In QPR Metrics, you can arrange elements hierarchically.
You can think of the top elements as being large compilation elements themselves. When you create a new scorecard, there is always one top element at the top of the element hierarchy that is created by default. You can use top elements to draw together data from sub-elements below them. For instance, the top element can be specified to compile all the elements in that scorecard. This element gives you an overview of your scorecard's general status.
Compilation elements compile element data from elements under them. They can be used to get an overview of the situation in a specific area. For more information on entering data into compilation elements, see Compilation Element.
Sub-elements are elements that have another element above them. Sub-elements use data that you have entered or imported into them or, if they also have other elements below them, sub-elements can act as compilation elements and sub-elements at the same time. For more information about entering data, see Defining Data for Sub-elements.
Comparing Measurement Data
Another important feature of QPR Metrics is that you can easily compare and compile data from different measurements by normalizing the data. With QPR Metrics, you can easily normalize different measurements by using value settings and ranges. This means that not only is it possible to compare data measured in different measurement units, but you can also compile the elements into a compilation element. Finally, by using the same value settings, you can also compare and compile measurements across different scorecards.
When the sub-elements are using a different measurement unit, the compilation element does not calculate a result directly, but uses representative range values instead.
For example, if you want to compare and compile data from two different elements (net sales in dollars and lead time in days), you can easily do this by using value settings.