Less than five years after graduating from university, he’s already guiding students through the world of data analytics and production technologies. Jakub Vancl is an expert in Shopfloor IT, who realises how important initial practical experiences are for students – and manages interns and their theses accordingly. After all, he’s still close to them in age.
It actually has double potential. Students can help us significantly, for example in the form of administrative tasks such as editing internal wiki pages on which we publish important information about projects, or instructions, for example how to gain access to a specific system. Or by verifying hypotheses for data analytics projects. For the area of IT, it also applies that there‘s a shortage of people in the market, so at the same time we hope that a functioning collaboration will ultimately lead to the students joining our company after completing their studies.
I’m in charge of data architecture, which is also related to data management. To put it very simply, I make sure data flows properly through the company and gets to the people that need it. For this purpose, I manage projects that deal with data analytics.
I studied at the Prague University of Economics and Business, the Faculty of Informatics and Statistics. My field of study focused on project management and business intelligence, so I can really apply what I learned in school. And that’s brilliant. Immediately after school, I joined another automotive company, where I also worked as an IT administrator and BI solution developer. When I found out about the opportunity to work in this position in Škoda, I was really interested, because the offered work mix so far corresponded most to what I had studied. And you’re right – it was a major challenge, and I learned a lot. But in IT a person must constantly educate themselves so that they don’t miss the train. It’s hard to catch up on any delay.
Definitely. Škoda is very happy to supplement its employees‘education. For example, a week ago I defended my final thesis in the postgraduate MBA study programme in which our company is a partner.
I analysed car production, specifically the effect of configuration on the length of vehicle production.
For example, I researched whether a car will take longer to produce if it includes heated seats. I used the machine learning method to predict how long it will take to manufacture a car with a certain specification, and which production elements will most affect overall length of production.
I was already thinking about my doctorate when I was approaching the end of my university studies. But I don’t really like when someone starts their doctorate immediately after school, without having some practical experience beforehand. So I said to myself that I’ll first try working in the field for a while. When I found out about the Data & Analytics for Business Management MBA programme in the Prague University of Economics and Business, in which ŠKODA AUTO is a partner, I said to myself that this is it; I’d like to avail of this opportunity. So I tried to arrange it with my boss, and I succeeded.
For example DASOP, which is an abbreviation of Data Analytical Shopfloor Operational Platform. It’s a project with which we reacted to a production problem during the launch of the new Octavias. At the time, there were software problems; there were faults in how the control units flashed, and our colleagues in production lacked the data that would help them find why it was happening. So, together with the team, we proposed a solution for obtaining this data and providing it to production experts, who then compiled the reporting themselves on its basis. At the same time, using the same platform, we also managed to ensure fast access to other data for reporting, so that it’s available in a matter of minutes.
Exactly. And the individual experts then create the reports themselves. It’s great progress, thanks to which we, the IT workers, are no longer as burdened by work that the business can do itself, if we prepare the conditions for it.
Some day, I’d like to be in charge of a data analytics team, with which we could formulate our own hypotheses and use data science and analytics to improve both the quality and speed of production.
Communication is the foundation; data analytics cannot be performed at some desk outside the production plant. First you must understand the process by which the actual data you’re analysing is created, and how it all works. Some time ago, one supplier tried to deliver a data analytics project from their Prague office, without coming here to have a look, and it didn’t work at all.
Unfortunately I don’t have time for that, but at the start of the project we always come to take a look at the field, what we’ll be working with.
In most cases, requests arrive directly from production experts. Nevertheless, if I come across an opportunity to improve something somewhere when solving a problem, we discuss it, and if everything really makes sense, then we define the assignment.
It’s definitely a plus that we’re close in age, because we have similar attitudes. More senior colleagues, on the other hand, have more experience.
First we announce a project in which we define and describe the topic for the final thesis. We display it on the career website, and if a student chooses it, then we arrange an interview with them – at these, I usually inform the students that it’s important to be as independent as possible. My role is primarily that of a mentor; I try to help them orient themselves, but I certainly won’t be writing the thesis for them. The student is then usually loaned Škoda technology – a notebook with access to the corporate network – and they can devote themselves to their topic. Afterwards, when they defend their thesis and we’re satisfied with the collaboration, we offer to hire them. Apart from the writing, students have the opportunity to avail of internships and participate in other topics. For this, they‘ll be financially remunerated.
When I was in university, I also always found a practical topic in collaboration with a company much more interesting than work on a theoretical level. I tried to find employment in a company, and now I’m happy to help others do the same. What’s more, Škoda is so big that practically anything can be invented. You can focus on the technological aspect of production, or devote yourself to the issue of marketing, finance, controlling… there are lots of topics Škoda can cover.
That too can be resolved. I was recently contacted by a student who registered for a relatively complex topic that involved a lot of maths. We included him in the selection primarily for maths and physics. He later told me directly that he doesn’t want to deal with such a difficult topic, and asked me if it’s possible to come up with a different one. I found out what he’s interested in, and together we came up with a new topic that he’s still verifying with the head of the school. And if it’s OK, then we’ll start working on it.
Of course I do. Our boss discourages us from working overtime unnecessarily, and urges us to have our personal and work lives in balance. For me, sport is a major component of relaxation. I participate in long-distance cross-country skiing races, for example the Jizerská 50 and the Vasaloppet in Sweden. Cross-country skiing is my main hobby.
I try to, but when there’s no snow I don’t enjoy roller skiing that much; usually I only force myself to do it in the autumn. I come from the Liberec Region, where I have good conditions for winter training. On roller skis it‘s slightly worse, because it’s hard to brake on them. So I solve it by only skiing uphill.
I commute to work, but by car. It takes me about 25 minutes. And now I actually haven’t been commuting there so regularly for a year. Even before the coronavirus, we had home office as a benefit, but now it’s more of a standard. I’m curious as to how the situation will develop further.