Augmentation and Automation Strategy Grid
Place caller-supplied augmentation and automation scores on a transparent human-baseline, augmentation, automation, or integration grid.
Description
Augmentation and automation describe two distinct dimensions of a work strategy.
Augmentation and automation describe two distinct dimensions of a work strategy. An explicit threshold divides a simple four-cell grid.1
The returned values include Grid label, Grid position. The How section below explains the calculation, input rules and interpretation.
When to use Augmentation and Automation Strategy Grid
Use Augmentation and Automation Strategy Grid when you need to evaluate the supplied records under the calculation and evidence rules below. No optimal strategy, productivity estimate or empirical readiness is established.
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 Augmentation and Automation Strategy Grid 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 augmentationScorePercent, automationScorePercent, gridThresholdPercent using the field table and calculation rules, then run the tool.
- Read gridLabel, gridPosition. 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 |
|---|---|---|---|
| augmentationScorePercent | Augmentation score (%) | number; minimum: 0; maximum: 100 | Required |
| automationScorePercent | Automation score (%) | number; minimum: 0; maximum: 100 | Required |
| gridThresholdPercent | Grid threshold (%) | number; minimum: 0; maximum: 100 | Required |
Require finite scores/threshold 0–100. Both high gives integration; only augmentation high augmentation; only automation high automation; neither humanBaseline. Return category and score/threshold string.
highAug=augmentation≥threshold; highAuto=automation≥threshold Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| gridLabel | Grid label | string; one of "humanBaseline", "augmentation", "automation", "integration" |
| gridPosition | Grid position | string |
{
"input": {
"augmentationScorePercent": 80,
"automationScorePercent": 20,
"gridThresholdPercent": 50
},
"output": {
"gridLabel": "augmentation",
"gridPosition": "augmentation=80; automation=20; threshold=50"
}
}Limitations and assumptions
No optimal strategy, productivity estimate or empirical readiness is established.
Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. 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 Automation Labor Displacement Share Model: Labor-displacement scenarios can combine a potentially automatable share with adoption and execution assumptions. The returned shares have different denominators. For a complementary task, use Takeoff Speed Fast Slow Scenario Classifier: A takeoff-speed scenario depends on both capability development and deployment. Their equal-weight mean gives this caller-defined speed score.
References
Similar or alternative tools
- Automation Labor Displacement Share Model
Labor-displacement scenarios can combine a potentially automatable share with adoption and execution assumptions. The returned shares have different denominators.
- Takeoff Speed Fast Slow Scenario Classifier
A takeoff-speed scenario depends on both capability development and deployment. Their equal-weight mean gives this caller-defined speed score.