An illustrative example of how IBCS® / ISO 24896:2026 visualisation, analytical structure and composition shape decision-ready financial reporting Contractor costs are forecast to exceed budget by NZD 1.20m, the largest undesirable variance in the operating result. Should management tighten contractor spending? The accounting view points strongly in that
How analysis accumulates into analytical memory Earlier in my career, I supported commercial decision-making in a large global technology business. Some of the most demanding work took place in bid and pricing review meetings, where decisions had to be made while important information was still emerging. The meetings deliberately
Reconciling financial-modelling notation with ISO 24896 and IBCS 2.0 to improve clarity, consistency and auditability What a financial model communicates A financial model communicates two related things. Model mechanics explain how the model works – which values are entered, which are calculated, how information moves between schedules, where calculation
Why performance analysis must infer the structure that modelling formalises? A financial model begins with stated premises. It identifies relevant drivers, specifies the conditions in which they operate, defines how they combine and calculates the resulting outcomes. Performance analysis usually begins with much less. The outcome is visible – revenue is
These propositions emerged while preparing a recent presentation on analysis, reporting, performance management, and governance. They reflect my current thinking on how organisations create understanding, action, and learning. 1. Excessive explanation may be a symptom of weak analytical structure. 2. Partitioning information is often mistaken for causal analysis. 3. Explicit
True understanding does not arise merely from orderly explanation or even architectonic arrangement, but from grasping structure in its unity.
The Clarity Series is a set of six essays on decision support in organisations, treated not as tooling or technique, but as a system of meaning, reasoning, and action. The series begins from an observation: many reports and analyses are numerically correct and professionally presented, yet still fail to support
This glossary defines how key terms are used across the Clarity Series. Where everyday meanings differ, the series meaning takes precedence. Definitions are deliberate and constrained to stabilise meaning across articles and applications. Clarity The condition in which meaning, reasoning, and implications can be inspected reliably – not merely received or
Data visualisation is not decoration – it is the interface through which structural analysis becomes inspectable. This essay shows why analytical-looking charts are not enough, how IBCS preserves meaning, and what happens when visuals drift into narrative instead of examination.
Many analyses explain results convincingly yet fail to guide decisions. This article examines why analytical failure is often structural rather than technical, and sets out the conditions under which analysis becomes a durable system for reasoning about change, not just explaining results.
Clarity in performance reporting is not a presentation problem. It is a design problem. When analytical structure, performance management, and governance are left implicit, reporting stabilises around compliance and narrative – not understanding, action, or learning.
Why management reports keep growing longer yet feel no clearer. This article explains why narrative explanation dominates, why it cannot create clarity, and how inspectable structural analysis reduces the need for explanation altogether.
clarity
Clarity in financial analysis is not created by storytelling or polished slides. It is created upstream through disciplined structural analysis that makes drivers, assumptions, and causality visible. When understanding depends on narrative, the problem is structure.
clarity
Clarity is achieved when structure is sufficient and explanation becomes optional.
analytical communication
High-density visualisation is often misunderstood. This article explains why common fixes fail and what actually improves clarity.
data visualisation
Choosing the right axis baseline defines how meaning is encoded in a chart. This piece explains when baselines must be zero, when they follow a benchmark, and why shifting them distorts truthfulness.
data visualisation
Colour in data visualisation is not decoration – it is meaning. This article explores why colour should support understanding rather than aesthetics or corporate branding.