Data Science and Design Thinking: The 5-Minute Interview with Stefan Wendin, Neo4j Innovation Lab

“The Innovation Lab is a concept that we developed, bringing the best of data science and design thinking together,” said Stefan Wendin, Global Head of Business Design and Strategic Programs, Neo4j.

In this week’s five-minute interview (conducted at GraphTour), Stefan Wendin gives an overview of the Innovation Lab and how it develops new use cases.

What is the Innovation Lab?

The Innovation Lab is a concept we developed to bring the best of data science and design thinking together so that we can very quickly prototype and then validate the use cases presented to us.

What types of people do you like to bring together to make an Innovation Lab successful?

The more diverse the group, the better it is. We try to take the different kinds of mental paradigms that people have, which is very often based on the domain they work in or one they have studied, and then bring out the good parts of each and make a remix.

The group can include data scientists or architects, developers, business developers, marketing people, and sometimes HR. Basically, we want people with diverse backgrounds, because if we have eight people with the same background, we just have one voice and arrive at one thing. We like a mixed group of people on all levels, ages, and qualifications; the bigger the range, the better it is.

Feature Image Stefan Wendin

What is the end result of a successful Innovation Lab?

For me, the end result of a successful Innovation Lab is that we have validated a use case and found something of real and great value.

When we have a business case for that use case, we have a clear contingency plan on how to go forward. We can often save a year of talking about whether we should invest in graphs by just knowing that it is worth spending money on. This also allows us to spend the right money on the right things. After all, spending money on talking is also money spent, right? Instead, we have a great time working with graphs and creating a successful outcome.

Why do graphs and innovation go hand in hand?

On a level of ideation, for me, what I do is basically graphs. I take one thing, and I connect it to another thing. Apparently, that looks like magic to a lot of people. I don’t have any magical skills: I just bring things together.

That is also how Steve Jobs worked. A lot of technical people bash him because he didn’t invent anything. He basically took things and put them together, and in the end he created a new thing. This is a lot of how innovation works. And if we look at a graph, that’s what graph theory is basically about: the idea of weak ties connecting and trying to map those ties into networks.

I think this is one of the reasons that I fell in love with Neo4j. It enables connecting things with speed and flexibility, which is how I work with Post-it Notes. I can now do data science the same way. Graph technology just naturally lends itself to kind of unfolding or traversing the graph by saying, “I’m going over here, I’m going over there. And when I know this, I also know that.” It allows for discovering things that I didn’t know that I didn’t know, but that I want to know.

What advice do you have for people who are getting started with graphs?

To get started with anything, there is only one way. You need to start doing it, right? Download Neo4j and try it out. If you want to start with Innovation Labs, ping me and I’ll be happy to share the steps, but at the end of the day, there is only one way to do it, and that is to actually do it.

Think about learning to swim. You can’t learn to swim by downloading PDFs. You need to get in the water. This is the way we try to design, to remove the friction of people trying on their own. Working with graphs is a change, and we all know that change is a bit painful. Removing that pain is part of my job.

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