Jtbd Outcome Engineer

JTBD Desired Outcome Engineer

Turn "users want it faster and easier" into measurable, survey-ready research metrics.

Use this when

• You have a specific job map step and want to engineer precise performance metric statements.
• You have vague customer complaints ("too slow", "hard to use") and want to rewrite them into formulaic metrics.
• You are preparing an ODI quantitative survey and need standardized outcome statements.

Don't use this when

• You need to extract switching forces or non-consumption barriers (use jtbd-context-explorer or jtbd-forces-analyzer).
• You need to calculate mathematical Opportunity Scores from survey ratings (use jtbd-opportunity-calculator).
• You need to evaluate market growth strategies (use jtbd-growth-strategist).

Minimum input

• Minimum Input: Core Functional Job, Job Executor, and a single job_map_step (or a qualitative pain point statement). Supports three modes:
  1. Step-to-Outcome Mode: Generate outcomes for a job map step.
  2. Audit Mode: Audit an existing survey question for formulaic precision.
  3. Pain-Point Mode: Convert a broad complaint into candidate outcome statements.

What you get

1. Next Use Handoff: Qualitative questions for interview probes AND survey-ready questions for quantitative surveys.
2. Formulaic Desired Outcome Statements: Statements following [Direction] + [Metric] + [Target] + [Contextual Clarifier].
3. Metric Classification: Metric type tag (time, likelihood, effort, cost, output).

Quick prompt

"Formulate desired outcome metrics for this job step: '[Paste job map step statement]'."

What to do next

• Need qualitative interview probes? Use the next_use.qualitative questions in jtbd-switch-interview.
• Ready to collect quantitative data? Export next_use.quantitative items into an ODI survey, then pass ratings to jtbd-opportunity-calculator.

Outcome Statement Formula

Every Desired Outcome Statement MUST follow this exact structure:

$$\text{Desired Outcome} = \text{Direction} + \text{Metric Type} + \text{Measurement Target} + [\text{Contextual Clarifier}]$$

• Direction: Minimize (or Maximize when increasing capacity/yield).
• Metric Type: time | likelihood | effort | cost | output.
• Measurement Target: The precise action, event, error, or state being controlled. (Must be concrete and observable; avoid vague words like "error", "failure", "problem").
• Contextual Clarifier: Optional phrase specifying environmental or conditional boundaries.

Output Format

next_use:
  qualitative:
    - "Interview probe question for qualitative discovery"
  quantitative:
    - "Survey question item for 1-10 Importance/Satisfaction rating"

job_context:
  core_functional_job: ""
  job_executor: ""
  job_map_step:
    category: define | locate | prepare | confirm | execute | monitor | modify | conclude
    statement: ""

outcomes_status: provisional | validated

desired_outcomes:
  - id: ""
    statement: ""
    direction: minimize | maximize
    metric_type: time | likelihood | effort | cost | output
    measurement_target: ""
    contextual_clarifier: ""
    source_step:
      category: ""
      statement: ""
    status: evidence_supported | hypothesis
    basis: direct_evidence | domain_rationale
    evidence: []
    assumptions: []

excluded_items: []
evidence_gaps: []
next_research_question: ""

Reference

Read references/outcome-statement-rules.md before:

• Distinguishing metric types (time, likelihood, effort, cost, output)
• Enforcing concrete specificity on likelihood targets
• Stripping quality buzzwords ("easily", "reliably", "accurately")