How did you become a forecaster?
My first experience with forecasting was back in 2017. At the time, I was working on inventory optimization at Bridgestone. We worked on using ML to create demand forecasts with another consultancy team. This triggered my interest and curiosity. I started to learn how to code in Python, as well as data science best practices (I learned both by following online classes).
Since then, I have been working on many different forecasting models (using both ML and statistical techniques), always relying on a data-driven scientific approach. I think I fell in love with statistical models when I discovered the temporal aggregation logic proposed by Nikolaos Kourentzes.
In 2018, I published Data Science for Supply Chain Forecasting (2nd edition published in 2021) to show to practitioners how to apply my models & ideas.
What areas of forecasting interest you?
Anything that can be used to make better forecasts for supply chains! I am not dogmatic concerning models and always on the lookout for new ideas. I like to blend different approaches and models. The more, the better.
How has the International Institute of Forecasters influenced you?
I am usually working alone on projects, but I am always looking to discuss and debate with other experts worldwide. I spend a lot of time reviewing other people’s work and projects. If I like the proposed ideas, I usually contact the author personally to start a discussion.
What do you do in your free time?
I like to spend time with friends and family around brunch or diner (usually playing board games). I am also a big metal music fan, listening to it all day long to stay focused and energized.