String to Date&Time node and decision tree learner

@ajatal my impression is that you have to put more work into understanding and setting up your data. What information is there that might influence the orders and their timing. Do you have any data about that. Is it seasonal? Would it depend on the customer placing the oder - and so on.

The next thing is the presentation of data to the model. As said before using fixed dates in a model would not make much sense since it would then only work for past data. You might be able to create something like a prefect model for the past which might be entirely useless for further predictions (if this is what you seek).

You have plenty of model types in KNIME (Can KNIME be used to show the employment and unemployment rate in the UK from the year 2008-2018, showing the prediction for the next year? - #11 by mlauber71) but you will have to prepare the data in the right way. And again: the problem might be better formulated as a time series task. But that depends on the data and what you want to achieve.

Maybe you could provide sample data representing your challenge without spelling any secrets. Sometime Kaggle might have a similar case you could adapt.