There are a couple of settings that may help in case of irrelevant time periods, one could be "ignore time periods", this one will do lineal interpolation of the datapoints before passing the history to the forecasting algorithm, another option would be to see If the datapoints are detected as outliers, the correction will use the forecasting model to replace outlier the value on the inputted values to the algorithm, however outliers are only detected on the last 20% of the history.
Original Message:
Sent: Mon October 30, 2023 10:36 AM
From: Asgeir Thorgeirsson
Subject: PAW Forecasting issues
Thank you, Julian
It would be useful if I could create a prediction from one year's pattern (as you highlight in red) and the trend in the past few months.
The patterns from the past are sometimes irrelevant and if you think of the covid periods then everything was skewed.
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Asgeir Thorgeirsson
Original Message:
Sent: Mon October 30, 2023 10:25 AM
From: Julian
Subject: PAW Forecasting issues
Hi Asgeir,
Few ideas,
- Move the sandbox dimension to the rows
- Makes sense,
- Seasonality is not auto-detected, because there is no repeatable pattern in the data (as I said, you can see about 1 season and a half in the chart), for the algorithm to pick a value or trend just as in "the previous month last year", it will have to get the seasonality, so you need a repeated pattern, in the chart there iso. the Unable to get the preview could be due to insufficient points for the 12 time periods input (but deserves some investigation). More data should give you better results (you mentioned 2 years of data, but at least in the chart only 1 year and 8 months are shown as historical data), In short this pattern must be present at least twice :
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Julian
Original Message:
Sent: Sat October 28, 2023 07:48 AM
From: Asgeir Thorgeirsson
Subject: PAW Forecasting issues
Here is something to think about for designers/developers of PAW that comes from my old software engineer heart
When selecting an option like "Seasonality" it is confusing for the user if you change the status icon and also the label for that option.

The image below indicates that the seasonality is not manual

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Asgeir Thorgeirsson
Original Message:
Sent: Fri October 27, 2023 12:31 PM
From: Julian
Subject: PAW Forecasting issues
HI Asgeir,
- Unfortunately, for the forecast, the sandbox dimension cannot be either in the context or the bench. MDX wise there is no difference between having those dimension on bench or context. If you pick a sandbox in the view then the forecast will be written to that sandbox. However I do see why a user may be confused since the message does not mention Bench
- If the forecast (dimension) columns are changed it should clear the values, the redundant message seem like a bug.
- From what I can see in the chart, the forecast is performing well, for the algorithm to work and detect the seasonality automatically, at least 2 seasons are required (otherwise there is no repeatable pattern), what I can see on the chart is about 1 season and a half, in some cases inputting the seasonality manually will help, but the best option is to add more historical data.
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Julian
Original Message:
Sent: Fri October 27, 2023 08:55 AM
From: Asgeir Thorgeirsson
Subject: PAW Forecasting issues
Hi all
I guess I am just reporting some bugs in the PAW forecasting option
- Not able to preview due to "Sandboxing" error
- Error message each time I change some dimension, Asks me to select the forecasting periods again even though they are visibly still selected.
- When the preview works based on periodical data, the result is useless.
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1. Not able to preview due to "Sandboxing" error
The Base sandbox dimension is in the "Bench", not in the "Context Bar" but I still get this error

2. Error message each time I change some dimension,
Asks me to select the forecasting periods again even though they are visibly still selected.
The start date is selected but I always get this message
3. When the preview works based on periodical data, the result is useless.
Based on these periodical values, this forecasting result makes no sense, ..at least will not help

Thanks, Asgeir
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Asgeir Thorgeirsson
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