A successful innovation provides an elegant solution to a real-world customer need, says Olivier Toubia. But while the winning formula seems simple, bridging the gap between innovators and consumers requires skill and patience.
“What makes innovation fail often is the fact that the information about solutions and the information about needs [are] owned by different parties,” says Toubia, a Professor of Marketing at Columbia Business School.
Toubia teaches a course on customer-centric innovation. He is also the faculty director of Columbia’s Eugene Lang Entrepreneurship Center. His research includes measuring customer preferences, commercializing research, and gamifying idea generation.
“The manufacturer [or company] has the solution expertise. They know how to build stuff, they know what is feasible, they know the design parameters. So they have the tools,” Toubia says. “And the consumers have the needs and the problems that they want to solve.”
We sat down with Toubia to discuss the factors that lead to failure, how connecting with customers can lay the foundation for success, and gathering winning ideas from the crowd.
What Leads to Failure
Just having a culture that allows people to take risks and to take time to explore, [that’s] something that is sometimes hard for larger companies that often focus on quarterly results…
And now in terms of more operational changes…there’s usually a few different ways in which innovations can fail. … The innovation funnel, the structure, and the tools that have been developed are ways to try to reduce these failures.
Sometimes the issue can be that there’s not enough novelty in the idea. There is not enough of an opportunity. It is not different enough. It’s not exciting enough. So that’s more of a failure in the very front end of the process, where…the idea that you had in the first place was not promising. So it was doomed to fail from the beginning.
And then there could also be failures more in the next stage, which would be more of the design stage, in which…the package of features is not attractive. Maybe there’s some flaws in the design, the quality, the interface, the product-market fit is not there. Tools have been developed to help companies achieve this product-market fit and designing products that would resonate with the needs of the customers.
And then, of course, there could be failures in the launch phase. There are so many things that could go wrong — from the pricing, the channel, the adoption, the advertising. So there’s a lot of pitfalls along the way. And I think that’s why it’s helpful to have a well-structured process that tries to check and reduce these mines as you work through this minefield.
Most large companies have an innovation process in place. And they customize the processes based on their own markets. I think having a way to evaluate ideas in a fair and systematic manner as they go through the funnel is helpful. … If you’re going to fail, you want to fail early and cheaply. And you want to focus your resources on the project that has the most potential. … It’s very helpful to partner with outside constituencies…whether their consumers need users, consultants, partners, startups, universities. … [Companies get] fresh ideas…by being exposed to the wide range of talent.
The Importance of Staying Close to the Customers
If it were easy for consumers to express their needs to manufacturers, then there would be very few failures because every product would be…a solution to a well-defined, well-articulated need of a consumer. …
If it were easy for consumers to express their needs to manufacturers, then there would be very few failures because every product would be…a solution to a well-defined, well-articulated need of a consumer.
The fundamental problem is kind of a translation problem between, “What is the problem we’re trying to solve? And…what are the tools we have to solve the problem?” … Being customer centric is really appreciating…the fact that consumers have information that [companies] don’t have and trying to understand how to extract the needs that they may not be able to articulate. They may not be able to tell us what they need, but find different ways to try to understand what problems [companies] can solve for them, and then using our expertise as designers and manufacturers to find the best possible solution to these needs.
Tools for Customer-Centric Innovation
Design thinking is a very popular framework. … Ethnographic research observing consumers, trying to map their experience, their journey, understand the pain points. Being able to identify problems they have that they don’t even realize…because they usually think a certain way. But actually, if you could change the way things are done, [they] would be happier but didn’t even know that because they’ve only seen the world in one way. …
Of course, you can also ask consumers directly. So in the entrepreneurship world, customer discovery is a very popular…term, just talking to customers getting out of your office out of your shell, and just talking to many people trying to understand their lives, their problems, and what may be interesting or relevant for them.
