What would be the best approach to analyse accounting data for the Newcomb-Benford’s Law?
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It will of course vary by process area and use case, but here is an example of something you could try for O2C data models:
- Create an OLAP Table and use the LEFT() function to create your dimension as the leading digit of the sales document line item dollar amount (the table/field I usually use is VBAP.NETWR_CONVERTED). PQL Code: LEFT(VBAP.NETWR_CONVERTED || '', 1). Note: Notice that I concatenated an empty string to the dollar amount field by adding "|| ''" to the end. This is required because the LEFT() function only works on Strings and there is no explicit conversion for a float to a string in Celonis PQL. Therefore, we have to do an Implicit Conversion by appending an blank string on the end.
- In the KPI section of your OLAP table, simply do a COUNT_TABLE(VBAP) to get the count of the occurrence of each number.
- Sort the COUNT_TABLE(VBAP) in descending order and the numbers should flow from 1-9 accordingly.
- OPTIONAL: You could now convert your OLAP to a bar chart to more clearly see the distribution of numbers in columnar format.
Hope this helps.
Interesting use case / question, also perhaps you might want to look using Celonis ML https://youtu.be/FJoE2Dbi7Dw
Keep us posted with your finding!
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