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The Best Innovation Management Software Translates Between Teams

We’re all familiar with the way knowledge is siloed by organizational structures and the momentum of daily work. Cross-pollination is key to innovation, but it goes against the current. So it’s hard, and the serendipity of chance conversations at the water cooler or a conference happy-hour often determines if it happens.

Even if an organization intentionally shares across domains, knowledge gets trapped behind disciplinary barriers. A surgeon doesn’t speak the same scientific language as a chemist. But thoughtful sharing between them led to a major innovation in medical science.

Cross-Disciplinary Translation is Required

So, to actively facilitate innovation, an organization can intentionally translate ideas between disciplines. A global NGO, for example, is attempting to eliminate dengue fever. There’s a team of entomologists working on how to sterilize mosquitoes, the carriers of the disease. Another team of virologists is trying to kill the disease itself. The two approaches share the same delivery device, a spray. The two teams ought to talk! But that’s easier said than done.

The Best Innovation Management Software Helps Translate Between Teams

Innovation management software should help translate between teams. Here’s how.

Concept Extraction

Natural language processing algorithms can extract concepts from people’s work that are deeper than the titles of their publications or the summaries they give in conversation. (We call this kerneling. You can try it with just pen and paper.) Whole teams, bodies of research, and techniques can become useful resources with a deeper, granular view of what they are about.

innovation management software concept extraction overlap

This is a visualization of two teams within a global research network, one of medical researchers and another of data scientists, that are connected by their mutual focus on birthweight. They would not otherwise have a reason to talk, based on a superficial understanding of their expertise and focus.

Finding Overlaps in Work Streams

Extracted concepts can be analyzed for similarity and difference. Instead of a milieu of conference attendees or office-workers, people with something to offer each other can be organized by the concepts that bring them together in useful ways. Those resources can be visualized for innovation managers and researchers to interrogate and find non-obvious collaborators with complementary differences.

cross-disciplinary collaboration, expertise overlap

Intentional Cross-pollination Activities Supported by Software

Conferences and meetings bring us together to ideate, and we meet new collaborators by chance. Software can make it more intentional and productive.

Through concept extraction, kerneling, and visualizing overlap, software can connect people with useful differences that can offer useful perspective on our research. It can collect and measure the results of those interactions to help drive further cross-pollination, collaboration, and innovation. (Here’s a pen-and-paper exercise that demonstrates a little about how.)

If cross-pollination supports innovation and cross-pollination requires translation between disciplines, the best innovation management software should do that translation.

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