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First time poster. Been a long time reader on the community and thankful for all the help that you guys provide.
I'm trying to develop an auto-reordering model and need some help with forecasting data.
Looking for a model for Seasonality and Trend Forecasting with several different products that each have their own trend. Attached is the historical sales data which will be the source.
I need Alteryx to group by each SKU and perform the forecasting process based on it's sales history. I have tried following the instructions from CristonS and a couple others' articles in addition to creating batch macros, but keep running into errors.
The forecast for each SKU is for the next 1 year. If possible, the next 3 months' forecast needs to be comparatively more accurate than several months into the future.
The source data will refresh every week with new inputs(this workflow is already ready). Model needs to account for these continuous changes and make adjustments accordingly for the entire year.
This should get you started, but I'm not an expert on time series modeling. The attached workflow features a batch macro that will create a new ARIMA model (uniquely evaluating trend and seasonality). for each [INV_ITEM_ID] value, and output the forecast for the next 12 periods (months).
To enable seasonal differencing on the ARIMA tool: on the "Model Customization (optional)" tab, there's a couple check boxes and a numeric input to adjust. A setting of 1 will use the trend of the last (1) year in the forecast of each period.
This should get you up and running (forecasting). Let me know if you have any questions about this workflow. Hopefully others with more expertise in time series modeling can chime in with model suggestions.
There is a way to "downgrade" the version by editing the XML of the workflow, but 2018.3 is pretty old at this point so maybe it is time for an upgrade. Let me know if you have any questions about either option.
Have you tried out the TS Model Factory Tool yet? It is a free download from the public gallery and allows you to use a string field for grouping (just convert the [group] to string). This will create a unique model for each group with sufficient data (24 months in this case). You can use the TS Forecast Factory Tool to make predictions from those models.
I tried using those tools, but I am not very well versed with using them and keep hitting obstacles like 'A record was created with no fields and input was not initialized' errors.
I have re-attached an updated data set and looking to forecast data for the rest of 2020. One tab has data at a consolidated level and the other tab has data from a plant level. Looking to forecast for both tabs.