### Joannes Vermorel

As a rule of thumb, whenever supply chain is involved, probabilistic forecasts yield superior results compared to traditional periodic forecasts; i.e., forecasts expressed per day, week or month. Yet, there are also a few situations where demand uncertainty is very low such as where demand is very steady and non-sparse. In those situations, it might still make sense to consider periodic demand forecasts.

Therefore, we have extended our latest forecasting engine to support periodic forecasts. This feature is live and readily available for all Lokad accounts. The output of the periodic forecast takes the form of a table with 4 columns:

- the product identifier
- the target date for the forecast
- the mean value for the demand
- the sigma (square root of the variance) for the demand

In particular, unlike the probabilistic forecast, the periodic forecast does return fractional demand values, even if the historical demand is expressed as pure integers, typically reflecting the number of units sold.

Under the hood, this periodic forecast is obtained by generating a probabilistic forecast, and by projecting the *mean* and the *variance* of the resulting distributions. This periodic forecast benefits from all the perks associated with the probabilistic forecast such as native support for stockouts, for example.