Risk and options / Delivery leads, planning owners and acceptance reviewers

Decision ledger

Keep severity and frequency distinct in review

Avoid letting a frequent minor issue hide a less frequent unacceptable condition.

This separates empirical occurrence counts from nonnumeric consequence labels rather than calculating an acceptance preference average.

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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

Minor issues occur in 4/5 of this log; required-output loss occurs in 1/5. These are descriptive case counts. A category name is not a numerical loss unit, so averaging category codes would not supply an expected loss.

The bounded result

Report occurrence counts and consequence categories separately: four minor issues and one required-output loss. The majority category cannot describe the consequence of the fifth case.

01 · Inspect the inputs

Every record stays visible

Inspect the invented case records
Rehearsal case	Observed issue	Consequence category
A	Copy typo	Minor correction
B	Copy typo	Minor correction
C	Copy typo	Minor correction
D	Copy typo	Minor correction
E	Required output absent	Required outcome lost

Use horizontal scrolling for wide tables. These records are invented, not customer data.

Records · CSV Complete case · JSON Manual brief · Markdown

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.

Original worked-case definitions
Definitions, policy choices, records and calculations are authored for this worksheet. No external standard, statistical validation or live product measurement is claimed.

External references checked 6 October 2026. Demand for these topics has not been measured.

Keep the reason with the decision

Illustrative decision record

Synthetic planning case: A five-case rehearsal records four minor copy issues and one loss of a required output. A report says most issues were minor and therefore the consequence picture is minor.

Decision 01

Minor correction count

Rationale and evidence: Four logged cases
Revisit condition: Descriptive frequency only

Decision 02

Required-output loss

Rationale and evidence: One separate case
Revisit condition: Retain its different consequence

Decision 03

Category coding

Rationale and evidence: Names, not common loss units
Revisit condition: Do not average invented numerical codes

Decision to make: Report occurrence counts and consequence categories separately: four minor issues and one required-output loss. The majority category cannot describe the consequence of the fifth case.

Keep the case-level consequences

Owner role · Recorder

Evidence: Case E stays visible alongside the four minor corrections.

Use meaningful units

Owner role · Risk reviewer

Evidence: No arithmetic is performed on arbitrary minor/major category codes.

Choose the consequence-specific response

Owner role · Receiving owner

Evidence: The required-output case gets its own recovery decision under the actual brief.

Filled manual planning note

Invented planning text. Adapt it to your evidence and confirmed owners.

Report occurrence counts and consequence categories separately: four minor issues and one required-output loss. The majority category cannot describe the consequence of the fifth case. Minor issues occur in 4/5 of this log; required-output loss occurs in 1/5. These are descriptive case counts. A category name is not a numerical loss unit, so averaging category codes would not supply an expected loss. Consequence categories are supplied local descriptions, not a universal severity scale or assurance standard.

Put the outline to work

Keep the case-level consequences. Check: Case E stays visible alongside the four minor corrections.
Use meaningful units. Check: No arithmetic is performed on arbitrary minor/major category codes.
Choose the consequence-specific response. Check: The required-output case gets its own recovery decision under the actual brief.

Questions about this workflow

Does one serious case predict future frequency?

No. These five invented observations do not estimate a population rate.

Can consequences ever be quantified?

Yes with justified comparable units and assumptions; arbitrary category numbers are insufficient.

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.

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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