Hi There, I have an interesting challenge that I think I'll have to write customized coding for. Thought I'd post it on this forum to get some statistics and expert ideas... I have a data set of monthly volumes of a product by province, region, & then city. I use Forecast Studio to create projects and use the rules of hierarchal forecasting in the tool for a bottom up reconcilation. The timeseries trends show growth, however I still enter in an provincial override to almost 100% inflate that growth for the longterm forecast. FS disaggregates the overide by proportions of the reconciled forecast. My challenge here is I'd like to decrease those proportions and distribute out the disaggregations for the long term overrides more evenly. For example if one product has 10% of the distributed override, then for next override, I'd like that allocate only 8% of the override, and then next month 5% etc etc. Since the granular timeseries trends are increasing, the way FS is disaggregating the override does not reflect this scenario. Is there a way to code this situation or control/change the distribution of how the override is allocated in FS (other then the two options of: based off of proportions or evenly distributed) ? Thank you kindly! ... View more

Hi There, I have successfully used Forecast Studio (FS) for many timeseries projects. I have encountered a new issue with the data that I'm forecasting. I am forecasting for a new product by regions. I am comfortable with the growth forecasts selected for the first 2 years however knowing the evolving industry, in the latter years the trend will not show much growth and at one point should level out (ie. logarithmic type of trend). The problem is, the models selected do not reflect this as the data actuals will show a growth trend. 1. Is there a way in FS where I can select for models to only choose the group of 'log' types of curve fitting models? 2. Or any suggestions on modeling this data? The dataset is very large with many products and regions so it would be time consuming to select specifically an appropriate logit model for each timeseries at each level. Thanks in advance. ... View more