Sean Gorman of FortiusOne wrote and article for Mashable titled: Open Data: Why the Crowd Can Be Your Best Analytics Tool
The premise is that the crowd will be key in analyzing big datasets. His example is not a “toss the data out there and ask for an interpretation” or “toss a challenge out to public” with which the geospatial community is familiar. The former is what the Steve Fossett crowdsourcing effort, the latter is along the lines of OpenSreetMap. Rather Gorman uses a linear vision of crowdsourcing specifically for deep analysis. In his example, John does something with the data and post his results openly. Then Kate does something with that. Then…Bill, then Lauren.
While I have no reason to believe this sort of thing couldn’t happen now or in the near future, I do not believe this is how things are working right now.
The data may well be public. In his example Gorman uses public tweets.
But, the tools to do this sort of work are fairly complex and may or may be accessible to the key executives. I know FortiusOne and others are working to democratize those tools.
Another challenge: How are John, Kate, Bill and Lauren connected? Do all these people all work for Walmart? In the same department? How do they learn about each other’s data? The social and communications aspects of this type of crowdsourcing are significant.
I agree with Gorman that there is power in the open data and open sharing of analyses of those data. I just want to point out that crowdsourcing these analytical efforts will be far more complex than the data gathering and simple analyses that came before. Further, I’ll suggest that one of the key enablers of this sort of workflow will be those who work in the various communications roles within and between departments and organizations.