Are You Brainstorming the Right Way for Innovation?
Conventional wisdom says
brainstorming works best when people from different departments or groups come
together to think of new ideas or solve problems. But research from Sarah Kaplan,
a senior fellow at Wharton’s Mack Institute for Innovation
Management, shows that diversity is not enough. What is
also necessary is in-depth expertise of the topic at hand. Those two factors together
result in truly innovative ideas and also yield the highest economic value.
Knowledge@Wharton recently
spoke with Kaplan, who is a professor of strategic management at the Rotman
School of Management at the University of Toronto and a former Wharton
professor, to discuss her research.
An edited transcript of the conversation
follows.
Focus of the Research
I have been conducting research … on
innovation, specifically as looked at through the patenting of technological
innovations. I published a paper recently with a former doctoral student at the
Rotman School, Keyvan Vakili — who’s now at the London Business School — called
“The Double-Edged
Sword of Recombination in Breakthrough Innovation.”
I want to tell you a little bit about the
double-edged sword that we found. Basically, in research on innovation, there
has been an idea that breakthrough innovations, those with the highest impact,
are ones that are produced through … what we call “re-combination” or
combination processes of distant and diverse knowledge.
What we found in this study was that this is
only one creative process and there are other creative processes that contribute
to breakthrough innovation. Specifically,
we found that different types of creativity contribute to the novelty in the
knowledge space — how novel the idea is relative to the economic value that is
created Twitter .
In the study, we examined patents in the
sphere of nanotechnology because it’s an emerging and exciting new field with
lots of breakthrough ideas for over about 20 years and found few patents that
were both novel in terms of knowledge and also high impact in terms of economic
value.
Patents that were both novel and had economic
value were the most valuable. And that was only about 1% of the total patents,
so it’s very rare to have a breakthrough in knowledge and a breakthrough in
economic value. But when you have that, you get the highest impact patent.
Key Takeaways
For practitioners, the important thing is to
remember that not all creativity happens through combination processes. We have
this idea out in the world that … bringing distant and diverse knowledge
together is the way to get creative insights, and that’s certainly true.
However, what we discovered is that there’s an equally important process of the
deep dive, of deep knowledge in one domain.
So, if you are only designing your R&D
processes or your new product development processes around that kind of
diversity of ideas and combination, you may be in trouble because you don’t
have the deep knowledge you need.
This relates to the idea of brainstorming.
Everyone thinks we’re going to solve a creative problem by coming together and
brainstorming.
What this would say is brainstorming is not
enough without the deep knowledge development that you would need in a particular
domain to understand what the issues are so that you can break away from
existing ways of thinking.
Surprises
This study was actually quite surprising and
we found something that we did not expect to find at all. Prior studies of
innovation — in particular, studies that look at patenting of scientific
inventions — have only focused on measuring breakthrough innovations according
to measures of economic value. In the patent world, a measure of economic value
is how many times it then gets cited by other patents. What that means is any
time you go to get a patent in the patent office, you are required to list
prior patents that were essential to the development of your ideas. And the
more times your patent gets cited as a prior patent that is essential to the
development of ideas, the more valuable that patent is.
And so, in the field of innovation studies,
we tend to measure breakthrough innovation as those patents that get many, many
citations from subsequent patents saying that it’s really a foundational idea.
That is the way historically that the field has always measured innovation.
We actually adapted a computer science method
called “topic modeling” to look at the text of the patents themselves, to
understand the language in the patent so that we could see when there were
shifts in language that would allow us to understand when new novel ideas are
being developed. So when the language changes based on this methodology, we are
able to say, “That’s a breakthrough idea,” because it’s talking about the
domain in a fundamentally different way.
“Brainstorming
is not enough without the deep knowledge development that you would need in a
particular domain to understand what the issues are so that you can break away
from existing ways of thinking.”
What we did in this study is introduce this
alternative measure of breakthroughs that focused on knowledge breakthroughs as
opposed to just the economic value as measured by the number of times a patent
would be cited. And what’s interesting about that is that prior studies had
always assumed that if you got a high level of citations it was because the
idea was very novel. And so, they just said, “Because the idea’s novel, it gets
more citations and therefore, it’s a breakthrough innovation.”
What we found in our study is, in fact, that
most of the patents that do get highly cited are not necessarily novel — truly
novel from a language standpoint, from a knowledge standpoint — that is,
they’re not breaking new ground in the knowledge space.
And so, we break down the set of assumptions
that people have made before: that novelty automatically leads to high levels
of citations. And by doing that, we’re able to then show that there are
different creative processes that lead to novelty than those that lead to
generating citations. That’s really the surprising part for me was finding out
that the assumptions that the field had been making up until now about the
direct connection between novelty and citations were not as neatly linked as
people had assumed.
