- Create a cross table
**Profit per Product Hierarchy by Customer Country**. - Add a new calculated measure
**Segment %**that calculates each Product/Customer Country combination as a percentage of the grand total profit. - Instead of referring to all columns or all rows on a certain level it will often be relevant to refer to a single column or row at the 'All' level:

**sum(0, 0, m1) / sum(all, all, m1) -> sum(0, 0, m1) / sum(all, d-1(l0), m1)**

Another example of the level parameter being useful can be observed in the simple trend calculation, where the level parameter can make a calculation robust in case of hierarchy expansion.

- Add a crosstab –
**Profit**per**Product Hierarchy (Product Group)**and by**Time Hierarchy (Year).** - Calculate a difference between the last 2 columns:
**Trend = sum(d-1, 0, m1) – sum(d-2, 0, m1**)

This calculation always **calculates the 2 last columns** – if the hierarchy is expanded the calculation will calculate the 2 last columns at the expanded level – as shown below:

Not expanded:

Partially expanded (now the Trend calculation calculates the difference between Q4 and Q3 in 2015):

This could be the intention – and in that case there is no problem, but if you want to make the calculation robust to expansion of the hierarchy you can use the level parameter.

**Trend = sum(d-1(l1), 0, m1) – sum(d-2(l1), 0, m1)**

As **level 1** in this case specifies the **year level** the calculation is now **robust to expansion**.

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