Define actual action consequences
Owner role · Decision owner
Evidence: The four-to-one loss convention and zero correct-decision loss are declared.
Forecast evaluation / Delivery leads, planning owners and acceptance reviewers
Decision deskInspect a forecast decision with asymmetric mistake costs
Compare the supplied losses of overcommitting and waiting before using a probability threshold.
This links a binary decision threshold to asymmetric declared mistake costs, distinct from accuracy or probability-error scoring.
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Original worked case · Manual planning resource
Inspect the decision, not just the summary.
Start with the invented evidence, follow the reasoning, and retain its limits when adapting the brief.
02 · Follow the reasoning
How the case leads to a decision
Commit loss=4(1−p); wait loss=p. They tie when 4−4p=p, so p=0.8. This threshold follows the toy losses and supplied probability, not a universal readiness policy.
The bounded result
Under these hypothetical inputs, committing has expected loss 1.6 points and waiting 0.6, so the declared loss rule favors waiting. A majority probability alone does not choose the action.
01 · Inspect the inputs
Every record stays visible
| Action | Mistake probability under supplied p | Loss if mistaken | Expected loss |
|---|---|---|---|
| Commit | 1−0.6=0.4 | 4 points | 1.6 |
| Wait | 0.6 | 1 point | 0.6 |
Use horizontal scrolling for wide tables. These records are invented, not customer data.
Definitions and method context
Records, decisions and policies are original synthetic examples. External references supply context; they do not validate these cases or TeamBoostAI capabilities.
Forecasting: Principles and Practice — accuracy ↗
Genuine held-out forecast and point-error evaluation context. Binary scoring examples use their own explicit toy definitions; no real task model is validated.
External references checked 6 October 2026. Demand for these topics has not been measured.
Decision desk
Decide before adding more work
Decision to make: Under these hypothetical inputs, committing has expected loss 1.6 points and waiting 0.6, so the declared loss rule favors waiting. A majority probability alone does not choose the action.
Synthetic planning case: A toy decision can commit or wait. Its supplied readiness probability is 0.6. A false commitment costs four declared loss points; waiting when ready costs one. Correct decisions cost zero.
Inspect the conditional comparison
Owner role · Reviewer
Evidence: At supplied p0.6,1.6 exceeds 0.6 expected loss points.
Check evidence before real use
Owner role · Planning lead
Evidence: Actual probabilities, authority and consequences need independent justification before any commitment.
Filled manual planning note
Invented planning text. Adapt it to your evidence and confirmed owners.
Under these hypothetical inputs, committing has expected loss 1.6 points and waiting 0.6, so the declared loss rule favors waiting. A majority probability alone does not choose the action. Commit loss=4(1−p); wait loss=p. They tie when 4−4p=p, so p=0.8. This threshold follows the toy losses and supplied probability, not a universal readiness policy. Loss points are local toy preferences, not money, measured harm or a legal/safety assurance. No live task probability is validated.
Questions about this workflow
Is 0.8 a recommended business threshold?
No. It is the algebraic result of this invented four-to-one loss rule.
Does the worksheet validate the supplied 0.6 probability?
No. It is a hypothetical input; a real decision needs justified probability and consequence evidence.
Does this create tasks in the product?
No. The brief is a manual planning resource. Use the product access link to check onboarding and the workflows available in your account.
Put the outline to work
- Define actual action consequences. Check: The four-to-one loss convention and zero correct-decision loss are declared.
- Inspect the conditional comparison. Check: At supplied p0.6,1.6 exceeds 0.6 expected loss points.
- Check evidence before real use. Check: Actual probabilities, authority and consequences need independent justification before any commitment.
From a useful outline to team work
Explore TeamBoostAI for your team
Use the owned checks and downloaded brief to discuss this planning decision alongside your TeamBoostAI tasks. Confirm available fields, roles and account features separately. The example is manual; it does not calculate live analytics, create work or run an experiment in the product. Confirm the workflows available in your account before adopting this outline.
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