaningful influence and impact.

Since I have, on many an occasion, opined about the importance of data I often get (mis)labeled as a "data wonk" or "an outcomes geek," or something along those lines. I always find this a little funny, because in the very same paragraphs in which I've written that "data are the new platform for change," I've also pointed out that philanthropy is inherently irrational and data are only likely to be used within certain limits. I am a big believer in data but I also know its limits. I believe in asking the question about influence and impact more than I believe we can find one easy, always-useful answer.

Finally, my company, Blueprint Research & Design, is up to our eyeballs on projects where "social analytics* meet community engagement." So even as we're being asked to account for our "impact" we're helping our clients help their grantees do this same thing. This keeps us up-to-date on a wide range of social media impact work - ranging from Jessica Clark's work on public media to the new "21st century statecraft" discussions that have been personified in Alec Ross and Jared Cohen.

Here's my prediction for the future of understanding community change - we need to integrate what can be learned from social analytics into our measurement approaches to community engagement.

Finding the ways in which "data trails on the web" - click throughs, "likes," tweets, forwards, favorite lists, recommendations, diggs, etc - relate to action on the ground are key new measures of activity. Cracking the code between actions on the web and actions in the real world - what predicts what, what leads to what, what foreshadows or follows certain kinds of activities - by whom, how and when - is a key set of skills and methods for project designers, managers, funders, evaluators, policy makers, and community activists.

Why? Because more and more of our social change efforts are being designed and delivered on the web. Those that aren't fully digital (web or mobile) almost invariably have some kind of web/mobile component - whether it be for outreach, awareness, monitoring, or partnership building. To paraphrase Shel Israel, change efforts are at a "flex point" when it comes to digital media.

Just as click through rates changed advertising forever - and with it the news business, recording industry, publishing, real estate - the deep connections between generation and use of data on the web and actions taken in community are going to change how we make change happen. Being able to apply data on page views or unique visitors in a meaningful way to how neighbors organize or communities protest or vaccines get delivered or votes get cast will be as important going forward as old standbys of community organizing (serve pizza at the meeting) have been in the past.

There are whole methods and sciences of "social analytics"* being developed that look at how we travel through our web and mobile and social network worlds - but most of what is known is known from a marketing and sales standpoint. This means that major advertising companies (like Google) and corporate marketing departments (like those at Amazon or Starbucks) know how to answer these questions:

How many times did I abandon my shopping cart on the web site?
How many times was I shown a certain recommendation before I bought the book?
Did I use the coupon that was texted to my mobile phone to get a free cup of coffee?

We need to take this kind of intelligence and apply it to other questions, such as:

If I join a disease-oriented social network do I manage my medications better and am I healthier because of it?
If I read and comment on a story on my neighborhood on a local blog am I more or less likely to show up at the supervisors' hearing on a subject than if I read about it in the print paper?
What about if I submit a story to that same blog?
If a follow the tweets from a nonprofit am I more or less likely to donate or volunteer to that organization?
If I become a "fan" of an organization on a social network site will I do anything else to raise awareness of the group? Will I take any offline action to support its work?

Social analytics don't hold all the answers. They may not hold many of them - anyone with a blog knows that page views and unique visitors are highly variable and easily manipulated stats. At the same time, everyone with a Facebook account knows how easy it is to count their friends, Twitterers count retweets and all of us sigh at the number of emails in our inbox or texts on our phones. We've all gotten good at dousing ourselves in our own web-wash of data.

But we don't yet know how to connect those numbers (and which numbers to use) to our actual goals for our work or to our other methods of measuring our success. Do I tell the foundation that asked about my success measures about the number of blog readers and twitter followers? Do I do a citation search on the articles and books I've written to see who references my work and how often? Do I count the number of organizations around the globe that have hired my firm to do strategy work? Should I take the results of our client satisfaction surveys, multiply the positive responses by the number of blog readers, Scribd downloads, and Blueprint 2010 purchases and then divide by the number of negative responses? What about interviews with organizations we worked with years ago who've subsequently referred other organizations to us? Measuring success of my firm and my work hasn't necessarily gotten any easier or better since we've gotten all these potential data points - but it sure gives us lots of mathematical possibilities.

How many twitter followers you have may not matter as much as who they are and who follows them. We still need constituency voice surveys, focus groups, interviews, and ethnographic analysis to really understand how and where change happens. The web is full of data - every time you do anything on the web it generates more data. Some of it is going to be useful. What an opportunity to learn how digital data can help us all do our work better.

*Social analytics, defined by Jeremiah Owyang of Altimeter Group as "the practice of being able to understand customers & predict them using data from the social web."

