question-framing

Skill: Question Framing

Purpose

Structure analytical questions using the Question Ladder framework so every analysis starts with a clear decision context, measurable success criteria, and testable hypotheses.

When to Use

Apply this skill when starting any new analysis, when a user asks a vague question ("How are we doing?"), or when an analysis request lacks decision context. Always frame before analyzing.

Instructions

Pre-flight: Load Learnings

Before executing, check .knowledge/learnings/index.md for relevant entries:

• Read the file. If it doesn't exist or is empty, skip silently.
• Scan for entries under "Question Framing" and "General" headings (or related categories like "Business Context", "Methodology Notes").
• If entries exist, incorporate them as constraints or context for this execution.
• Never block execution if learnings are unavailable.

The Question Ladder

Every analytical question climbs four rungs:

GOAL        → What business outcome are we trying to achieve?
DECISION    → What specific decision will this analysis inform?
METRIC      → What will we measure to inform that decision?
HYPOTHESIS  → What do we expect to find, and why?

The rule: Never start analyzing data until you can state all four rungs. If the requester only gives you a goal ("improve retention"), your first job is to climb the ladder before touching data.

Framing Process

Step 1: Extract the decision Ask: "What will you DO differently based on the answer?"

• If the answer is "nothing" or "I'm just curious" → this is reporting, not analysis. Offer two paths:
  • Path A: Quick stat/dashboard (if truly no decision)
  • Path B: Clarify decision context first, then frame properly
• If the answer is a specific action → you have a decision. Proceed to Step 2.

Step 2: Define success criteria Ask: "How will you know the analysis answered your question?"

• The answer should be specific: "If conversion rate dropped >10% in segment X, we'll prioritize a fix"
• Not vague: "We'll understand our users better"
• Success criteria should include specific thresholds, conditions, or decision rules