Royal Smit & Zoon strengthens innovation power with in-company Design of Experiments course

At Royal Smit & Zoon, a family business with an impressive history of more than 200 years, innovation is at the forefront. Making the leather industry more sustainable requires well-founded decisions backed by data. For this reason, the R&D team recently completed the in-company Design of Experiments (DoE) course at PAOTM. We spoke with Wouter Hendriksen and Anouk Roolvink about their experiences.

Wouter Hendriksen is R&D Manager at Nera, a subsidiary of Royal Smit & Zoon specializing in tanning agents. He is at the forefront of the company’s data-driven approach. “Since 2015, we have increasingly been using statistics and DoE to purposefully develop chemistry and leather applications,” he explains.

Anouk Roolvink has been working as a product development engineer in the retanning department since 2018. “I focus on synthetic tannings and support colleagues in applying DoE. Since not everyone has the same level of experience, I wanted us to build a solid foundation together.”

Why an in-company course?
Within the team, DoE experience ranged from “heard of it once” to active users. Some mainly knew it from reports, while others used it regularly,” says Anouk. "The course was intended to get the team on the same page, so we can share and strengthen knowledge.” Wouter adds: “We had training five years ago, but the group has since grown. With this course, we wanted to raise the overall level.”

Smit & Zoon chose PAOTM because of both flexibility and content alignment. We saw a previous customer case from the chemical industry, which gave us confidence. And we immediately noticed that PAOTM really thought along with us about the content and setup,” Hendriksen notes.

Practical use of DoE in the process
In leather processing, Royal Smit & Zoon uses DoE to optimize process parameters and improve leather quality.“For example, we use it to study how we can improve light fastness in leather,” Hendriksen explains. “By systematically testing variations in chemistry or process steps, we can better understand which factors influence properties such as fading caused by sunlight.” Roolvink: “It’s like cooking: you play with ingredients, quantities, temperature, and time. DoE helps us get a grip on that.”

AI as an extra asset in the training
An unexpected enrichment during the course was the integration of generative AI such as ChatGPT or CoPilot. Course leader Koo Rijpkema has extensive knowledge of this and likes to provide insights into the usefulness of AI in data analysis.“Koo showed very concretely how you can combine tools like R or Minitab with generative AI to process data more efficiently and plan experiments,” Hendriksen explains. “That perfectly matched our ambition to further advance digitalization.” Roolvink especially appreciated the balance between innovation and realism: “Koo also emphasized that AI is a tool—you remain responsible for interpreting the outcomes. That nuance was very valuable.”

Follow-up actions and internal reinforcement
For the team, the course was not a one-off exercise.“We want to organize group sessions where we discuss completed experiments,” Anouk explains. “That way, the knowledge remains active.”
Using existing intern reports as practice material is also part of the approach. “We’ll soon pick up an old project as a case study,” she adds. “We learn from what has already been done while staying sharp.”

Recommendation for other organizations
Both Hendriksen and Roolvink would certainly recommend an in-company training. “Because you’re only with your own team, you can really tailor the content to your practice,” says Hendriksen. And valuable conversations often arise in the informal moments.” Roolvink: “Make sure there is enough room to go deeper into the topics that matter for your team.”

Looking ahead
For now, new colleagues will be trained internally. In a few years, Wouter and Anouk plan to organize another in-company training. “We currently have a lot of expertise in-house,” says Hendriksen. “But repeating it periodically helps the team stay sharp.”

DoE for your organization
Curious what a Design of Experiments course could mean for your organization?
Whether you are working on process optimization, product development, or data analysis: PAOTM offers practice-oriented courses in Design of Experiments, statistics, and data science—both in-company and open courses. Our lecturers combine scientific expertise with practical application. Contact us and discover how we can take your team to the next level together!