Posted from at 37000 feet above sea level - I blame the typos on turbulence.

Policy change over time at home and elsewhere

I think it is pretty interesting that the Chinese have launched the China Foundation Center (CFC). A research center on philanthropy at Beijing Normal University also launched this year.

Think about it - if you were the most populous country in the world, with one of the fastest growing economies (with all the accompanying good and bad that comes with that) and a rapidly shifting philanthropic sector -- what type of supports for this emerging sector would you build out first? Technical Assistance? Advocacy? A data center? Research? Legal and financial agents, shared space providers, trade publications, professional development providers?

Philanthropy in China is, of course, not new. Foundations as an institutional form, including many of the 1800 whose data will be archived at the CFC are relatively new, as the country continues to shift the roles of the government and the private sector the third space also shifts.

U.S. news articles about the centers focus on the need for transparency and trust of these new foundations by the people. Of course, the information, data and research conducted by these two centers will also be available to the government. It gives us outsiders a chance to watch the dynamics between philanthropic, public, and private from a distance and ask the questions about roles, accountability, transparency, data, access, and trust that are sometimes (always?) easier to ask of others than of ourselves.

Closer to home I've been thinking about a different kind of development on the public-private-independent relationship front - that of the proposed United States Council on Nonprofit Organizations and Community Solutions that Representative McCollum of Minnesota introduced in the Nonprofit Sector and Community Solutions Act (H.R. 5533). Most of what I've read about the act - which isn't much yet - has been neutral to favorable. I'm not so sure - I am still thinking about it. If you can point me to other resources or thoughts on the bill I'd appreciate it (please note them in comments so all can read)

More to come.

Gone fishing

Well, no, not really. But I am going on vacation and will be offline for a week. Enjoy yourselves.

What kind of data are you talking about?

I got this email from Dennis Whittle of GlobalGiving in response to this post on "new solutions from data and crowds."

"I had my own aha! moment when reading your post. As you know from some of our discussions, I am resistant to the idea that more data is "the answer." This is because I chased the holy grail of cost-benefit analysis during my World Bank days, and I came to realize that a) there are fatal conceptual flaws to the idea you can rank initiatives by the same metric, and b) such rankings don't motivate behavioral change in practice anyway. From your post below, however, I realize that you mean data in a broader sense - not just numbers but *information*. Now I can AGREE with that! And it is worth more discussion when we get a chance."

I've had a great time talking with data wonks, open government types, NGOs, communities, activists, White House staff, hospital IT directors and all kinds of other folks over the last many many months about data and the role they play as a platform for change.

But how does this work - why do data matter so much? And what kinds of data am I talking about?

Second answer first - any kind of digital data - photos, videos, stories, numbers, financial information - can play the role as platform for change. For example, think about some of the recent photos of oil covered birds from the Gulf of Mexico. They spark giving of time and money to animal and environmental groups (data encourage action). Some photos are the result of volunteer action - such as the pictures taken by GrassrootsMapping kite and camera systems.

As far as philanthropy is concerned, data MIGHT be anything - grants information, evaluation findings, videos of work happening, pictures from partner organizations, citizen provided survey responses about the state of the local community, text messages that map local crime or that tag community resources.

All of these data matter. They might be useful to lots of people for lots of reasons. If you think of data as anything that can be digitized, and realize that this is what we are sharing using communications technologies, you also quickly realize that data are why we use these technologies. I don't have any interest in what kind of email system is better than the other, I care about the news from my friends, family, and colleagues. This is why I use email. It's the data that matters (the news from my friends) not the technology (Eudora v outlook v Mail)

This recognition matters. It explains the big interest in the iPad from grandparents. They don't necessarily care about all the whiz bang features - they like that it is so easy to use that they can read and send emails to their grandkids.

I don't think data hold all the answers - this blog is named 2173 because I think we are on a constant cycle of learning what we didn't know before - which includes learning that what we thought was right is actually wrong. I don't think data are objective - what we collect, how we frame it, how we present it - every one of these is as subjective as the day is long and have, over the years, led to every kind of human suffering from eugenics to racial segregation to genocide.

And now the answer to the first question - how is it that data matter so much?

I think data are inherently subjective. And that is part of why I think sharing data is so important - as coders says "Many eyes make for shallow bugs." In other words, the more people looking at datasets the more apparent the biases of a few become. For centuries, only "experts," the powerful, and the wealthy had access to most data - whether we are talking about government data that has been locked away and hard to get, photos of abuse at prisons, the location and numbers of oil soaked birds, or health information that would be useful to patients and caregivers but was only accessible to researchers.

