So, now we have seen what we shouldn't do, we have seen the different features of
it, the different aspects. So, can we say what is innovation? Something we can claim is
that innovation is not about luck. It's not a lottery. It's not: you do
some research, and you... you will find something, and this something will save
the world. You know you could say that... if you ask
people who won the lottery, if you ask them "how did you proceed?", and they will
say "Oh! that was very easy! I bought a ticket and I won!". So, if you want to do
the same, you will apply the same recipe... means... buy a ticket, and you
won't win. So, as I said, yes it could happen that someone by chance will find
the molecule that would cure cancer, do something. So, this is really a discovery
that leads directly to innovation because now you have something that can do
something that nobody could before. But overall, if we forget the luck factor, we
should say that innovation is mostly about the vision and it's about context.
Now, I want to show here a graph that was created by Professor Seelig, and professor
Tina Seelig, she's a Professor at Stanford University, and she came with
what is called... she called the "innovation engine". And the innovation engine is very
very good because it summarizes in one single picture
most of the features, and qualities, and asset
you must combine for successful innovation. So, we have two rings or two
triangles, and the internal triangle you see, it's inside, contains "attitude",
"imagination" and "knowledge". And this is what you must demonstrate. That's the
personal quality we must have: we must know something! OK! it doesn't mean that
if you don't have the knowledge, you can't develop innovation, but this knowledge
must be combined with imagination, being able to think out-of-the-box, to
identify to a given problem... solutions that nobody had thought about before. And
of course, it must come with specific... let's say... attitude. That means you cannot
do innovation as a natural result of research. If you want to do innovation,
you must actually adapt your mindset to an innovation mindset, you must switch
your mind to an innovation attitude. The three external sides of the graph here
are "resources", "culture" and "habitat". And this is about your environment: if you
want to have more chances for success in innovation, it's better if you can
develop and apply your knowledge, attitude, and imagination in the
context where you have resources. Resources could be just you know...
a building where other teams are working and the way that you share
discussions, things... will feed your mind. And you will improve and increase your
knowledge. Culture it's about the social
side of it. I mean.. are you living in a culture where it's well seen to think
out-of-the-box? And the habitat is actually the environment that you have.
So, on this graph, you can also connect the internal triangle to the external
triangle: the knowledge is connected to resources, imagination is connected to
habitat, attitude is connected to the culture. Now if we want to go a little
bit deeper in what we can call an innovation project, we must conclude that
an innovation project it's more than just doing research. It means you must
really switch as I said, your research driven mind into an innovation
innovation driven mind. If we go back to our triangle, what I called a magical
triangle, we can say that innovation is not invention. Innovation, being able to
conduct innovation, will require a combination of skills that go beyond
pure research.
And something very important, and this refers to switching your mindset in the
innovation driven mind: innovation always starts with problem, never with solution!
Research can start with a question that means "okay! What happens if I mix A with
B? What happens if I go in the wood, in the forest, and I start to look around me?
and you can discover a new insect, you can discover new plants... and if you mix A
and B, you could have a reaction. Or if you expose a molecule to light you could
see something about the light emission or things like that...
So this is driven... research is mostly driven by curiosity. But innovation must
be driven by the way that we want to solve problem, that people want to be...
this problem... to be fixed. So as scientist or engineer, we must learn to identify
and target the right problem because you can find... remember that 40% of startups
fail because there's no need for their invention. So, we can work on solving a
problem, but the better, or the quicker we learn that nobody wants
really this problem to be solved, the faster we'll give up on it ,and we'll
move to another problem that maybe more people will be willing to to be solved.
So, innovation is not about doing something in your rooms,
innovation is trying to bring something to the market that people would buy or
will use. So, for scientists, we must... the key is when you have
identified a problem, and what functions should be combined. We
must learn how to assemble the functions because now we.. I can say... that we are
getting rid of the easy solutions, we have to develop smart solutions. And smart
solutions are actually combining different functions. Nobody will buy a
cellphone right now because the cellphone can allow you to call people.
They want a high-resolution camera, they want a stereo sound, they want good
screen, they want to... they want to do a lot of things. They want actually the
object to combine a lot of functions, and when you look at how many
functions are combined with a very very high quality, actually you could say at
the end, that they're not so expensive... even if they are expensive. So, for the
scientists, we must learn how to assemble functions, and also we must learn how to
make, to organize a project, to build a project, because it's complex.
It's a complex process. That means, you must be able to see what will be
the steps. And because you can control it, you must be able to adapt, you must be
able to change. Because you developed something, and actually, people say "no!
Your solution is not good enough, your solution is too expensive, or your
solution is not different enough from the competition."
And also something very important is that scientists and engineers must learn
to talk to non-scientists because very rapidly, what you will have to,
will be to explain, or to... I will come back to the term "explain" after... you will
have to talk to people who are not scientists. They have no knowledge about
technology and actually they don't mind what... how your system works. They are not
interested in this. They want to know something else.
So, because we are scientists, we are engineers, we know how to speak to other
scientists and engineers, we know how to explain to them in detail, etc... And we will
think that if we do the same with other people, that would be good... and usually
it's not!
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