The road to becoming a Process Mining consultant

The Process Mining Consultants at Bright Cape analyze operational processes and guide our clients through the entire process. They play an important role in translating complex data into meaningful insights to show clients what actually happened in the process and help them understand why it happened. This data-driven approach uncovers inefficiencies to effectuate important improvements. One of our Process Mining Consultants, Femke, started with us last year. She is a young professional with a background in mathematics, that just happened to run into the field of Process Mining. Please read Femke’s story, as she explains how and why she kick-started her Process Mining career with us.

It was the beginning of 2019 and the schedule was clear: after five and a half years of studying, I would finish my master’s degree in mathematics around March 2020, and after one or two months of vacation, I would find a job within the mathematics field. Nothing could be further from the truth. In December 2021, I started working as a Process Mining consultant at Bright Cape… I hear you thinking: What happened between March 2020 and December 2021? And why the switch? I will tell you in a minute, and a spoiler: Covid-19 had nothing to do with it.

Pursuing a master’s degree in Data Science

First of all, I spend the last months of my mathematics master’s degree in Australia to do my graduation project and travel around. The idea was to finish the last two months of the graduation project when I came back to the Netherlands in January 2020. However, during this period abroad, I felt that my time as a student was almost over, but I wasn’t ready for work-life at all. I wanted to stay close to my study association and my friends and enjoy student life a little longer. On top of that, I really wanted to keep learning. I never disliked it and I knew that if I wanted to extend my knowledge, this was the time to do so. Several fellow students were doing a double master’s degree, combining mathematics and data science, which interested me because I had already done quite some programming by that time. Besides, data science matches very well with mathematics. After a short period of exploring my options, it turned out it would only take me a little over a year to finish the extra master. So there I was, starting a second master in data science. The new schedule: graduating with a double master’s degree in September 2021. This time, I succeeded to reach this goal.

Discovering Process Mining and its added value

What I didn’t know back then was that this choice would lead me to where I am right now. Why? Because I discovered the field of Process Mining, which I didn’t even know existed. Two of the courses that I followed were about the basics of Process Mining. What interested me most was the switch from an unstructured event log full of information to a clear overview of a process model together with its bottlenecks and inefficiencies. It was touchable and understandable, and the number of possibilities to improve a process is huge.

 

“We had to be creative and develop our own algorithm to discover a fitting and clear process model”

– Femke van der Schoot, Process Mining Consultant

 

After this discovery, I became interested in a follow-up graduation project in the field of process mining. Supervised by a Process Mining expert from the TU/e, we helped a Dutch hospital to get a proper overview of their processes of scheduling surgeries for the operating room. Their event log was really complex and full of extra information for every surgery, but this resulted in the fact that none of the existing process discovery techniques worked properly. Hence, we had to be creative and developed our own algorithm to discover a fitting and clear process model. The Dutch hospital had a second request: How can we reduce the number of rescheduling events? Our approach: prediction algorithms combined with pattern recognition techniques. The task was to find frequent patterns in the attributes of a surgery that indicated a high probability of rescheduling this surgery. This part was more related to data science and less to Process Mining. However, this didn’t make it less fun. In fact, my supervisor proposed to write a paper together about this out-of-the-box approach, and in the end, we even received the “best paper award” from the conference committee where we presented our paper. It was a great way to end my time as a student.

Process Mining as my preferred job choice

The next step, I had already postponed once, but this time I was ready: I needed to find a job. An advantage of having a double master’s degree: I had plenty of jobs to apply for. A disadvantage of a double master’s degree: I had plenty of jobs to apply for… I had to answer many questions: Do I want to continue in the mathematics field? Or do I want to continue in the data science field? Can I find a job that combines these two? And if I choose data science, do I want to specialize in Process Mining and become a Process Mining expert? Especially this last question didn’t want to leave me alone.

While looking around for jobs, Bright Cape was the first company that I came across to mention Process Mining as a core competency. They were looking for a creative, critical thinker; someone who wants to uncover the meaning behind data and is driven to learn more. I don’t think I could have fit better in any other job description. All these skills were exactly what guided me through my second graduation project. I was immediately enthusiastic to apply for the vacancy of Process Mining consultant. Just a few weeks later, I found myself working at Bright Cape in the Process Mining team, learning from the experts to become a Process Mining expert myself.

Thinking about a possible career as a Process Mining Consultant?

Get in touch with me. I am happy to answer any questions that you might have to help you make the right decisions regarding your career path. And who knows, we might even become colleagues.

We've got great career opportunities

Join our team and guide our clients in using their data for good by building and implementing scalable, sustainable data science solutions.