Scenario Planning Two-Axis Quadrant Builder
Assign scenarios to four caller-defined two-axis quadrants using explicit midpoint thresholds and return quadrant counts.
Description
A two-axis scenario grid separates combinations of high and low coordinates.
A two-axis scenario grid separates combinations of high and low coordinates. Explicit midpoints control quadrant membership.1
The returned values include Scenario quadrant assignments, Quadrant counts. The How section below explains the calculation, input rules and interpretation.
When to use Scenario Planning Two-Axis Quadrant Builder
Use Scenario Planning Two-Axis Quadrant Builder when you need to evaluate the supplied records under the calculation and evidence rules below. No axis selection, independence test or plausibility score is supplied.
Define the question, evidence and scenario assumptions first. Supply the chosen score scales, time horizons or reference selection explicitly. Interpret generated text as a discussion template and screen labels as the stated rules.
How to use Scenario Planning Two-Axis Quadrant Builder and understand its results
- Define the question, evidence and scenario assumptions first. Supply the chosen score scales, time horizons or reference selection explicitly. Interpret generated text as a discussion template and screen labels as the stated rules.
- Enter scenarioIds, xMidpoint, xValues, yMidpoint, yValues using the field table and calculation rules, then run the tool.
- Read assignments, quadrantCounts. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| scenarioIds | Scenario IDs | list of string | Required |
| xMidpoint | X midpoint | number | Required |
| xValues | X values | list of number | Required |
| yMidpoint | Y midpoint | number | Required |
| yValues | Y values | list of number | Required |
Require aligned nonempty scenario IDs/x/y values, finite coordinates/midpoints and trimmed nonblank IDs. Equality is high. Preserve duplicate IDs/order and return assignment strings plus counts Q1–Q4.
Q1=highX/highY; Q2=highX/lowY; Q3=lowX/highY; Q4=lowX/lowY Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| assignments | Scenario quadrant assignments | list of string |
| quadrantCounts | Quadrant counts | list of number |
{
"input": {
"scenarioIds": [
"Growth",
"Stability",
"Resilience"
],
"xMidpoint": 0,
"xValues": [
2,
-1,
0
],
"yMidpoint": 10,
"yValues": [
12,
8,
10
]
},
"output": {
"assignments": [
"Growth: Q1",
"Stability: Q4",
"Resilience: Q1"
],
"quadrantCounts": [
2,
0,
0,
1
]
}
}Limitations and assumptions
No axis selection, independence test or plausibility score is supplied.
Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Core numeric and string lists are limited to 100,000 entries; text entries are subject to the general large-text limit. Follow any smaller calculation limits above. Missing fields without a declared default, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use Strategy Robustness Across Quadrants Score: Robustness across scenarios requires every supplied quadrant to satisfy chosen payoff and risk criteria. Good averages can conceal a weak quadrant. For a complementary task, use Probable Plausible Preferable Scenario Sorter: Plausibility and desirability answer different questions about a scenario. Rankings should retain that distinction.
References
Similar or alternative tools
- Strategy Robustness Across Quadrants Score
Robustness across scenarios requires every supplied quadrant to satisfy chosen payoff and risk criteria. Good averages can conceal a weak quadrant.
- Probable Plausible Preferable Scenario Sorter
Plausibility and desirability answer different questions about a scenario. Rankings should retain that distinction.