It is easier than ever to measure and monitor people and machines, but the technology of Big Data is not without its shortcomings.
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Scooped by Beth Kanter onto Social Media and Nonprofits: Measurement |
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Curated by Beth Kanter Influences means a couple of different things. You can measure other people's influence - as part of identifying champions or super fans or you can measure your own influence or organization's as part of a goal to have "thought leadership." This is a vanity metric - and there are several tools you can use to measure it. This Infographic shows some of them. Most important bit is the how to: If you are really interested in taking advantage of your social influence score, it’s not enough checking your level every now and then. You’ll have to act. What follows are the steps to develop a successful action plan according to Brian Solis (new media analyst at The Altimer Group) : Track performances against current benchmarks that capture existing sentiments, behaviours and awareness.
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At the Dublin Summit last week, new industry standards were announced for traditional media analysis (Proposed Interim Standards for Metrics in Traditional Media Analysis) and for social media measurement (read more here). Delete the scoop?
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A good basic primer to analytics Delete the scoop?
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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?