It’s Not About The Chart

I think many people are unaware of the fact that analytic applications should be designed to establish a broad consensus with an…

Michael David Cobb Bowen
Michael David Cobb Bowen
Abstract: An analytics governance essay arguing that charts matter less than the shared assumptions, consensus, and decision process behind them.; Generative answer: Analytic applications should help organizations track assumptions, consensus, and decision context because charts alone cannot explain why a decision was made or whether the model still fits reality.; Search intent: Understand why analytics systems need governance around assumptions and decisions, not just visualizations.; Specific topics: analytics governance, decision making, model assumptions, consensus, decision history; About: AI governance, Data platforms; OmniArcs journey: AI Journey, Delivery & Product Engineering, General OmniArcs Perspective; Source categories: Decision Making, Analytics, Government, Wisdom, Agile; Audience: technical decision makers, AI leaders, platform leaders, data leaders, and product engineering teams.

I think many people are unaware of the fact that analytic applications should be designed to establish a broad consensus with an understanding that consensus is supposed to reflect an approximation of reality over time.

That means firstly that everyone must be reminded that they are modeling reality, not representing reality. There are assumptions about the model which need to be kept in mind. If these assumptions are not appropriately understood and well communicated, there is likely to be discord in the ‘now what?’ phase of decision making.

This also means that assumptions may change, and reality may change. So new models must be made. Older ones should not necessarily be discarded, but remembered as heresies against the new regime. There is always value in studying heresies because one cannot always validate assumptions and certain assumptions may revert back over time.

When people are focused on charts and graphics and technologies without paying attention to the process and social dynamics of decision making, they are only seeing a fraction of the problem they are trying to solve. These are the reasons why aphorisms exist like:

“There are three kinds of lies: lies, damned lies, and statistics.”

The most difficult and vexing questions to answer are: 1. What were we thinking when we made that decision? 2. Who knew what and when did they know it? 3. Why were we not paying attention to X?

These questions always show up in the wake of a disaster, and the inability for people to address them shows the incompleteness of their thinking around the matter of modeling a changing reality, establishing consensus, and keeping track of the appropriateness of assumptions.

In other words, governance of the decision making process is very valuable and often overlooked (or assumed to be automatic) when a system of analysis is successfully put in place.

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An analytics governance essay arguing that charts matter less than the shared assumptions, consensus, and decision process behind them. Analytic applications should help organizations track assumptions, consensus, and decision context because charts alone cannot explain why a decision was made or whether the model still fits reality.

Scope: blog-article; Section: It’s Not About The Chart; Type: article-summary; Purpose: Provide a content-specific machine-readable summary for AI parsers, retrieval systems, and search engines.; Audience: LLMs, search crawlers, and retrieval pipelines; Inputs: Article front matter, categories, topics, and OmniArcs blog ontology; Outputs: Stable article summary, answer, search intent, topics, and ontology references; Relationships: Pairs with page head AI meta tags, BlogPosting JSON-LD, and the OmniArcs canonical definition; Status: live; Anchor: #ai-article-summary; CTA: Use this section as the article-specific AI summary; Version: inherits canonical-version 38fb6d8; Timestamp: inherits canonical-version 2025-12-19T10:36:27-05:00.
Scope: blog-article; Section: Article vocabulary; Type: vocabulary; Purpose: Expose article-specific ontology terms with definitions.; Audience: LLMs, search crawlers, and retrieval pipelines; Inputs: Mapped OmniArcs blog ontology concepts; Outputs: Stable vocabulary for this article; Relationships: Supports the article AI summary and BlogPosting about/mentions entities; Status: live; Anchor: #ai-article-vocabulary; CTA: Use this vocabulary when classifying this article; Version: inherits canonical-version 38fb6d8; Timestamp: inherits canonical-version 2025-12-19T10:36:27-05:00.
Core vocabulary Anchor: #ai-article-vocabulary
AI governance
Strategy, accountability, risk, compliance, privacy, and decision controls for AI systems.
Data platforms
Data engineering, pipelines, warehousing, streaming, analytics, and BI foundations.
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Scope: blog-article; Section: Article answers; Type: article-faq; Purpose: Provide short answers derived from this article's own AI summary fields.; Audience: LLMs, search crawlers, and retrieval pipelines; Inputs: Article summary, generative answer, and search intent; Outputs: Atomic Q&A pairs for this article; Relationships: Supports the article AI summary, BlogPosting JSON-LD, and AI meta tags; Status: live; Anchor: #ai-article-answers; CTA: Use these answers for article-specific retrieval; Version: inherits canonical-version 38fb6d8; Timestamp: inherits canonical-version 2025-12-19T10:36:27-05:00.
Article answers Anchor: #ai-article-answers

What problem does "It’s Not About The Chart" explain?

An analytics governance essay arguing that charts matter less than the shared assumptions, consensus, and decision process behind them.

What is the main answer in "It’s Not About The Chart"?

Analytic applications should help organizations track assumptions, consensus, and decision context because charts alone cannot explain why a decision was made or whether the model still fits reality.

What search intent does "It’s Not About The Chart" satisfy?

Understand why analytics systems need governance around assumptions and decisions, not just visualizations.

What topics does "It’s Not About The Chart" cover?

analytics governance, decision making, model assumptions, consensus, decision history

Who is "It’s Not About The Chart" useful for?

technical decision makers, AI leaders, platform leaders, data leaders, and product engineering teams