An Interview with Daan Wout | ORTEC

 

Happy new year dear reader. Last year, not too long ago, I sat down with Daan Wout. He is currently working at ORTEC, which is a very interesting company that leverages Data and Mathematics to create value for businesses and society. Similar to ORTEC, Daan is a very special person, so let’s see what he has to say!

Hi Daan, please could you share a bit about your background with us?

Yes of course! My name is Daan from Arnhem. I completed my high school studies in Eindhoven before joining TU Delft for my Bachelor’s degree in Mechanical Engineering. During this program, I also chose to study abroad in Australia and the USA, each for a semester. 

You studied engineering, but now you are not working as an engineer. How did that happen?

Frankly, after completing my Bachelor’s degree, I didn’t already know what I wanted to do. However, I had joined the board of Yes!Delft Students, which is a student association focused on entrepreneurship that provided students with the knowledge and tools necessary to start their own company. Here, I learned a lot about the world of business!

After spending one year with Yes!Delft, I decided to pursue a Master’s degree in Systems and Control. This field may sound unfamiliar to you, but you could imagine the field dealing with finding ways to balance a launching rocket. Without control science, rockets would simply go upside down and crash! In my thesis, however, instead of launching rockets, I decided to explore the field of data science. (I’m sorry to interrupt, but does that mean your thesis is not about systems and control, or your major?) This might be a surprise, but during your thesis, you could investigate anything you find interesting, given your background eligibility and your supervisor’s permission. For me, I did research in reinforcement learning. A part of my research involved using optimization (which you may have done in university) in order to find the point where human input is most valuable for a computer or robot. This may sound fuzzy, but the research did motivate me to do data science, which is something I now do daily.

That was a very interesting path that you took! What about your path to ORTEC?

I have to say that it was very stressful while writing my thesis. My supervisor came up with the idea to publish my findings, so running tight deadlines and night work had been a regular activity. Thus, after completing this daunting task, I spent a couple of months to “revive” as well as think about my next move. I found that control science was very interesting, yet only in an academic perspective. However, for work, I gravitated more towards data science. From a business perspective, what you could do with data and big data is just massive, ranging from anomaly detection, predictive maintenance, fraud detection, or optimization just to name a few. Moreover, though I enjoyed doing research, I didn’t particularly like the writing process, which is unavoidable in academia. So, I decided it was time to join a company.

I had talked to many companies here in the Netherlands, asking them for instance, what they were working on, what are the challenges, and could I help with that. In the end, I came to ORTEC and talked to the recruiter, who made me very enthusiastic about what ORTEC had been doing, which helped me make the decision to join ORTEC.

Could you tell us a bit more about ORTEC?

An interesting fact is that ORTEC used to focus on Operations Research technology, and hence the name “O-R-tech”! Nowadays, however, we are focusing more and more on data science and optimization. In fact, ORTEC supports (large) companies in getting more data driven by “The Analytics Academy” that we organize. Client enterprises such as Shell, BP, Phillips… are particularly interested, since ORTEC could help them answer many important questions. For example, when is equipment likely to fail? Or, for Shell, can we use available data to know where we can drill for oil and gas.   

Just a quick question, could you tell us the difference between Operations Research (OR) and Data Science?

I think that OR mainly deals with the day-to-day operations of a business such as supply chains or the scheduling of personnel. A point where you usually end up with in OR is optimization, for instance in logistics, how you could schedule drivers best. And of course, data science could be a big part in OR, since we are interested not only in what’s currently being done, but also what can be improved in the future. However, there are situations in data science where OR is not involved. A very good example is predictive maintenance. Here we use more statistical modeling to predict, for instance, the longevity of gas valves. So, I would say that data science is more future focused.

Thank you for your clarification. Continuing the discussion of ORTEC, how is the company organized and what are its operations?

I would say that ORTEC does A LOT! Within ORTEC, there are two rough departments. One is the product side and the other is consulting.

