Seattle Method

A model is an intentional abstraction of reality: a simplified, structured way of describing a system so people can understand it, communicate about it, and solve problems together. It is not the real-world thing itself, but a useful approximation that captures the essential elements, relationships, and patterns of a subject domain.  A model is an abstraction of reality according to a certain conceptualization . Modeling is the process of organizing information for community use in the form of a model.  The model provides a framework for human communication about the subject domain, a mechanism for explaining conclusions about the subject domain, an a mechanism for managing varying viewpoints within the subject domain. A map is one of the clearest examples of a model. You might have heard the phrase, "The map is not the territory."  The map is not the actual territory, but a map can be quite useful in navigating a territory. A map includes just enough information about t...

"Isn't it astonishing that all these secrets have been preserved for so many years just so we could discover them!!"  -- Orville Wright, June 7, 1903 Accounting, reporting, auditing, and analysis will go through a significant refactoring over the coming years.  This refactoring will transform the roles of accountants, auditors, and analysts from their current roles as "data janitors" into curators and stewards of knowledge and truth. Allow me to explain. The Legacy Paradigm: Systems Built Assuming Inconsistency For decades, accounting information systems assumed that data would be inconsistent. Errors were expected, and organizations compensated by building manual pipelines for checking, fixing, and reconciling information; a perpetual cycle of remediation. This approach produced two forms of fragmentation: Physical fragmentation : data scattered across spreadsheets, ledgers, platforms, and files  Semantic fragmentation : incompatible meanings, definitions, and ...

For decades, accounting information systems were not engineered to ensure that data remained consistent by design. In that paradigm, inconsistency is assumed. Errors inevitably enter the system, and organizations respond by building endless processes (a.k.a. pipelines) that allowed humans to manually check, fix, adjust, and reconcile. This mindset treats truth as something assembled after the fact, through labor‑intensive cleanup. It is a paradigm of perpetual remediation . This legacy mindset also produces physical fragmentation (data scattered across systems, files, electronic spreadsheets, ledgers, and platforms) and semantic fragmentation (incompatible meanings, definitions, and structures). Fragmentation has costs associated with it.  For example, once fragmented the traceability and provenance chain breaks. You cannot reliably follow a fact from its origin to its use. You cannot prove what is true; only reconcile what went wrong. Accounting & Audit by Design (A&AD)...

The Accounting & Audit by Design (A&AD) Framework is about freedom from drudgery for accountants, auditors, and analysts. It is about streamlining processes. A&AD is about eliminating the waste of time and energy that goes into transaction chasing. A&AD is about fixing processes that allow mistakes rather than spending time fixing mistakes a process allowed or dealing with the consequences of a mistake escaping from the system undetected. The following sections will help you understand what the Accounting & Audit by Design (A&AD) Framework is and what it enables. Environment What is A&AD? Why A&AD Now? How does A&AD Work? Business Outcome Fifty to seventy five year ago it would have been impossible to contemplate something like A&AD; it just was not feasible. We did the best we could to implement accounting information systems using computers and software that we had at the time.  That gave us the paradigm, the normal science per The Kuhn Cy...

A business model explains how a company makes money. A moat  is a defensive measure and explains why that business model keeps working even when competitors attack it. Without a moat, a business model is fragile. Without a business model, a moat is meaningless. Companies build moats in order to make their success hard to compete with, hard to imitate, and hard to erode over time. A strong moat lets them keep customers, maintain pricing power, and generate durable profits. One type of moat is knowledge . But knowledge only becomes a moat when the knowledge is encoded. Raw expertise is not defensible. Encoded expertise is. Knowledge is encoded when it is turned into metadata, rules, theories, ontologies, taxonomies, schemas, governance frameworks, process automation logic algorithms. When knowledge becomes machine‑readable, enforceable, and extremely hard to replicate you create a moat that artificial intelligence cannot erode. Knowledge can be organized within a knowledge org...

PWC and Anthropic announced their partnering to create what they are referring to as the Office of the CFO; see  Anthropic and PwC Expand Alliance, Driving Impact Across Client Work and the Firm , and my commentary here . PWC and Microsoft announced their partnering to collaborate strategically to transform industries using AI,  PwC and Microsoft announce strategic collaboration to transform industries with AI agents .  EY and Microsoft announce partnership to help clients scale AI,  EY and Microsoft announce global initiative to help clients scale AI enterprisewide value creation and move beyond experimentation . What they have is effectively a platforms to do consulting to large organizations in the financial services, insurance, pharma, healthcare industries and other industries. What I am wondering is if there is an appetite for a similar offering targeted at small and medium size enterprise, but could be used by anyone.  Something that is modular, based on ...