Philip McNaughton and Andrew Needham (both of Face), are talking about "From Socially Intelligent Businesses to Socially Intelligent Research"
Consumers are doing things that companies previously paid their employees to do. Value creation is moving outside the walls of the corporation. They have a cool hexagon graphic showing how technology platforms enable value creation.
What clients need: make more, better decisions faster, instead of trying to make perfect decisions. (Sounds like Agile to me)
So what is socially intelligent research? It seems to involve "sexy metadata" and "continuous, integrated, holistic view of the consumer." I'm a little unclear, actually, but I still like the concept (System 1 thinking at work!) There is a white paper on Slideshare.
Putting data in context -- look at social data not just in terms of what is being said, but who is saying it, and who they are saying it to. Move away from how many tweets, to what are foodies saying? Instead of how many negatives, ask what is the brand equity?
Question about how many people involved? They start with 50 people through screening and do some early work to get down to about 16. This is a very different approach than the 400, or 4,000 member insight communities we hear about.
My take: If we agree with the view that more value is being created outside the firm (and I do), then how to we actually start to think about adding value to our customers by shifting value creation outside our walls? Is this a strategy we can actually use to drive innovation, instead of a just a trend to observe? This has been done in the past.
Observation: The rooms were switched, but the online agenda is actually correct, so those of us who thought we needed to adjust went to the wrong place. Arggh.
Next up, John Barrett of CrowdMed is going to talk about using prediction markets in healthcare. I met John last night on the deck, and thought this would be fascinating. Stay tuned ...
The company founder wanted to help his sister with her depression problems. (So much innovation comes from this kind of motivation!) He considered The Wisdom of Crowds by James Surowiecki, and the prediction markets that Infosurv had been doing in marketing applications, and in political prediction.
A new person is introduced -- Stacey, who had irregular periods and mild depression. Plus a bunch of other problems. Over 970 days a number of experts could not figure out what was going on. So, a crowd solution was sought. The group of people was given the same information and facts that the family and doctors all had. They were invited to use any resource at their disposal. Most of these people made their contribution within 12 to 15 minutes. They could earn additional rewards for being correct, or being closer to the result.
A number of ailments were offered up. Five were weighted. A second market was run, with the same background and information, and given the chance to invest in only these five opportunities.
The results of the crowdsourcing came up with FXPOI (an ovarian insufficiency), which Stacey took to her doc, who confirmed the crowd diagnosis, and was able to treat her.
This is a start-up situation for founder Jared Heyman, who is still running proof of concept cases, and hopes to take this to a different kind of market. They are not clear where the commercialization comes in this application.
What is important to make crowdsourcing work? A controlled panel produces much better quality information than a river sample.