Those of us who have been around the business intelligence (BI) space for a while will be familiar with the old mantra – ‘one version of the truth’. What this primarily refers to is the problem of data consistency when storing data in the mess of separate spreadsheet files used for managing analysis and reporting in most businesses. One version of the truth means using a database for storing the BI data (in so-called ‘fact’ tables) and then sitting the spreadsheets (or spreadsheet-like report views) on top of this single server-based data repository for data presentation and manipulation at the desktop. Pretty simple concept. So what’s this got to do with XBRL taxonomies?
Even when data is retrieved in a spreadsheet from a conventional relational database you still can’t be sure that a specific piece of data stored in a specific table column actually means the same thing or even easily figure out what the data is supposed to mean. That’s why storing ‘tagged’ data, subject to a mutually agreed taxonomy – either within an organization or between co-operating businesses or as mandated by a regulator – helps to ensure not just one version of the truth but one definition of the truth. The database is storing not just numbers that are retrieved by the spreadsheet for presentation and manipulation but also what you have mutually agreed the numbers mean.
You can still label the numbers wrongly in the spreadsheet and you can still manipulate the numbers in the spreadsheet to give a false impression. But ultimately, when you drill down from the spreadsheet to the underlying data, the XBRL tags will tell you what that data actually should mean, making discrepancies harder to hide. So if you are a Sarbanes-Oxley 404 auditor looking for evidence of lack of controls over data integrity or fraud in financial reports and spreadsheets, One Definition of the Truth is going to help you a lot.
xbrl-truth
Tags: spreadsheet
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