[Companies can also view] consumers as co-creators…through open innovation and crowdsourcing. Here…you ask consumers for ideas, for new products. Oftentimes when you do that, the ideas themselves may not be valuable or feasible…because consumers don’t have the solution expertise to design the best possible product. But when you engage with them, and ask them for ideas, these ideas are going to be some expression of their needs. So it’s actually as an indirect way to tap into consumer needs by just asking them to engage and come up with ideas. Maybe the solution that they come up with may not be the right one, but the problem that they’re trying to solve is probably a problem that they have.
Using Lead Customers in Different Industires
Companies like 3M…[follow the] lead users approach. … That’s another tool where you partner with users that may not be your users, but they’re people that have developed some solution expertise that could be relevant for you.
So for example, if there’s an interesting case from 3M that was trying to develop surgical drapes for the operating room for the top US hospitals. [They] actually went to hospitals in developing countries to see how doctors there were able to fight infection with limited resources. And they went to veterinary hospitals to see how vets were able to fight infection in much harsher environments. So trying to look for people that have solved similar problems ahead of you.
I did a project with Pepsi a few years ago. They were trying to innovate for Baby Boomers, and they tried to look for people that have faced similar issues to Baby Boomers, but in a more extreme manner and for a long time. So they went to people with disabilities, because as you get older, you can’t see as well, don’t hear as well, don’t move as well. So they went to people that have disabilities and tried to get insights from them as to how they addressed these disabilities to see if there’s ideas that they could then transfer to helping Baby Boomers in the retail environment.
How to Gather Ideas that Win
[Start by] knowing exactly what you’re looking for. … If you know the problem you’re trying to solve, and you’re looking for solutions, then maybe you don’t want to go to the average consumers… Maybe you want to go to experts, lead users, internal engineers.
If…you’re trying to look for an opportunity, or a need, [or] a new problem that you can solve, then maybe you want to look…at average consumers…with the caveat that the ideas themselves may not be actionable directly, but there will be a source of insights, which will then feed into the innovation process.
And then also, there’s actually quite a bit of research on how you structure the actual task to get the most ideas out of whoever’s going to give you ideas. … We looked at this notion of decomposing the problems. … Let’s say you’re trying to innovate for movie theaters, you could just ask people, “Okay, give me ideas for movie theaters.” You could also ask people to give you ideas for the ticket purchase process, the in-theater experience, or the concessions service. [When] you decompose the problem, we find that this gives you more ideas.
Narrowing Down Winning Ideas
We draw on the theory that says that creativity comes from finding the right balance between novelty and familiarity. You need to find a novel twist on something that’s familiar. If the idea is completely novel, and there’s no familiar base, it’s going to be too weird… [and] too out there. If it’s only using very familiar combinations of topics, it’s going to be not novel enough. So you basically need to find something novel, which at the same time is useful. Usually, usefulness comes from being linked to something that’s more familiar. And so basically, what we do is we’ve developed a tool that, given an ideation topic is going to automatically scan the [submission] for content about this topic, and find one of the key words that are relevant to this topic, and see for each of these words…whether it’s a novel or a familiar combination.
Creativity comes from finding the right balance between novelty and familiarity. You need to find a novel twist on something that’s familiar.
If you’re doing cooking, for example, egg and cheese would be a very familiar combination. Chicken and chocolate may be a more novel combination. So we establish this baseline network of words and their relation to each other. And then when we see a new idea we can extract…the combination of concepts that are featured in the idea. How many of these are novel? How many of us are familiar? And then we can actually weigh that against a benchmark that we’ve developed that kind of tells us what would be the optimal balance between novelty and familiarity, and then we can screen ideas that seem to have just the right amount of novelty in them.
[We found] that actually [machine learning] can help you prescreen, say going from 1000 ideas to 100 ideas. You should still read these 100 ideas carefully, but with this, we can eliminate the ones that are very low potential…
Our recommendation is to have some humans do the final stage. Because you want to really have an expert who understands the domain…the constraints of the design, [and the] problem. … We don’t think you should completely automate the process. But we think that this can really weed out the 90 percent of ideas that have no chance of being relevant, and then focus on the 10 percent that’s more likely to be useful.