Top 10 Reasons Why Large Companies & Government Fail at Crowdsourcing Data

Why Do Big Companies Fear Using Crowdsourced Data?

We have been crowdsourcing map data for over 15 years, long before the term "crowdsourcing" was coined by an article in 2006.  The more I speak with large companies about crowdsourced data the more I begin to understand why most large companies and governments fail at collecting and using crowdsourced data for their benefit.
  1. Management fear of data having "errors" and lack of control
  2. Lack of management leadership, passion, and communication for the problem
  3. Poor filtering processes and requirements for contributed data 
  4. Not sharing enough data that is collected by your users 
  5. Lack of confidentiality and not allowing anonymous users to contribute data
  6. No SEO / PR / marketing strategy to find data collectors 
  7. Scrapping data from “like” sources is not crowdsourcing 
  8. Lack of engaged community discussion on the data
  9. Poorly defined niche categories and lack of a problem being solved 
  10. "Too many cooks in the kitchen" managing data.  
Crowdsourcing was trendy a few years ago and now the companies that do it well can be very successful. Waze (now owned by Google) is a perfect example of a company that got it right and still does a great job.  However, crowdsourcing and making money don't necessarily go hand-in-hand.  Waze is successful because they got bought by Google for $1B+ but they never made $1 before they were purchased.

Companies that are successful at crowdsourcing now and in the future are lean and mean.  They are self-funded, bootstrapped by advertising, or subsidized by a large parent company.  Some license data as well to other mapping companies but this is a tough business.  Owning and taking a risk on building data sets is the future of geospatial crowdsourcing.  

Buying versus building is a better solution for big companies in my opinion.