Maker Mindset for Data Entrepreneurs
This time the story behind the person who normally shares others’ stories. He was the marketing rockstar behind Science Rockstars, previously worked as a “Travel Scientist” for Booking.com, has built his social media presence under the name “happy bandits”, loves hanging out with extraordinary people, regularly stands in the spotlights while wearing sunglasses, teaches others the art of persuasive technology and who is on a mission to fix the future. I am talking about Arjan Haring 🔮🔨 . Keep on reading to learn more about the underlying ideas and strategies of the Scientific Advisor who sees it as the ultimate challenge to contribute to building the “Stanford for Data Science”.
Distribution is Key
Since May 2017 Arjan has fulfilled the role of Scientific Advisor which he describes as follows: “In the first place I advise on future developments of Data Science, but I also try to connect JADS academics with other prominent researchers in their respective field of expertise.” For the outside world people can see he has been very active on social media (Twitter/LinkedIn) and initiates numerous Data Science meetups at JADS. For colleagues and students at JADS he is often known for his widespread network and creative ideas.
He elaborates on this inner drive to share and connect: “I love initiating meaningful things, but it is as least as important to communicate your message with the rest of world. Producing high-quality work is time-consuming and definitely not for everyone, but it often requires another set of capabilities to get it to the attention of other clever people.”
Getting Your Foot in the Door
One of the things that stood out to me during the interview was his ambitious perspective to aim as high as possible in whatever he is undertaking. An example that illustrates it quite well: “Once I come across an excellent read, I just send the authors an email. In most cases it’s a piece of cake to find out their email addresses online.” My logical follow-up question was whether he always gets a reply to his emails: “I might have a backlog of 1000 people who never responded. But that doesn’t matter, I simply don’t give a crap. It is about the people who do respond.” Then we moved on to some tips and tricks he deployed to get his foot in the door of renowned entrepreneurs and academics. “Ideally you use a funny and energetic voice of tone; big names are all too often taken way too seriously. They prefer to be treated like everybody else.”
Academia 🤝 Industry
In line with my previous post I asked Arjan about his view on the differences between the two worlds: “Most companies are very far away from science. That is a bit of a shame, but experiments can close this gap. Once companies start adopting a data-driven mindset they come closer to the basic principles of science. On the other hand, I expect that scientists will shortly reap the benefits of industry collaborations due to the exponential growth of data collection. This will lead to new research areas which you already see happening at tech giants such as Twitter and Facebook.”
Despite his general concerns about the lack of an experiment-driven culture in business, it turns out Arjan is very excited about the tech giant whose head office is located in the beautiful capital of our very own country: Booking.com. In his former role as — what his mentor Mats Einarsen likes to refer to as — Travel Scientist Arjan was trying to find answers to questions such as: “Are we able to accurately forecast at which holiday destination potential travelers will have the best experience of their life?”
What he relished most in this position was the data-driven culture: “In the morning you drank a cup of coffee, thought of an experiment and delivered it to the ‘Experiment Tool’ (i.e. Booking’s in-house built A/B testing platform). You thus executed the experiment and evaluated its results after which the process started all over again the day after. This approach was so radically different than what was common for most companies at the time: first a meeting to brainstorm ideas, then someone needed to write a project plan, another meeting to discuss the project plan, yet another meeting to create a budget to find out two years along the line that the experiment did not work at all.”
He continues: “In business assumptions are often still the norm: ‘I think that…’ [followed by a list of personal beliefs]. The first thing they asked at Booking.com once you had shared your new idea was: ‘Do you have any data to support that claim?’. I have not yet come across a single company that has integrated this data-driven approach across all departments and processes to such an extent.”
Data Science with a Human Touch
Although Arjan warmly welcomes new flagship, research and educational partnerships, he also expressed himself somewhat critical about certain developments in the industry. “I am not a fan of typical engineering questions such as ‘What is your big data technology stack?’ because it neglects the bigger picture: what is the added value; how does it make the world a better place? In Data Science it is currently one big technology feast. That is the risk of tech fanboys who get down to the nitty-gritty.”
Back in 2013 he wrote an article, Why We Overestimate Technology and Underestimate the Power of Words, which has a similar message: incorporating more, better, faster hot blackbox technologies does not necessarily make a world of difference, it is sometimes as straightforward as copy that does.
“In Data Science it is currently one big technology feast. That is the risk of tech fanboys who get down to the nitty-gritty.”
Doing > Dreaming
Next to his role as Scientific Advisor, he is also a lecturer for the Data Entrepreneurship in Action MSc-course. He elaborates on what characterizes a JADS-student: “We distinguish ourselves by understanding both engineering and business. That is a challenging combination and I must say there is still a big gap to close: in the industry but also in our own thinking. I would, for example, love to see students adopt more of a ‘Maker Mindset’. Regard university as a playground for experimentation and start building and testing. And please don’t limit yourself to the availability of a dataset. You can turn on a video camera, let it record for an hour and you have more than enough data to work with. On a final note, I would encourage all students to openly share their ideas rather than ask for a Non-Disclosure Agreement (NDA) before they have actually put in the work.”
As the first batch of Data Entrepreneurs (picture above) is about to graduate in the summer of 2018 I asked him about their career perspectives and where he currently sees data science opportunities worth exploiting. “If I would start a company tomorrow it would be in the field of energy. That is because the energy transition is every fascinating due to its nature: supply and demand fluctuate heavily throughout the year which makes it an interesting optimisation problem. Aside from that, I believe that plenty of charitable and governmental processes could be significantly streamlined using data science principles. At the same time we should question whether it is ethically sound that Google and Facebook capitalize on, for example, the presidential elections.”
Stanford for Data Science
As a closing question I wondered how he expects the JADS ecosystem will develop over the next few years. “In my vision JADS has a powerful professional network in the same way Stanford’s Computer Science department is well-known for its industry-academia partnerships: the majority of all tech-investments in The States directly go to Stanford alumni. In other words, JADS should be the place to be for investors. Even though our current network (TU/e & Tilburg University) is already strong, there is still room to push through to the next level. On a normal working day I hope to see incredibly smart and entrepreneurial people hanging around in the Mariënburg.”
Some may say ‘your network is your net worth’. Beyond a doubt there is a grain of truth in that statement: your network has a crucial role to play, especially for entrepreneurs in making. But in order to become the worlds’ leading teaching and research institution there is probably more to it than that. Let’s take a step back for a moment: why should world-class companies and the greatest investors be willing to cooperate at all? Most likely because of the people that brought them there in the first place: students, staff and academia. In that regard attracting and retaining the best people is key, because talent speaks for itself. It goes without saying that all unicorns will then find their way to the Mariënburg for sure..
As you have read, Arjan definitely puts the bar extremely high, but at this moment of the year — while you still have good faith in keeping your New Year’s Resolutions — that might actually be a good thing. So on that note, one of the goals for “The Outlier” in 2018 is to increase involvement and engagement among the data science community. Hence my question to you: “How would your ultimate ‘Stanford for Data Science’ look like? Let me know in the comments down below ❤️!
