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Touting Innovation Isn’t Innovation
Some companies resort to “fake it until you make it” through innovation by association. Innovation becomes a marketing budget line item. They sponsor splashy events and hackathons and invite startups to award ceremonies for PR photo ops. Others run company accelerators but struggle to create an innovation pipeline that isn’t crushed by the parent organization’s bureaucracy and political roadblocks.
A few, such as Amazon’s Lab126, manage to innovate successfully. They check all the boxes: autonomy, multi-year budget, unwavering commitment from CXOs and the innovative culture to fail with discipline. But if your company isn’t ready for an organizational design overhaul, how can you think outside of the box to get substantive wins?
The Symbiosis Of Human-Machine Innovation
According to a recent study, companies can systematically achieve better innovation outcomes by utilizing a combination of crowdsourcing and artificial intelligenc (AI) computation to create serendipity. Great ideas don’t have to occur once in a blue moon; they can happen consistently. The researchers assert that great ideas are inspired from other domains, which is referred to as analogical innovation.
Counterintuitive to our logic, the research shows that we can improve innovation by analyzing a small part of the problem rather than the whole.
To address our natural tendency to ideate primarily within our domain of expertise versus looking beyond to find analogs in distant domains, the first step is to break the problem down into a distinct set of concepts that can help organize the information. Using the example of a kindergarten chair, the researchers segregated complex desired benefits into multiple characteristics such as safety versus flexibility, adjusted the level of granularity such as safety versus preventing it from tipping over, and then integrated comparable analogs to address each of the desired benefits in the solution. For instance, when we think about designing a new chair, we wouldn’t naturally think of obtaining inspiration from an egg-shaped Weeble doll that is designed to stay upright even if tipped. Yet, when we look for inspiration on the characteristic of preventing something from tipping over, it makes more sense.
The process involves a different set of people analyzing the characteristics to avoid fixating on the source problem, in this case, designing a kindergarten chair. Another set of people apply the mechanisms identified in distant domain analogies to the original problem. The methodology separates people who develop the characteristics from people who find inspiration and solve the problem.
The research found that human crowdsourcing can take very complex, multi-constraint design problems and turn them into structured objectives with better-defined constraints such as being easy to move and stack, not tipping over and protecting fingers and toes from injury.
Crowdsourcing increases the human capacity to find analogies across distant domains, and by distributing the steps to different people, alternate paths can be explored in parallel. This approach also allows non-subject-matter experts to participate in the innovation process.
AI then addresses the scalability issue by learning from crowdsourced processes to scale up the search and analogy mapping across the millions of patents, research papers, videos, products, web pages and information on the internet and internal data stores. AI’s ability to systematically search across large and diverse data sets increases the probability of finding higher potential analogs.
Humans and machines together can solve highly complex product development and innovation efforts by supporting multiple constraints and levels of abstraction.
Ease Into It
Many consultants would have you believe it’s all or nothing when embracing new technologies. Management consultancies and creative agencies will come knocking on your door in a few months with a whiz-bang proprietary innovation engine with an accompanying framework to go with it. You simply put in your desired product or service attributes and, voilà, out come game-changing ideas to transform your product portfolio.
Or, more realistically, many readers will think, “Interesting!” and then move on to the next news feed.
But for those that want to make a difference in their work and their companies, here is a practical how-to road map that you can ease into without the huge price tag or political pushback.
In a typical product development agile session, you have the business or product owner, scrum master and development and design members. Following the methodology mentioned above, consider breaking up the group into distinct tasks; develop the schemas, find analogs and solve parts of the problem. Try to maintain a multi-disciplined, cross-functional sub-team so one function or domain doesn’t dominate. Each innovation activity should have a very specific set of tasks and deliverables. The process can be parallel, as many innovation paths can be explored. If you follow the methodology, it would yield more creative outcomes.
Over time, add others into the process so that, eventually, innovation becomes a companywide platform employees can participate in optionally via collaborative idea boards. Once you’ve ironed out the process and the stakeholders believe it is an improvement from the status quo, then begin to consider which non-confidential phases can be crowdsourced further internally and possibly externally.
If you have managed to build up a robust crowdsource process that consistently produces better-than-expected results, consider adding AI automation to scale. By then, you would have built up enough wins to garner sponsor support and project funding.
April 25, 2019 at 08:37AM
Forbes – Entrepreneurs