how to create adoption dashboard / widgets from scratch (using the out-of-the-box formulas we will make available in all cubes)
special callout about the nuances of the "comments" and "Scrap" formulas. ---> We had an issue while creating these formulas where they did not work properly when you try to pivot them by day. but anything higher than the day level (week or above) works fine. for this we created 2 variants of those formulas. the one called "detail" is the one to use by day, and the regular one in all other cases. This was documented roughly in a previous version of the internal confluence doc but looks like it was removed while rewriting. but if you look at previous document versions in confluence and check version 19 you will see my old notes there.
By following the instructions below, you will be able to effortlessly navigate and engage with the data present in the dashboard.
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From here, users can freely configure and adjust the weighting of each metric in the Overall Adoption Score calculation. To be more specific, the weighting can be adjusted by changing or altering the 1x value on each individual metric.
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Creating an Adoption Dashboard from Scratch
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Click Advanced Configuration and select Indicator from the dropdown menu. On the right select Gauge and click the coloured box in Values to adjust the colour coding.
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Click the + icon in Secondary, and add the formula (which represents the total number of downtime hours without a reason)
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The steps above can be repeated to generate other adoption metrics widgets.
Variants of Formulas
There are certain nuances behind the formulas for the metrics Comments Usage and Scrap Usage.
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To be more specific, both of the metrics have two formulas: ____ and ____ (Detail)
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TWhen pivoting by your data by day, it is highly recommended to be using the Detail version of the formula, whereas in any other scope of time, the regular formula will suffice.
For example, in the chart analyzing the last 7 days of data, we leverage the Detailed variants, as seen below:
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Whereas when analyzing at a larger scope of time, such as months, we leverage the base variants. This can be seen below:
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