The whole power dynamic is shifting around data - THIS is why data can be so powerful. Read Joe Flood's incredible book, The Fires, for a recent and local (1960s, New York City) story about what can happen when "experts with data" don't listen to "experts from the streets." In a book reading I attended in Brooklyn about The Fires, Steven Berlin Johnson asked Flood if the story shouldn't be read as a warning about our faith in data. Flood answered (and I paraphrase here),

"No. The problems come when both data and decision making are centralized. I think the lesson of the book and more recent urban data experiments is we should centralize the data - by which I mean clean it up, store it, and make it mixable and readable - and decentralize the decision making."

I was reminded of this in reading about Sergey Brin's data centric approach to finding a cure for Parkinson's. In this month's cover article of WIRED about Brin's quest, Thomas Goetz writes:

“Generally the pace of medical research is glacial compared to what I’m used to in the Internet,” Brin says. “We could be looking lots of places and collecting lots of information. And if we see a pattern, that could lead somewhere.”

In other words, Brin is proposing to bypass centuries of scientific epistemology in favor of a more Googley kind of science. He wants to collect data first, then hypothesize, and then find the patterns that lead to answers."

This kind of thinking simply wasn't possible before the age of massive data. Time was the scientific method relied on a process of hypothesis - stating what you were looking for and then looking for it. Brin's proposed approach is to look first and ask questions later. The possibilities that lots of people might find lots of things - "Looking for a cure for cancer? Don't overlook this finding, which might be a cure for Parkinsons" - is exciting.

And now return to philanthropy and communities. Imagine if the stakeholders in a community - be it the Bronx in the 1960s or those with Parkinson's and medical doctors and researchers - could bring their individual kinds of expertise to bear on a dataset? This is what happens with sites like Crimestopper and PatientsLikeMe. It is also what happens when people can act on their right to know, a shift marked by Freedom of Information and the #opendata movement. Read this story in Tuesday's New York Times for examples of how information access can change the behavior of the poweful vis-a-vis the poor.

The technologies to do this exist - the challenges in making this happen are about power, privacy, and organizational culture.

Buzzword 2010.3 Networked

We hear about networks all the time in every aspect of our lives. Network is a long overdue buzzword - but today is precisely the right day to declare it as such because June 21 marks the virtual launch of the must read manual on the topic, The Networked Nonprofit by Beth Kanter and Allison Fine.* I hereby declare Network as Philanthropy Buzzword 2010.3!

Change is all about the network. Your social network - who you know. The organizational network - how you interact with other organizations and how permeable you make the "walls" around you. The technological network - how you connect electronically.

Now, it isn't every buzzword that comes with its own user's manual. In fact, this is the very first one. And The Networked Nonprofit is exactly that - the user's manual for today's activists, professionals, donors, and volunteers. What David Pogue does for tech consumers, Kanter and Fine have done for change agents.

It is the most complete practical guide for making change in our global, digital, always on world. Beth and Allison have worked with, experimented with, and documented just about every iteration and evolution of social media tools. From blogs to wikis to social networks to video to slide decks to online competitions to twitter fundraising to geolocation tools - you name it, they've played with it, used it, tested it, learned from others, and shared their wisdom.

But the book is about more than tools - it is about an operational culture that starts with the values of openness, sharing, and connections and uses those traits to accomplish a purpose. A perfect example - the book's launch party is all about working in a networked way. Starting on June 21 at 4 pm EDT/1 pm PDT the authors are throwing a virtual launch party - on twitter at #netnon and on u-stream - geared toward driving sales of the book and donations to The Sharing Foundation and Hope for Henry.

Kanter and Fine live and act like the very types of organizations they explicate in the book. As leaders and learners they connect, share, give credit, invite, discuss, rehearse, improve and introduce. They try things out in public - the book was written collaboratively across different time zones, drafted and shared in countless speeches, slide decks, workshops and twitter feeds.

And they've done their homework. The Networked Nonprofit has a dozen examples for every idea it offers - from big organizations and small, digital native enterprises and transformed "old line" institutions, freelance activists and professionals of every stripe. You might read the book from cover to cover, as I did. Or skip from chapter to chapter, looking for nuggets as you need them. Either way, bring your marker (actual yellow highlighter or the e-book reader button of your choice) - you'll dog ear, post-it-note, and underline your way through this. And clear space on your bookshelf - real or virtual - this one's a keeper. Technology changes quickly, but the culture shifts and modes of operating that Kanter and Fine describe are here to stay.

*Full disclosure: I know both Beth and Allison and have learned a tremendous amount from both of them.