In his book "The Wisdom of Crowds" author James Surowiecki begins with a story of British scientist Francis Galton attending a country fair in which he was able to show that 800 guesses on the weight of a cow, with a handful of those responding experts and a majority of them non-experts trying their luck, were able to collectively guess the weight within a single pound. Galton's discovery, and the driving message behind Surowiecki's book, is that "under the right circumstances, groups are remarkably intelligent, and are often smarter than the smartest people in them."
The key, of course, is within the definition of the phrase "under the right circumstances." Surowiecki goes on to point to Google's ability to tap into the collective choices of individual searches to improve the overall quality of their search results. We are just beginning to see startups and technologies that utilize the power of networking, both through automated (data-driven) and social (user-driven), to deliver new information and services. Our search results in Bing, for example, are now modified with data from our friend's profiles on Facebook, giving us context to our decisions on what to read, to buy, to consume based on social context. Fascinating stuff when you think about how fast these things are evolving.
But then what about when we make, collectively, bad decisions? What of the collective wisdom of a mob? Are their decisions any smarter than the smartest people in them? In a business context, what about the collective choices made by an IT department moving forward on a plan based on faulty data? Surowiecki may be correct in his core idea, but free will and the choices people make are often contrary to what they know to be right (but that's an article for another day)
Some ideas that popped into my head:
We use surveys to collectively check for movement or trends in ideas and activities rather than gather information from one or two customers to influence our decision-making.
We increasingly turn to social platforms to gather a wider perspective on issues, but the sites we frequent and the data we gather must be considered with an understanding of their bias. For example, to get an honest opinion on a conservative idea, you wouldn't go to a purely conservative site or a purely progressive site, and its not so simple as to blend the two and look for an average. There is science behind surveys, and many ways in which is bend statistical analysis and results.
Crowdsourcing is an excellent way to expand your mind (safer than drugs), find new ideas, and get some different perspectives, but at the end of the day, you still need to make decisions. The crowd can't do it for you.
Social tools, surveys, and most statistical analysis should not be viewed as empirical data, but should be treated as a method to inform you of decisions. They should be one piece of your research, not the entirety..
Of course, Surowiecki's ideas are not so black and white. He recognized that crowds were not good at making every kind of decision, and some of the best decisions are actually the result not of consensus, stating "Diversity and independence are important because the best collective decisions are the product of disagreement and contest, not consensus or compromise." Like a muscle, a decision becomes stronger with the more stress you put it under, causing the growth of new, supporting ideas and a stronger position overall. #socialcomputing #crowdsourcing #knowledgemanagement #socialmedia