Practical Implications
When we think about any organization that is
trying to promote innovation, it’s typically been recommended that you try to
create processes that bring together distant and diverse knowledge. So we hear
lots and lots of research about diverse teams, you know, bringing marketing and
R&D and engineering and all the different groups together to generate
innovation.
And while that is clearly very important,
what we are finding from this research is that you also need different
processes that allow you to do the deep dive into one knowledge space. So if
we’re thinking about an R&D organization, that means really valuing the “R”
part of R&D, the research part that says we’re going to really dive deeply
into an area before we even know specifically what the product might be or the
service might be because we have to understand an area deeply enough in order
to be able to identify the key problems, challenges or anomalies in the field.
Once you have those insights, coming together
in this process of combining different ideas makes a lot of sense. But if you
just go straight for combination and diverse teams, you may be missing out on
the highest impact ideas because you haven’t done what I consider to be the
pre-work, which allows you to have that in-depth insight into innovation.
This corrects a misperception held by
organizations, the public and media about how creativity is always about the
brainstorming among diverse teams and the like. But what we’re finding is that
you also need this deep dive information to get the most novel ideas.
This connects to an idea that — for people
who have read [T.S.] Kuhn’s work on scientific paradigms where he talks about
changes in paradigms — breaks in paradigms really require this deep dive. And
so, what we’ve been able to do in this study is contrast the creative process
around combination with the creative process around a deep dive in knowledge.
Other Research
There are two things that set the research
apart from other analysis. One is the methodology. I mentioned that we used a
computer science technique called “topic modeling.” Topic modeling is a
technique that was developed to improve search algorithms.
For example, we’re going to a search engine
and we want to put a term in to get search results. [Topic modeling] was
developed to help us improve those search results, so that we’re getting the
results that we want. We then took that technique and said, “You know, what
topic modeling is really about is, it takes what they call a bag of words, a
body of text and in the case of our study, the body of text were the texts of
the patents that we were looking at, and it infers from that body of text by
the co-location of all the different words, what are the key underlying topics
in the data?”
This is interesting because most of the time
in the social sciences, when we want to categorize themes or topics, we come up
— as analysts — with the topics and then we look at the texts or we look at the
products or we look at whatever it is and we do the categorizing ourselves.
What’s nice about this computer science technique is it allows the words to
speak for themselves and tells us what the categories are without us having to
impose our own frames of reference on the data. We then identify the topics
that were in the body of texts of the patents that we studied and could
identify which patent was the source patent of the new topic. So as topics
emerged in the field … we can see which patent it is that is the actual source
of that idea.
That’s methodologically an important
contribution. It’s the first paper in the social sciences that has taken topic
modeling and used it in a statistical regression analysis of the kind that we
are doing. And it’s part of a vanguard of scholars who are now beginning to use
these computer science techniques to analyze texts, understand social science
phenomena in new ways.
The other contribution is theoretical, which
is that we’ve gone back to the creativity research and found that there are two
schools of thought in creativity research. One school of thought is what we
call the “tension view,” and that’s the view that in order to get creative
ideas, we have to break from our current way of thinking and therefore, we need
diverse ideas, we need different ways of thinking, we need to combine or in the
language of the field, recombine ideas from all sorts of different domains in
order to break us out of our current mental models.
All of the theories around combination and
diversity have been based on this tension view, which says that new knowledge
is in tension with old knowledge. But there’s another view of creativity — if
you go back to the psychology literature — called the “foundational” view. The
foundational view says, “No, what you have to do is go deep into one domain in
order to see the anomalies, and it’s only when you do that that you can really
break out of the existing way of thinking.”
So, the other contribution of this paper is
to go back to those insights from psychology and creativity and say, “Wait a
minute, we’ve forgotten about the other half of the creative process.” We’ve
spent all of our time focused on combination and diversity and less time
focused on what the deep dive into existing fields can help us produce in terms
of breakthrough ideas.
Follow-up Research
My co-author on this project and I have a
follow-up project that is looking at what specific recommendations we might be
able to make to organizations about how to design their innovation processes;
it’s looking at the organization design for innovation [and] the team
structures so that we can understand which types [work best]. You need a
combination of experience and less experienced researchers, you need research
in different domains. We’re going to look at the team structure and we’re also
going to compare different technological domains because nanotechnology, in
particular, … is more of a chemistry-based type of innovation process.
We’re going to compare that process to a more
engineering[-type] of innovation process like looking at MRI machines that are
used for imaging and comparing that to stem cells, which is more of a
biological innovation process. We’re going to look at different domains where
different creative processes might be at play and then understand what types of
team structures are best at producing the breakthrough novel ideas, the ideas
that can be highly cited and then the magic 1% that are both novel and the most
highly cited out there … which is a way of measuring economic value.
We’ve got a whole project that will get
deeper into those specific organizational recommendations. That is one project
that I’m doing as a follow-on to this research.
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