In the product department, we offer standardized products to companies such as personal scheduling programs, inventory routings or logistics manager software. To put it more concretely, ORTEC develops one software package, and depending on the needs of the client, several settings can be tweaked to customize the product. A good example is a personnel scheduling program for the health sector, a sector in which ORTEC is very active. With this program, healthcare workers could give their work preferences (such as preferred time slots , workdays), and the program will then do some magic using for instance linear programming, optimization, to create an optimal schedule. You may think that this is similar to scheduling your university timetable, but for the health sector case, this involves a more human aspect as opposed to the more clear set rules of your school timetable (such as a lecturer cannot be in two lectures at the same time). In other words, the software has a rating algorithm for the preferences of people in order to schedule optimally.

On the other side is consulting, which is where I am active. Here we make programs which are really customized for the client. We don’t make a product twice but instead we make a “customary object” that the customer wants. For example, my colleague is working on predictive maintenance on up to one million valves of Shell. Of course, such a product cannot be applied to another customer, since only Shell needs it. Some of our customers in this department include ASML, Phillips, BP, PostNL, … who require specialized products. These companies also come to ORTEC for strategic advice, which doesn’t require much coding.

What project are you working on now?

I am currently working on an optimization application for gas production for Shell. Specifically, this is an optimization application to maximize the output of a certain asset. Three years ago, when the project commenced, ORTEC had not been involved yet. However, after Shell tested the feasibility of the project, they invited ORTEC to join. Thus, we had, at our fingertips, the tools and knowledge to accelerate the project.

 How did you get up-to-date with all the research and workflow of the existing project when you arrived?

You do a lot of trainings! Regarding ORTEC, in the first 4 weeks you are trained a lot with the tools that already exist such as a crash course in python, a program to solve linear optimization problems, or online courses in React, Angular to make web pages and applications… You will get the necessary training depending on what your first project will be.

Regarding particularly myself with Shell, that was quite difficult. However, we would organize a lot of meetings, ask a lot of questions, and in about 1 or 2 months, believe me, you will know around 95% of what they had already been researching.

What does it feel like working at ORTEC?

Python and backend coding were not something I knew beforehand, so when I was asked to do such a project, I thought: “I have never done that before!”. I knew a bit of MATLAB, but when I saw a bit of Python, I felt I had no idea how to approach this. That was why I asked a lot of questions with my colleagues. We have a lot of knowledge at ORTEC, and everyone is very willing to help thanks to the rather “flat” organization. Thus, the nice thing is you could approach anyone you need for help. For example, we have Python experts who could help you on what packages to learn for communicating between databases, or optimization experts who could recommend and show you free but powerful software. Therefore, all the information you need can be found within ORTEC, and that is, in my opinion, an advantage of working here. Thus, you never feel you are left alone in the dark. There will always be someone willing to help you.

There seems to be many experts at ORTEC. I am curious to know who works here?

I have seen many different people at ORTEC, but all of them have a common interest in technical issues. Everyone is interested in different techniques in data science, optimization, etc. They have a lot of knowledge about their interests and loves to talk about them. Thus, working here means you will also know and learn a lot! Another attribute I find in people at ORTEC, especially in the consulting department, is their ability to explain the complex applications to the client in a very simple way. Thus, they strike a very good balance between technical understanding and communication.

Working at ORTEC does seem like a great advantage! Do you have any advice for students still in their Bachelor’s years before we wrap this up?

For Bachelor’s students, I would say that this is a good time to explore what is out there, and what you can do to help. So, my best advice is to talk to a lot of people, companies or academia, and explore what you would like to do best. At ORTEC, you will see a lot of mathematical/statistical/data science techniques and the use cases that you may have encountered in your studies, but don’t be tied to just one company or one technique. Try to talk to many people, look at what many companies are doing and explore the many techniques that you find interesting.

Thank you very much for sharing your experiences, both academic and professional. We wish you all the best in your career, and we hope that you stay safe during this pandemic!