The Seattle Method
Financial reports are knowledge graphs of the logic conveyed by the information within the financial report. A problem arises when a knowledge graph of a financial report is less capable masquerades as more capable or fully capable knowledge graph of meaning. The Seattle Method provides guidance.
The Seattle Method is a proven, good practices, standards-based pragmatic approach to creating provably high quality XBRL-based general purpose digital financial reports when reporting entities are permitted to modify the report model.
Financial reports are knowledge graphs. In the past, these knowledge graphs have only been readable by humans. Now, using the XBRL global standard, the knowledge graphs can be readable by both humans and machines: financial reports are machine-readable global standard knowledge graphs of XBRL-based information. The only way this “machine-readable financial report” thing can work is if such reports are trustworthy, interpretable, explainable, and the origin or provenance of provided information is known (i.e. WHY you can trust, WHAT are the facts, HOW are you interpreting, WHERE did you get the information you are using, WHO stands behind that information). The knowledge graphs must be of the professional level and provably of high quality.
Effectively, the Seattle Method provides a fixed method for representing (i.e. modeling) financial accounting, reporting, auditing, and analysis experience and information in machine readable form. It starts with terms, sets of relationships, sets of rules that govern the relationships, other rules that describe what is permitted, and how to represent facts within this scheme so that information is understandable to machine-based processes. You can think of the Seattle Method as a patterns language with exactly the appropriate level of flexibility in exactly the right areas such that things represented using that pattern language are always "computable" because the foundational "container" of relationships, rules, and facts never change. They are just patterns entirely known and understood by the method. As such, software can be used to effectively reason over the structures, associations, rules, and facts represented within different models because the sense-making machinery that is "baked-in" to the capabilities of the Seattle Method pattern language. The "fixed" way of defining the patterns provides us with this consistently useful method for defining or exploring complex information logic that always exists within the "guardrails" or "bumpers" provided by definitions of what is permitted and what is not permitted by, say, some specific financial reporting scheme represented using this approach. (To best understand this paradigm, please be sure you are familiar with the Essence of Accounting.)
The Seattle Method is an approach to controlling and managing flexibility; keeping report model modifications within permitted boundaries.
The Seattle Method provides accountants the freedom and responsibility within a strict framework of a highly developed system of XBRL-based digital financial reporting. The framework offers what can be thought of as “guardrails” or “bumpers” that help steer accountants toward high-quality machine-readable financial reports. Software applications can leverage this framework to create software which is easy for accountants to use and increases financial report quality.
The focus of the Seattle Method is financial reporting using financial reporting schemes such as US GAAP, IFRS, UK GAAP, and other schemes where the preparer of a financial report is permitted to modify the report model. Because modification of the report model is allowed per these sorts of financial reporting schemes, those reporting entity modifications must be controlled to keep the modifications within permitted boundaries.
As pointed out by the paper Critical Reflection on XBRL: A “Customisable Standard” for Financial Reporting? there are two general approaches to reporting: standardized and customized. There are trade offs between the two approaches in terms of comparability of information, the potential loss of idiosyncratic detail, and report quality. The paper provides a graphic which I took some liberties to modify, coming up with this graphic:
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