Focal Data aims to streamline data collection for innovation professionals by automating some tasks, positioning their service as an “expert researcher in a box.” FEI themed its tracks this year to feature an AI day, a human intelligence day, all kind of encompassing collective intelligence. Can you tell us about your company and the AI solutions it offers?
“It’s nice to be at FEI with a backdrop of some different focus areas, especially in the discipline of how innovation professionals are going to market, how they’re leveraging data and insights, because that’s what we really want to fit into at Focal Data,” says Pasqualina. “We’ve had our ‘coworker’ as a platform to be able to help innovators look at early-stage setup, delivery of interviews and collection of data and insights. It’s really about facilitating that process, and we’ve taken a lot of the repetitive tasks of research and automated those through AI and machine learning.”
Coworker is the term you use to describe the AI platform that Focal Data employs.
He adds, “We’re really anti-tool. We feel like the industry doesn’t need another tool. After all, you’ve got 20 already in your arsenal, and you probably don’t use half of them. We really think about the platform as sort of an expert researcher in a box, someone who’s a member of the team and is helping you move faster through the early-stage learning and exploration process, to talk to consumers and get that real learning back into those employees who can translate and turn insights from it.”
Pairing AI With the Innovation Mindset
There are indeed so many tech tools out there, and AI obviously helps with automation and efficiencies of that sort. But there’s still that human element for the innovator as well. At FEI, we held our Rogue Mindset roundtables and keynote presentation. How does that mindset fit into the AI framework and innovation community?
“The innovation mindset really fits in pretty well with AI,” relates Pasqualina. “At Focal Data, we have really thought about how to enable as much support for the user as you want. You can kind of create your own adventure in terms of you could let the setup agent work through all of your research goals and sub-goals for you. Or you can play a more active role and say, hey, I really want to learn this. And then take that first layer of learning and then iterate on it. You can be as involved in the early stages leveraging our platform as you want to be, and it doesn’t take the human element out of it.”
Focusing on the Innovation Journey
Executives in the community talk about the innovation journey, a process from the beginning stages and leading up to the final phase of the process. What does collective intelligence mean to you and your organization? How can this help in terms of understanding consumer behavior and problem-solving?
“We think about the double diamond theory and how to approach problems, giving researchers the ability to sort of circle back and relearn or reinterview and improve through iteration and other techniques for getting to that ‘why.’ We know consumers do x, y, or z. Why do they do it? And really understanding that journey. That just doesn’t come from one part of the organization,” says Pasqualina.
He adds, “There was a comment earlier in the rogue mindset presentation about a 120-year-old company trying to do things differently. That’s exciting. There’s some value and some tradition in having all that learning, but there’s also a way to leverage AI and other technologies to really improve.”
To improve and perhaps to take away some of the roadblocks to innovation.
“We’ve pointed our AI at sort of both the productivity side as well as the insight side,” notes Pasqualina. “There are tasks that we can offload from the researcher and give them more time, but there’s also thinking and learning that AI can do just as much at a faster speed. Having that balance across our portfolio at Focal Data is important.”
