Recently, our DR data scientist advisor has shown us how to go from basic model to process in "time series". What we're looking at now is how recipe fits into the picture. Would you have some recommendations for fitting recipe into a model that may involve some dependency on time series? with different inputs at multiple locations, it may be challenging to grasp an understanding of how to best assess recipe vs process vs time when all play an active role in the finished product. Any advice would be appreciated.