Extracting insights from data

With those backgrounds ranging from mathematics to engineering, you might be wondering what data science entails exactly. The term data science is actually somewhat misleading; decision intelligence is a better term as we aim to help AkzoNobel to make better decisions (and to do so in a quicker, more automated way).

In Integrated Business Planning, we use large datasets to make key decisions across different functions – and do it fast. During their time at AkzoNobel, the interns contributed to several projects. Nicolas and William helped to improve the Inventory Health process. Nicolas helped users get the right insights through our analytics and reporting dashboard IHART (Inventory Health Analytics and Reporting Tool) which allows users to gain insights on performance, leading and lagging trends and do standardized root causing and action tracking. The databases and dashboards provide us, throughout the layers and functions of the company, with one source of truth.

William worked on prediction modeling (i.e. which items are expected to become slow moving and obsolete items so that we can track and prevent this proactively). He applied different machine learning methodologies to come up with the best fit model and thus best decision support.

Alessio helped to improve decisions on optimal order quantities, lane frequencies and storage locations in intercompany delivery flows. These decisions are usually too complex for planners to make as they cover a large portfolio which needs to be optimized on e.g. transport, storage, handling and inventory costs while guaranteeing service. If we set the parameters right in the system, then planners just need to follow the proposals in daily operations. To enable this, Alessio built a model and dashboard for reporting network optimization of intercompany delivery flows.

Lots of responsibility

One particular aspect of the internship was appreciated by all – the amount of responsibility entrusted to them and the freedom to choose how they would work. “All my thoughts and opinions were listened to and taken into consideration whenever there were decisions to be made,” says Alessio. “I didn’t feel any hierarchical pressure.”

Nicolas adds: “I had quite a few responsibilities but also the autonomy to work my own way. I could freely give my opinions to my colleagues and managers. Everyone was open-minded, willing to listen and ready to welcome different ideas and thoughts.”

“I like it when I have unique responsibilities,” says William. “It didn’t feel like I should follow or assist what others were doing, but actually drive the deliverables myself. Everyone was very knowledgeable and willing to help.”

The big picture of data science 

The interns were surprised to find that the team at AkzoNobel was working in an interdisciplinary way. Driven by clear targets and goals, the team combines knowledge and expertise from various functions.

“I was expecting the team to be very data-science restricted, says Alessio. “But I realized that the team’s capability is bigger than just data. Data science is a part of the team. We need people with different expertise like in supply chain and business. It makes a bigger impact.”

Making the most of the internship

What about opportunities to connect with others outside the team? As an international company with employees from all over the world, AkzoNobel is a great place to meet interesting new people.

“Things are well organized,” says William. “I had some training sessions at the beginning of the internship, and we visited different offices and locations. They introduced us to as much as possible! The culture is very open and everyone I met in the company was so welcoming.”

Nicolas says: “Groups like YourAkzoNobel (YAN) give employees opportunities to interact and get to know one another, and there are good links between the interns. I’m excited to continue with AkzoNobel as a Data Scientist when my internship concludes.”

While Nicolas continues his adventure with AkzoNobel as a Data Scientist, Alessio and William will return to their studies at the end of January.

“This was a great experience,” says Alessio. “I already know I eventually want to work with data in a business setting.”

William adds: “My interest in data science and my passion for applying theoretical knowledge to business problems led me here. This internship has given me a great opportunity to learn and grow.”

Are you or do you know someone who just like William, Alessio and Nicolas wants to make an equally important contribution as intern in our Integrated Business Planning Data Science team? Join us here.