Crowdsourcing has a crowd of critics. Crowdsourcing is the notion of distributed problem-solving where problems are broadcast to large groups of solvers in the form of an open call for solutions. The belief is that the “wisdom of the crowd” yields superior results over what individuals can do. The use of the term has spread to just about any activity that involves groups of people tackling an issue.
The critics have a point. Crowdsourcing seems to be an old story retold a new way. The idea of collaborating with others is not new. The idea of reaching out to thousands to gain insights about a problem is not new either. Here are two examples held out as crowdsourcing best practices that make the point. A Catholic church in Germany launched an online open idea competition. On the competition platform, young people are encouraged to submit their ideas about what they would like to change at the Catholic Church.
That is not crowdsourcing. That is market research.
Here is another. CreateMyTattoo connects customers with a community of 700 tattoo artists who compete to design the perfect custom tattoo. Customers see several variations of their tattoo idea and provide feedback to the artists during the contest. The site guarantees at least ten unique custom tattoo designs or your money back!
That is not crowdsourcing. That is competitive bidding.
Here is a better example that starts to move in the right direction. DHL, a courier company, is testing a way to use city residents to deliver packages along the route as they go about their daily travel. The programs is called “bring.BUDDY,” and it hopes to reduce road congestion and DHL’s carbon emissions. Participants use a smartphone app to specify their travel. An alert is sent to them of any package that needs to be delivered along their route. In return, the participants receive points which they can redeem at local stores.
This is novel. But DHL could go further with the concept. What else do people know or do (explicitly or tacitly) that DHL could use to improve operations, reduce cost, or increase revenue? For example, what if DHL had a way to know what delivery routes are optimal based on information fed to it by customers (through cellular technology)? What if the crowd could identify open parking spots, report packages that need picked up, or spot activities that might demand the use of courier delivery?
There is a better way to leverage the crowd. Rather than “source” the crowd for their explicit ideas, we “cache” their tacit, day-to-day routines to detect patterns and insights. In “crowdcaching,” people don’t know that they are contributing their small, incremental movements and decisions to a larger pool. It is like digital ethnography. We collect large samples of tiny decisions to “bootstrap” our insights and decisions.
The Task Unification tool is perfect for this exercise. The tool works by assigning an additional task to an existing resource. Crowds of people become such a resource. We start with a phrase like this: “The crowd of customers will deliver information that reduces our cost to service them.” Then, using Function-Follows-Form, we work backwards to consider how this would happen, why it would happen, and what benefits would accrue to all involved.
Let’s revisit our two previous examples of the Catholic church and tattoo shop. Perhaps we “crowdcache” the movements of young catholics as a way to spread the gospel by carrying the message when it is needed most. Perhaps the church has a way to track their location and proximity to others (via smartphone…with their permission) The system knows when a young member of the parish is with a person who is particularly troubled or in need of the Gospel. It develops new outreach programs from this data.
For the tattoo shop, it would be more interesting to search tattoo designs by what others are doing (social proof). This site could show real-time tattoo designs being inked by 700 tattoo artists. Tattoo shoppers select a design and see information about others who wear the same or similar design. Demographics, affiliations, attitudinal data, etc, would help the prospective tattoo-ee decide on appropriate designs thanks to the wisdom of the tattooed crowd. The crowd delivers useful information without even knowing it. The tatto shop “caches” this information to deliver better service.
By the way, “crowdcaching” is an old story retold in a new way, too. Think Amazon.
Drew Boyd is Assistant Professor of Marketing and Innovation at the University of Cincinnati and Executive Director of the MS-Marketing program. Follow him at www.innovationinpractice.com and at https://twitter.com/drewboyd