Standardized metrics are measures created by data vendors to make company reported data comparable across companies. The need for standardized metrics existed long before XBRL because the variation in the way companies report essentially the same information existed since companies started to report data. As most of the data in Calcbench comes from XBRL based data, our examples are focused on XBRL.
When companies report financial information they tag that information using an XBRL tag and add a label to it as well. There is a great variation in the way companies can tag and label information. When choosing XBRL tags, companies can choose a tag from a list created by FASB (the FASB XRBL taxonomy) or create a unique tag (typically referred to as an extension, because it extends the taxonomy).
For example, let's take revenue, IBM labels revenue as "Total revenue" and uses the tag "Revenues", whereas Apple, labels their revenue as "Net sales" and uses the tag "SalesRevenueNet". This is a relatively simple case, because both companies used tags from the FASB taxonomy.
Users are typically not interested in the subtle differences of how companies tag or label information. In the previous example, most users would want Apple and IBM's revenue, regardless of how it was tagged. To that end, we create standardized metrics.
The standardized metrics are metrics created by Calcbench to include a certain type of information regardless of how it was tagged. Following the same example as before, Calcbench's metric "Revenue" would include IBM's revenue (reported as Revenues) and Apple's revenue (reported as SalesRevenueNet). Calcbench essentially maps a set of taxonomy tags and extensions to common data elements. Note that in some cases, the standardized metrics may be a combination of several pieces of data.
Do not forget that you can always use the trace function to trace the standardized metric back to the source, so you can see how the data was originally tagged or how the metric was calculated.
0 Comments