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Scoop.it!
Photo credit: Flickr user: maximillion. The social sector is undergoing an important transformation when it comes to research and evaluation. ... 
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Scoop.it!
This Learning Brief draws from literature and research, as well as more than a dozen interviews with foundation leaders, evaluation practitioners, and social sector thought leaders, with the intention of starting the conversation in the field...
Beth Kanter's insight:
Cover three big trends in social change evaluation - data, connectivity, and developmental evaluation. http://www.bethkanter.org/?p=8370
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It is easier than ever to measure and monitor people and machines, but the technology of Big Data is not without its shortcomings.
Beth Kanter's insight:
The bubble that concerns Ms. Perlich is not so much a surge of investment, with new companies forming and then failing in large numbers. That’s capitalism, she says. She is worried about a rush of people calling themselves “data scientists,” doing poor work and giving the field a bad name. Indeed, Big Data does seem to be facing a work-force bottleneck. “We can’t grow the skills fast enough,” says Ms. Perlich, who formerly worked for I.B.M. Watson Labs and is an adjunct professor at the Stern School of Business at New York University. A report last year by the McKinsey Global Institute, the research arm of the consulting firm, projected that the United States needed 140,000 to 190,000 more workers with “deep analytical” expertise and 1.5 million more data-literate managers, whether retrained or hired. Thomas H. Davenport, a visiting professor at the Harvard Business School, is writing a book called “Keeping Up With the Quants” to help managers cope with the Big Data challenge. A major part of managing Big Data projects, he says, is asking the right questions: How do you define the problem? What data do you need? Where does it come from? What are the assumptions behind the model that the data is fed into? How is the model different from reality?
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Curated by Beth Kanter This is the second reference I've stumbled upon that talks about social media tracking/monitoring and metrics as "social data." This is great reframing in the context of Networked Nonprofits - and measuring their activity. Here's the bit that caught my eye: Whether it be for learning when is the best time to tweet for your audience or keywords that bring traffic to your website, data can be used in some form or another to influence communication strategy (including future social efforts), improve customer service (including resolving complaints), inform product development and understand consumer interests, habits and behavior. In order for this to happen with nonprofits: (1) They already need to have a "data-informed" culture (2) They need foundational skills in collecting, analyzing, and applying social data. This could be: a) Brand Monitoring b) Influencer Research
Most importantly, there needs to be someone on staff who is responsible for the task beyond a quick hit of looking a monthly spreadsheet. Should also be an organizational process, given priority and importance. How does your nonprofit think about "social data" in the context of collecting data, sense-making, and applying it to decisions.
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Matti Keltanen explains why the big data hype may not help your business and gives four reasons for a lean approach
Beth Kanter's insight:
Big data can do most of the things your laptop does, the difference is simply industrial scale. By contrast, we can use the term 'lean data' to describe an Occam's razor approach to data capture and analysis: the lightest, simplest way to achieve your data analysis goals is the best one. Here are four reasons to prefer lean – rather than big – data. Starting with "big" puts the cart before the horse Dminishing returns still apply Hardest part is still done by humans
Media Impact Funders's curator insight,
April 18, 2013 9:54 AM
It's like a buffet vs a tasting menu - one gets you full but not any better off, the other is memorable and illuminating.
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![Big Data Reaches Cosmic Proportions [Infographic] | Measuring the Networked Nonprofit | Scoop.it](https://img.scoop.it/_mmUwdWr2rJFwLCgaRlm3Tl72eJkfbmt4t8yenImKBVvK0kTmF0xjctABnaLJIm9)
Since the advent of big data, it's been a struggle for some to get a real sense of just how big big data really is. You hear strange terms like "peta," exa" and "yotta"… but what does all that really mean? When managing massive amounts of data, the scales were talking about can quickly reach astronomical proportions. Recent efforts to quantify big data have produced interesting results. A recent infographic from clearCi is one such effort, outlining the scale of data produced on the Internet each day: 2.5 quintillion bytes of data... Read further to gain a better understanding of the scale of big data and the potential for future growth... Via Lauren Moss
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It's not that philanthropy doesn’t have anything to bring to the Big Data party. Think about it. Foundations possess resources, something most people do not. And they possess something even fewer people have, flexible resources. As a consequence they are surrounded by those hoping for their support, an endless stream of the brightest and most committed talent on the planet, people with amazingly creative ideas about how to solve the world's pressing social, economic, and environmental problems. But what's visible to the outside world -- the rare project that is actually approved and whose one-line description eventually makes it on to a foundation tax return and (maybe) a foundation Web site -- is merely the tip of the iceberg. (And a surprising number of foundations don't have Web sites at all.) Moreover, most of the (increasingly digitized) concept notes, project proposals, progress reports, evaluations, research, and strategy deliberations produced by foundations are unavailable for mining within individual foundations, across the field, or by anyone else interested in understanding philanthropy's immense contribution to making a better world. When it comes to data, foundations have the defects of their virtues. They are endowed, independent institutions with the freedom to innovate, experiment, and stick with challenges for the long run. But their independence too often creates isolation: whatever data they do collect remains locked within thousands of knowledge silos. America's foundations are changing, to be sure, but while many are still focused on catching up with the paradigm shift from giving money away to social investment, the next wave of change is already crashing over them. Either the philanthropic sector masters the technology of managing information and develops the habits of generating and sharing knowledge, or it risks being left behind. Yes, it will continue to do good in the world, but do we really want to settle for being, as Bart Simpson put it, an "underachiever and proud of it?" That said, getting philanthropy to embrace the era of Big Data need not be a Herculean challenge. Technology is on our side, and by not doing some things we can free up time and resources to start doing others. Here is a partial list of what that might look like.
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