Digital Financial Reporting

These two videos help you get your head around hypercubes:

• Contrasting Hypercube Structures (more information)
• Structure Representation Strategy (more information)

Happy hypercubing!

The following provides a summary of the different strategies for representing a structure within an XBRL taxonomy. For a video walkthrough of these, please watch Structure Representation Strategy.

• Approach 1: Hypercube as Unique Identifier - Using this approach each structure is identified by a unique hypercube and therefore every structure can be identified.  Given that each representation of a disclosure within a base taxonomy is an undisputed example of the disclosure, the disclosure mechanics specification can be reverse-engineered by software and are therefore unnecessary.
• Approach 2: Network as Unique Identifier - Using this approach each structure has a hypercube of exactly the same name which forces identification of the disclosure onto the network identifier which is guaranteed to always be unique.  If it is the case that the network identifiers of the base taxonomy are used in reports; then approach 2 works just like approach 1. Assuming that each representation of a disclosure within a base taxonomy is an undisputed example of the disclosure, the disclosure mechanics specification can be reverse-engineered by software and are therefore unnecessary.
• Approach 3:  Disclosure Specification as Prototype - Using this approach, neither a hypercube nor network can reliably be guaranteed to be unique and therefore cannot be relied upon to identify disclosure. However, disclosure mechanics rules are provided that do specify an undisputed example of the disclosure and a named list of disclosures has been created either as part of or independent of the base taxonomy.  As a result, every disclosure can be identified and verified to be consistent with the specification of the disclosure, even without unique identifiers.
• Approach 4: Hypercube as Unique Identifier Plus Disclosure Specification of Prototype - Using this approach, essentially approach #1 and approach #3 are combined.  Both unique hypercubes are provided plus disclosure mechanic rules that (a) refer to the unique hypercube as part of identifying the disclosure.
• Approach 5: Network as Unique Identifier Plus Disclosure Specification of Prototype - Using this approach, essentially approach #2 and approach #3 are combined.  Both unique network identifiers are provided plus disclosure mechanics rules.
• Pathological Example: No Unique Hypercube, No Unique Network, No Disclosure Mechanics Rules, No Named Disclosure - This is a pathological example provided for contrast.  In this case there are no unique hypercubes that can be used to identify structures, no unique networks (you have to imagine this, similar to XBRL-based reports submitted to the SEC), no specification for how disclosures should be structured, and no named disclosures.  Essentially, this cannot work reliably.

For more detailed information, please refer to the document Hypercubes, section 3 Structure Representation Strategy.  Also, take the time to look at the XBRL in the tool of your choice. This video Contrasting Hypercube Structures is also helpful if you want to better understand hypercubes.  You can download those examples here or view them online here.

XBRL-based digital financial reporting will, in my personal opinion, have a cross over affect on general business reporting and in particular business intelligence software.

The video, Digital Business Reporting, summarizes this information.  Business intelligence software is explained to be the following per this web site:

Business intelligence software is a set of tools used by companies to retrieve, analyze, and transform data into useful business insights. Examples of business intelligence tools include data visualization, data warehousing, dashboards, and reporting. In contrast to competitive intelligence, business intelligence software pulls from internal data that the business produces, rather than from outside sources.

Here is an overview of the top BI tools.  One thing BI tools have in common is the data warehouse and OLAP.  Here are some issues with OLAP that I have pointed out in the past.  Here is a summary of those issues; watch the video and I explain the enhancements provided by XBRL+ SBRM: 

My deliberate, rigorous, methodical testing of XBRL and SBRM for financial reporting leads me to believe that the ideas I am using for XBRL-based financial reporting will work well for digital business reporting.  Not quite as good as for financial reporting because of the higher level models of financial reporting; but it will still work well.

What is becoming crystal clear is the following.  XBRL+SBRM is a knowledge media that:

• Enables standards setter, regulator, or enterprise to describe and specify information about some reporting scheme in machine readable form
• Enables information bearer to produce information consistent with that provided specification that is machine readable.
• Enables information receiver or consumer to effectively consume information leveraging that provided specification using automated machine-based processes.

The rules provided by XBRL + SBRM (i.e. that specification) are the “orchestra leader” that enables the harmony (i.e. mitigates disharmony) and prevents anarchy (i.e. enabling effective information exchange).

Testing proves this.