Data-Driven Innovation

Blog Post Innovation that Creates New Value

Enterprises have a love/hate relationship with data. The sheer excess makes it hard to manage, but when analyzed correctly, it can provide meaning and customer insights that can lead to breakthrough innovations.

A caveat: Data by itself won’t provide you access to new information because it comes from the past. Innovators must search beyond the data to find what’s missing. They do this by observing closely and asking new questions.

World-renowned researcher Stephen Scherer exemplifies superior observation skills. He uses what he calls “oddball data points” in his autism research. Existing data from previous researchers points to there being five or six common behaviors exhibited by autistic children. This data was reliable, but it didn’t shed any new light on how to cure autism.

When Scherer focused on the data that everyone else was throwing away — aptly named the garbage can approach — he discovered a pattern in genetic variations.

Innovators can use data-driven evidence to find the blind spots and gain insights into how to solve customers’ problems or meet their needs in a new way. They should also factor in past attempts to resolve issues.

How does your enterprise manage all of the ideas that have been tested and trashed but could be applicable now? It takes both a dedicated infrastructure and a skilled data manager (who’s good at listening) to manage this process. With the right tools in place, you’ll be surprised at the results.

What have you observed that could help other enterprises innovate with data?

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