By Gary Wexler, Founder, Seize the Conversation Transformational Seminars, and Adjunct Lecturer in Nonprofit Marketing, Annenberg School of Communication and Journalism
“Where is the data that proves your nonprofit is creating either transformation or pervasive system change?” “Show us the data that explains how many thousands upon thousands of lives have been affected by your work.” These are questions posed and statements made by almost everyone in the philanthropy field when examining the success of nonprofit output. It is all about data.
It began in Silicon Valley
About seven years ago, data-driven concepts started to become woven into all things nonprofit. The trend coincided with Silicon Valley jumping into the cause-oriented world and applying their internal assessment methodologies to their nonprofit involvements.
Last year, when I attended a Dell Innovation Seminar gathering including professors from around the globe who teach nonprofit subjects, one of Google’s philanthropy executives told the group: “We will be looking at data for all our giving decisions. The anecdotal stories told by nonprofits will not influence our decisions.” The Google attitude on this issue has seeped into big foundation approaches as well. Just this week, Twitter was buzzing when the Knight Foundation posted an article, “Big Interest in Big Data.” In it, the author, Jonathan Sotsky, stated: “Nonprofits have shifted from asking if they should measure their work to how to most effectively measure impact.”
For companies like Google, which have the ability to gather billions of data bytes and decipher a trend, data analysis makes total sense for their business.
But not all business practices can be applied effectively to the nonprofit sector. In the case of data, there must be big enough sample cells to map a meaningful trend or result. However, the vast majority of nonprofits are not big enough to deliver such samples. And even if the nonprofit is large enough, budgets must be allocated to capture and track the data, and analyze it. The data then has to be strategically applied to a very complex enterprise, rooted in the soul of a community—and not rooted in sales.
When data does and doesn’t work for donor measurement
This complexity extends to donor trends as well. If data analysis is being used for a massive small donation fundraising campaign on the Internet or through direct mail, it is clear what to measure.
But if it is being used to assess trends among individual major and mega donors, it is not the same as measuring sales. Giving money away, as opposed to spending it, is a very different act. People are motivated to give from a deep, internal human place. Raising money is rarely met with an immediate measurable response. Sometimes, donors are cultivated for years before they lay down the dollar. How do you measure all these complexities with efficacy?
Can data accurately reflect the nonprofit role in transformation and system change?
If data is being applied to transformation and system change rooted in advocacy and participation, here as well there is a complicated set of circumstances to be considered. No nonprofit can claim to be the sole influencer of results. They may not even be the ones who initiated the early steps. Contributing to nonprofit results are the actions of community organizing, policy change, education, marketing, fundraising, and multiple collaborations with government, faith-based groups, community centers, educational institutions and even other nonprofits. How do you measure that with efficacy?
Many organizations, foundations and corporate philanthropies are struggling with measurement accuracy through an emerging discipline known as “social impact measurement standardization.” Can there really be standardization? In a 2011 article in the Stanford Social Innovation Review entitled “Collective Impact,” John Kania and Mark Kramer address social investment measurement in public education. They point out the specific needs and issues of this field and how there must be an expertise in understanding public education issues and their complexities in order to measure impact. Each field and each issue, to be measured appropriately, demands this type of intricate knowledge and understanding. While there can be a professional standard of evaluation approach, there can be no standardized methods.
In the nonprofit world, data can actually kill innovation
Here is the biggest danger of the data demand upon the nonprofit sector: it may be killing some very good ideas that are badly needed in this changing world. Today, funders at all levels want to see data proof before they move on a new idea.
I know this from first-hand experience. I am in an idea profession, working with nonprofits as a seminar facilitator and marketer, training them to think in big ideas for a new era. In the past, when we proposed new ideas to foundations funding the nonprofit sector, we would simply experience the vast majority of the ideas being immediately killed. (It’s not much different than my years in advertising, proposing new ideas to clients.) But today, the first reaction is, “What data do you have to prove this idea works?”
At the beginning stages of idea creation, this is not a smart question. Most new ideas are not coming from people or big places with hefty disposable income to pay for case studies, data collection and analysis. Without new operational ideas, this sector will eventually collapse. If the demand for data is insistent, then the foundation world must be ready to fund the data actions required for new ideas over the period it takes to create the proof they want—which may be years.
What happened to intelligent risk by implementing a new idea? No matter how much data one relies upon, the risk of a new idea will never be removed. Risk is its very nature.
Real dialogue between corporate philanthropy and nonprofits
Conversations between the corporate and nonprofit sector can be tense. The culture and motivations of making money are not the same as the ones that lead people to build a better society. There are many misunderstandings between the sectors. If the relationship between them is going to succeed in the way it must, it’s about more than data assessment. It’s about both sides sitting together as equals, sharing their different professional cultures, listening to one another and then collaborating on the ideas and methods that will work for their mutual outcomes. It’s about human interaction. How do you measure that with efficacy?
About the author:
Gary Wexler is the founder of Seize the Conversation Transformational Seminars. He is the Adjunct Lecturer in both Nonprofit Marketing, as well as Advertising in the Masters program at USC/Annenberg School of Communication. He has helped to market over 1000 nonprofit organizations in the US, Canada, The Caribbean, Europe, China and Israel. During his ad agency career, he created award-winning campaigns for clients ranging from Apple Computer to Coca-Cola. Read more of his work at www.seizetheconversation.com.