All companies already have access to all the crowdsourcing data that they will ever need.
Long before Wired writers coined the term, in fact long before there were people, there was crowdsourcing. Evolution is the ultimate crowdsourcing optimizer, and, if you can wait long enough, it sometimes produces remarkable solutions. Monarch butterflies from the Pacific Northwest can't survive its cold winters. But somehow, some learned to migrate south, like birds. In northern California right now, tens of thousands of Monarchs are arriving at predictable locations to spend the winter. There is no experienced navigation team directing their flight path. In fact, no one butterfly ever competes a round trip. And yet they stick to a migration route optimized by millions of butterflies in previous generations, and the species survives.
More and more, crowdsourcing is not just about asking one question to many people, or funding one project with lots of small contributions. It's about collecting information from the ideas and experiences of many individuals that can be used to generate innovation on a large scale.
I thought about this while reading a recent article in Harvard Business Review,* offering insights from an analysis of companies who've used an idea management system called Spigit. Spigit provides a platform to give a company's employees a vehicle to contribute and react to ideas and offer feedback on developing ideas — much like you might post an idea on Facebook and others would like it, comment on it, share it with others, or further develop the thought.
From analyzing millions of inputs, the authors say they found four key variables that support innovation. What's more: "They weren't what we expected."
But as I kept reading, the variables did not surprise me. They are all about increasing data inputs. First, you want to encourage as many people as possible to come up with new ideas. Second, you want to increase the velocity of new ideas you coax from that large number of people. Third, you want to get a large number of people evaluating those ideas and how to make them work, not a small number of judges who may be bottlenecks. And finally, you want that large number of people to have inherent diversity — not just engineers or design teams, but people from all over an organization, from sales to manufacturing to accounting, thinking about and contributing to what the authors called an "idea pipeline."
The Inxeption platform invites customers into the design process for the products they want to buy, which generates lots of data. Even ten years ago, it was not easy, not even possible, for customers to communicate their desires and issues to manufacturers like this, and there were few manufacturers who could listen and respond to that input — much less digitally capture that interaction. Before Inxeption, middlemen and brokers translated key information about customers to manufacturers, often withholding elements that protected their role in the process.
Inxeption cuts out the bureaucracy between the people creating things and the people using things. We're connecting customers who want to tell companies exactly what they want and they're willing to offer the information to help make that happen. In that sense, our model feels like a return to the ancient relationship between craftsmen and their customers, with lots of two-way feedback. But our software platform also captures information about what your customers order, how many iterations certain steps take, what customers tweak or change when they reorder, what new materials they ask about, how your communication to them impacts their behavior. This data informs the next interaction with that customer, but it contributes to a much bigger set of data about what all your customers are wanting and telling you. Now, you have crowd-sourced insights... you can better see where the common challenges and desires lie. You can see which solutions consistently rise above other options.
Inxeption is expanding the opportunity to innovate by making all of a company's interactions with its customers more detailed, transparent, and insightful. As the HBR authors note, the more people offering more data more often from more diverse sources, and the more people evaluating that data, the more fertile the conditions for innovation. It was millions of butterflies moving together that optimized those migration routes, not a team of designers. The data ecosystem you nurture will help you better serve the customer in front of you — and suggest new products for them and for new customers you'll come up with because you have more insights to the factors that make your products work for many people.