What do you use for model selection? Do you select the best model based on its cross-validated performance, or do you use in-sample measures like AIC? If so, there is a way to improve your selection process further. JORS recently published the paper of Nikos Kourentzes and I based on a simple but powerful idea: … Read more
So, our paper with Anna Sroginis got rejected from a special issue of the International Journal of Production Research after a second round of revision. And here is what I think about this! First things first, why am I writing this post? I want to share failures with the community, because I am tired of … Read more
When I read posts written by some ML experts, I sometimes notice that they either overlook or do not clearly explain a few crucial steps in demand forecasting. In this post, I want to highlight the three most important ones based on my personal experience. First and foremost, stationarity (see the proper definition of the … Read more
Here is another fascinating aspect of the seasonal profile in your data: it can evolve over time due to changing consumer preferences. How so? Let me explain. I’ve worked with a couple of companies where there were some examples of data with drastically changing seasonal patterns over just a few years. For example, Before Covid … Read more
Here is one thing you have probably not heard of: a workshop on Open Source Forecasting software, held in Beijing on 26th – 27th June 2025. This was a closed event, with speakers attending by invitation only. It focused on recent advancements and potential avenues in open-source forecasting software. But why am I writing about … Read more
Are there any PhD students in the crowd who want to learn more about forecasting? What about academic supervisors who have such students? Show me your hands! This post is for you! This September, we (Lancaster Centre for Marketing Analytics and Forecasting members) will deliver the Natcor course on Forecasting and Predictive Analytics at Lancaster … Read more
I’ve been acting as a reviewer lately, providing comments on papers about intermittent demand, and I’ve felt a bit frustrated by what some authors write. Let me explain. Several papers I reviewed claim that demand can be either intermittent or lumpy. They then mention the Syntetos-Boylan-Croston (SBC) classification and use the thresholds from Syntetos et … Read more
NHS has a helpful page with a set of questions you can ask your GP to ensure you receive the right treatment for your illness. Surprisingly, these questions can be applied in other fields as well. Here’s an example in applied forecasting, working with companies. I’m not going to go through all of them, I … Read more
If you have taken a course on forecasting or time series analysis, you’ve probably heard of ARIMA and the Box–Jenkins methodology. In my opinion, this methodology has a fundamental flaw and should not be used in practice. Here’s why. When Box and Jenkins wrote their book back in the 1960s, it was a very different … Read more
Everything is random! Your data, your model, its parameter estimates, the forecasts it produces, and even the minimum of the loss function you used. There is no such thing as a “deterministic” forecast – everything is stochastic! Whenever you work with data, you are working with a sample from a population. In some cases, this … Read more