Find the focus, make your work clear.

Find a method for your next update. Make the facts, judgments and next steps clear.

How can categories help you understand a data set?

The situation

Fictional scenario

Tickets and overtime both increased. Can I say tickets caused the overtime?

First distinguish association, composition and grouping by similarity. Moving together does not prove causation.

I’ll check paired records and describe composition and groups separately, without letting a connecting line imply a conclusion.

What is getting in the way

The relationships answer different questions: what varies together, what makes up a whole, and which objects resemble one another. They are alternatives, not steps or automatic causal explanations.

Method and tool

Distinguish three kinds of relationship

Choose the relationship before the evidence and visual. Association needs paired observations, composition needs a defined whole, and clustering needs stated features and rules.

The method at a glance

Distinguish three kinds of relationship

Concept sketches, not measured data or computed results; these relationships can apply separately.

Association

Examine how two variables vary across paired observations and retain alternative explanations; association is not causation.

Composition

Identify parts and their whole; shares require mutually exclusive categories covering the same complete total.

Clustering

Identify similar objects using explicit features and grouping rules; similarity groups are not laws or proof of causes.

bizthinkframe.com

Apply it to your own work

Copy the prompt and add your material to prepare a draft you can adapt.

View prompt

Use “Distinguish three kinds of relationship” with only my material.
Identify applicable relationships and evidence requirements. Do not invent paired records, clusters or causal links from totals.

Check this structure:
1. Association: Examine how two variables vary across paired observations and retain alternative explanations; association is not causation.
2. Composition: Identify parts and their whole; shares require mutually exclusive categories covering the same complete total.
3. Clustering: Identify similar objects using explicit features and grouping rules; similarity groups are not laws or proof of causes.

Separate facts, judgments, proposals and approvals. Mark missing information “To confirm”. Do not invent numbers, causes, owners, dates or agreement. Retain periods, units, denominators, scope and evidence gaps. The fictional example is not my evidence. End with up to three priority questions to verify.

My material:
[Paste records, goals, constraints and the response needed, with sensitive information removed.]