Hi Bruno, I can see your point, that this would help for some analyses. We will take a look if that is actually possible. Do you have a concrete example of an analysis where you came across this? Clear context of the use-case always helps us to find a better solution. What KPI did you create in what context? So why did you use the PU function in the first place and what did you want to achieve with the analysis? Best Regards, Manuel

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Hi Manuel, There are several examples of analysis where this would be helpful. Below you can find one of them: Data model:

1. Customers
2. Sales Orders
3. Deliveries

Cardinality Customers (1:N) Sales Orders Sales Orders (1:N) Deliveries Now imagine you want to offer, in the same table, a list of customers (as a dimension) and two KPIs (e.g. sum of sales orders amount and a counter of the total number of deliveries). Using the aggregation functions SUM(Sales Orders.Amount) and COUNT_TABLE(Deliveries) for the KPI calculation, only the last one would have the expected value, as it is based on the broader table. image.png981350 22.1 KB A solution for that would be to use a PU_FUNCTION for the KPI on the Sales Orders table image.png1014364 22.8 KB However, as soon as you apply a selection filter on the Sales Orders or Deliveries table, and as they are not considered in the PU_FUNCTION, the result wont change accordingly to the filters. image.png1036426 18.1 KB As I said, sometimes it is useful, but in many other cases it is not. I hope you can offer the developers an option to either consider or not the current filters when using PU_FUNCTIONS. Regards, Bruno

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Hi, Has this been reviewed any further? We are having a similar problem when calculating automation rates for customers on our sales order model. We want to contrast automation rates by sales order volume, value and customer volume. Because customers may have some orders that are automated and some that are not, we need to first classify a customer as automated or not using an automation threshold. To do this I have a pull up function to KNA1 to calculate this: COUNT (DISTINCT ( CASE WHEN (PU_COUNT_DISTINCT(KNA1, VBAK.VBELN, _CEL_C2C_ACTIVITIES.USER_TYPE != A AND _CEL_C2C_ACTIVITIES.ACTIVITY_EN = Create Sales Order Item)/ PU_COUNT_DISTINCT(KNA1, VBAK.VBELN, _CEL_C2C_ACTIVITIES.ACTIVITY_EN = Create Sales Order Item)) >= <%= customer_automation_threshold %> THEN KNA1.KUNNR ELSE NULL END ) ) However, when filters are applied to the overall analysis, the pull up function doesnt take into account the filters. So if I, for example, filter on sales order type, it may still show that the customer is considered to be automated even if there is no automation for the orders of the type in question. Any suggestions?

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Hi, Unfortunately not. Celonis customer service is, to be honest, quite poor. Best Regards, Bruno

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