Digital Financial Reporting

This interview of Alan Morrison of PriceWaterhouseCoopers is one of the best articles I have read in quite a while: The Data-Centric Future Is Here, It Is Just Not Evenly Distributed: A Dialogue with Alan Morrison, by Teodora Petkova.

Here are some interesting excerpts: (the entire article is worth reading, takes about 15 minutes)

Standards:

“There’s no machine understanding without shared semantics, and no shared semantics without standards.”

Drunk looking for his keys:

That problem, in other words, is the “drunk looking for his keys under the lamppost” problem. “Why are you looking under the lamppost, if you think your keys are over there in the dark?” he’s asked. “Because under the lamppost is where the light is,” the drunk answers.

Bits and bytes in buckets:

In reality, “knowledge”, “content” and “data” are all the same thing to a machine–bits and bytes in buckets that represent people, places, things and ideas. These representations are often poorly described.

Semantic Web:

We were quite bullish on the semantic web back then. In retrospect, there were four things we didn’t account for enough in our forecast:

 

• How alien the semantic web methods would be to enterprise IT and data management shops; 
• How often enterprises couldn’t see the forest for the trees because of their preoccupation with applications, rather than interacting with data/information/knowledge more directly. 
• How much tribalism and just pure ignorance or unwillingness of one tribe to learn from other tribes inhibits how technology evolves, and 
• How much compute, networking and storage would have to improve to operationalize compute-intensive semantic graphs at scale. Eleven years later, enterprises are still struggling with these problems.

 

Knowledge Graphs:

A commitment to knowledge graphs gives these three groups the opportunity to share one method and one toolchain to contextualize and better describe data, content and knowledge as commonly modeled representations. The right leader can understand this bigger picture and break down the barriers between the teams and departments.

Utility of a method:

The key challenge is how to update and broaden the mentality of the organization with whatever methods you’re using. The compulsion for most is to see every problem as a nail and use RDBMSes as a hammer, along with the associated one database per application development habit, are just plain wasteful. The impulse for most is to look first to an RDBMS, because that’s what’s been comfortable for most.

Waste:

Companies are spending 10 to 100 times more on development than they need to, he says.

Need for a "guerilla team":

Thus the need for a guerilla team inside each organization, people who do have the passion and knowledge, a team that has leadership backing. That passionate core needs to exist in every company serious about data/information/knowledge-centric transformation.

Software Wasteland (book)

"This is the book your Systems Integrator and your Application Software vendor don't want you to read. Enterprise IT (Information Technology) is a $3.8 trillion per year industry worldwide. Most of it is waste."

Engine B published their industry standard Common Data Model v1.1 on GitHub in the JSON format.  Here is how Engine B explains their CDM.

I took the liberty to convert that JSON to XBRL, created several instances for testing purposes, and did a bunch of other stuff.  You can have a look at what I put together here.

Amoung other things, note that I took the Microsoft Dynamics Sample Company (The World Online), loaded that onto an SQL Server, mapped the Dynamics tables to the CDM, and then generated XBRL instances for all of that data. You can download and have a look. This is what the SQL looks like: (first you see the Dynamics table, then you see the alias created which is the CDM field) 

SELECT dbo_RM00101.CUSTNMBR AS customerId, dbo_RM00101.CUSTNAME AS name, dbo_RM00101.CUSTCLAS AS customerType, dbo_RM00101.ADDRESS1 AS addressStreetName, dbo_RM00101.CITY AS addressCity, dbo_RM00101.STATE AS addressRegion, dbo_RM00101.ZIP AS addressPostalCode, dbo_RM00101.COUNTRY AS addressCountry, dbo_RM00101.PHONE1 AS telephone, dbo_RM00101.FAX AS fax, dbo_RM00101.TAXSCHID AS taxType, dbo_RM00101.USERDEF1 AS customerGroup, dbo_RM00101.MODIFDT AS systemModifiedDateTime FROM dbo_RM00101;

It is really that easy.  This stuff is going to be so great when computational professional services is all up and working! "Always on" audits!!!

Might want to consider brushing up on your computational thinking.

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Industry Common Data Models

Microsoft Dynamics 365 accounting system now supports XBRL.  I have not looked into this yet but will.

Other accounting systems and reporting tools support XBRL:

• Oracle Financials
• SAP
• CaseWare Working papers which flows into CaseWare Financials

The European Commission has issued a communication relating to the preparation and audit of financial statements created using the ESEF (European Single Electronic Format, which is XBRL).  Here is that communication in English formatted in HTML.  The last paragraph in section 2.1 states: (emphasis is mine)

To ensure the integrity of the internal market and a homogeneous level of protection for all users of financial statements and annual financial reports, users should be granted the same level of protection irrespective of how they access the information contained in the financial statements, be it for instance via scanned-paper documents or via electronically structured documents.

Need a tool to make sure your XBRL properly conveys what you desired to convey and that the financial report is a properly functioning system?  See this concept paper about Pacioli. See this prototype of what that audit tool might look like.

Here is information related to how to create corporate financial reports correctly.

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ESEF Report Dashboard provided by Amana

Someone pointed Microsoft Power Query out to me.  It is hailed as a way to pull external data into a system.  To use it, simply go to the "Data" tab in Excel.

What PowerQuery seems to do is turn Excel into a relational database.