#Measurement

Data Measurement as Organizational Protocol: Definitions, Measurement, Tiering, and Retrospectives

A research-design and protocol paper: reframing data measurement from what belongs on the dashboard into a recomputable, reviewable, decision-supporting collaboration protocol, with minimal mechanisms for definitions, measurement units, metric tiering, dictionaries, and retrospectives.

Data Measurement Guide (Part 4): The Metric Dictionary Template — Turning Definitions into a Recomputable Collaboration Interface

A ready-to-copy metric dictionary template, plus public examples for completion rate, retention, conversion, error, experience quality, and feedback metrics.

Part of the column “Data Metrics Guide” · Chapter 4

• #Data
• #Metrics
• #Collaboration

Data Measurement Guide (Part 3): Metric Tiers, Let Data Serve the Most Important Decisions First

Don't lay metrics flat on the dashboard: prioritize them by task relevance, scope of impact, actionability, and data trustworthiness, and choose what to watch at each stage.

Part of the column “Data Metrics Guide” · Chapter 3

• #Data
• #Metrics
• #Collaboration

Data Measurement Guide (Part 2): Define What You're Measuring Before Arguing About Metrics

A publicly reusable metric dictionary: from requests and users to tasks, explaining how availability, error, latency, performance, and feedback data should be defined, combined, and interpreted.

Part of the column “Data Metrics Guide” · Chapter 2

• #Data
• #Metrics
• #Measurement

Data Measurement Guide (Part 1): Data Definitions Are the Interface of Collaboration

Metrics are not numbers on a report; they are the shared language a team uses to describe the same thing. Only after defining the object, event, denominator, and time can data participate in decisions.

Part of the column “Data Metrics Guide” · Chapter 1

• #Data
• #Metrics
• #Collaboration