Yves Sagaert
University of Ghent

How did you get started in forecasting?

In 2012, I got in touch with the field of forecasting through my master thesis. This inspired me to start a PhD the very next year. I did my research in both Ghent University and Lancaster University Management School. I focused on enriching business forecasts with external data as the volatile global economy brought new opportunities in this field. In sales forecasting on medium-long term, I found macro-economic leading indicators especially interesting as these proved to enhance forecasting models. During my PhD, I started to work in a consulting firm, and found a tremendous interest of companies in my subject.

How was it to do research with two universities?

It was an unique experience to taste the different research cultures in Belgium and UK. Doing research in another country broadened my horizon, which enriched my research. During my research stays at the Lancaster Centre for Forecasting, I got submerged in an open and friendly culture of collaboration. The research seminars and late-night discussions really moved my research ahead. One might even say I got infected with the spirit of forecasting during my time in Lancaster.  On top of that, it broadened my network while interactions with other researchers and companies were unbelievable valuable for my PhD. Thanks to my supervisor Nikos Kourentzes, I got the opportunity to work with George Athanasopoulos in the Monash University in Australia. Furthermore, via my friends in Lancaster, I got the occasion to present at the University of Cardiff and the Saint Petersburg State University.

What areas of forecasting interest you?

I find it fascinating to see the potential of leading indicators for business forecasts. The concept of leading indicators is that they contain important information in advance to the realized sales, so these indicators can improve medium-long term sales forecasts. This is especially interesting in a volatile environment and a lot of companies are already reviewing leading indicators. However, selecting the most valuable indicators is incredible challenging! On the one hand, the domain knowledge for recognizing the interesting indicators is with the business users. On the other hand, this is a very labor-intensive task and hard to scale. Furthermore, a purely judgmental approach is known to be prone to bias in both the selection and estimation. This makes it a very interesting field to do research in.

Are you working with companies to improve their forecasting practices?

Yes, I enjoy the interactions with business users as it inspires me for new research ideas. Certain additional forecasting challenges are revealed while doing these real-life company cases.

I notice an increasing effort of companies to put energy into digitalization. More processes are getting monitored, and data is generated on a very low level of detail. I think this is a good point for forecasting, as more data opens up interesting research questions for new data-intensive models in forecasting. It takes time to set up these systems to collect and process the data, but growing data has enormous potential for new business cases.

How has the International Institute of Forecasting influenced you?

In my experience, the international forecasting community is very open to new researchers. I presented my research the first time at the International Symposium on Forecasting in 2014 in Rotterdam. Every year, the conference provides a broad spectrum on the different areas in forecasting, what makes it a very enriching conference to attend. I find it very motivating to receive constructive and challenging feedback from the audience on my research presentations. Also, it is exciting to meet other young researchers from around the world during the conference. Moreover, it was great to get the opportunity to explain my research in a non-technical way in Foresight, the forecasting journal for practitioners.

What do you do in your free time?

For me, forecasting is my free time. Also, I recently got a baby girl and I cherish every moment with my wife and her. Additionally, I enjoy meeting up with friends, gardening and renovating our house, and installing my own Internet-of-Things (IoT) home automation. I’m thus creating more home data that can be used for forecasting (laughs).

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