XBRL 2.0

Digital financial reporting that actually works

XBRL DEEP DIVE: COCA COLA AND WORKIVA

A company of Coca Cola’s stature understands the value of high-quality investor communications. And Workiva understands that protecting its dominant market share requires software that facilitates creation of the XBRL files, protects the filer against errors and omissions and informs the process through its knowledge of relevant specifications, taxonomies, filing rules and the tagging practices of other companies. So when these two market leaders combined to produce Coca Cola’s latest 10Q, I expected both data quality and usability.

 

I got neither. The filing scored 66.0 on XBRLogic’s Quality Score, well below the already pedestrian average of 88.7 for all filings in Q4. Here’s what I saw.




By way of orientation, RED is BAD. In this case, it means that these items are missing important metadata – their relationship to other items in the statement. Important? Extremely. This is the fabric of the extended taxonomy model created to depict the company’s financial results. Without it, data validation is very difficult. Standardizing custom items (shown with the blue ‘x’) is very difficult. Ensuring that values have the correct sign is very difficult. Usability of this data becomes very difficult.

The SEC requires that these relationships are explicitly reported in XBRL filings in an XML file called the ‘calculation linkbase’. Most companies comply, but many do not. And it raises three obvious questions.

  • Why does Coca Cola think this is OK?
  • Why does Workiva’s software allow this important omission?
  • Why doesn’t the SEC enforce its filing requirements?

The second issue is subtler, but just as important. Coca Cola created four custom tags in this statement, marked on the previous image with a blue ‘x’. Custom tags, or extensions, are allowed by the SEC but undermine the data’s comparability. These 4 extensions are clearly unnecessary. Shown below, each line item has a matching concept in the standard taxonomy. 


To take one example, ‘Purchases of Investments’ was created as a custom tag.  Three proprietary mapping algorithms yielded a single standard tag. Two approaches were based on tags by other companies for exactly the same item in the first case and approximately the same in second. They’re shown below.