Absolute contributions 1,1 and 4 give MAE two days.
Forecast evaluation / Delivery leads, planning owners and acceptance reviewers
Before / afterCompare absolute and squared forecast errors
Show how one large miss changes two explicitly defined evaluation measures.
The artifact exposes how one large miss changes two explicitly defined error summaries.
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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
MAE=(1+1+4)/3=2 days. RMSE=√((1+1+16)/3)=√6≈2.45 days. Units return to days after taking the square root.
The bounded result
The invented sample has a two-day MAE and approximately 2.45-day RMSE. The squared-error measure gives the four-day miss more influence; neither number selects a universal objective.
01 · Inspect the inputs
Every record stays visible
| Case | Forecast days | Actual days | Absolute error | Squared error |
|---|---|---|---|---|
| A | 2 | 3 | 1 | 1 |
| B | 2 | 3 | 1 | 1 |
| C | 2 | 6 | 4 | 16 |
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.
Compare the decision quality
Illustrative before / afterSynthetic planning case: Three duration forecasts are two days each. The observed toy outcomes are three, three and six days, giving errors one, one and four.
Squared contributions 1,1 and 16 give RMSE√6 days; the objective changes the influence of case C.
Match units and outcomes
Owner role · Evaluation owner
Evidence: All three errors describe the same duration target in days.
Calculate both declared summaries
Owner role · Reviewer
Evidence: Absolute and squared contributions retain the large case-C miss.
Choose the decision objective
Owner role · Planning lead
Evidence: The preferred loss rule is discussed in relation to actual consequences, not selected because its number looks lower.
Decision to make: The invented sample has a two-day MAE and approximately 2.45-day RMSE. The squared-error measure gives the four-day miss more influence; neither number selects a universal objective.
Filled manual planning note
Invented planning text. Adapt it to your evidence and confirmed owners.
The invented sample has a two-day MAE and approximately 2.45-day RMSE. The squared-error measure gives the four-day miss more influence; neither number selects a universal objective. MAE=(1+1+4)/3=2 days. RMSE=√((1+1+16)/3)=√6≈2.45 days. Units return to days after taking the square root. This tiny synthetic set is not a model comparison study. The rule and affected decision must be justified separately.
Put the outline to work
- Match units and outcomes. Check: All three errors describe the same duration target in days.
- Calculate both declared summaries. Check: Absolute and squared contributions retain the large case-C miss.
- Choose the decision objective. Check: The preferred loss rule is discussed in relation to actual consequences, not selected because its number looks lower.
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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Questions about this workflow
Can I directly compare an MAE number with RMSE to pick a model?
They summarize different loss rules; compare models under the same declared objective and compatible cases.
Why is the squared-error column in days squared?
Squaring a duration changes units; RMSE takes a square root and returns to days.
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.