Editing Bounds
This article explains how to edit bounds for input fields in Model Reef.
You will learn:
What bounds are and where they apply.
How to set minimum and maximum values.
How bounds interact with validation and warnings.
Bounds help prevent errors by flagging values that fall outside expected ranges.
What bounds are
Bounds are optional limits attached to an input field, usually at the variable or driver level, such as:
Minimum and maximum acceptable values.
Typical ranges for growth rates, margins or utilisation.
Thresholds for quantities like headcount or production volume.
They are not hard constraints on the model logic, but they provide warnings when inputs are outside the defined range.
Where to edit bounds
You edit bounds in the Units and bounds panel, accessed from:
The Variable Editor.
The Driver Editor for driver like assumptions.
For each relevant field or series you can set:
Lower bound (minimum).
Upper bound (maximum).
Bounds are defined in the same underlying units as the stored values.
How bounds affect input behaviour
When bounds are set:
Values entered outside the bounds may trigger visual warnings.
The system may request confirmation before accepting extreme values.
In some configurations, values beyond bounds might be blocked, depending on how strict validation is configured.
Bounds do not change or clip values silently; they highlight potential issues for the modeller to address.
Choosing sensible bounds
To set useful bounds:
Look at historical ranges for the variable or driver.
Consider realistic business constraints (for example utilisation cannot exceed 100 percent).
Set ranges wide enough to allow real variation but narrow enough to catch obvious mistakes.
Bounds can be adjusted over time as you learn more about the variable's behaviour.
Bounds and collaboration
Bounds are especially helpful when:
Multiple Editors work on the same model.
Viewers suggest input changes that are implemented by others.
You hand off parts of the model to less experienced team members.
They serve as embedded modelling guidelines and reduce the risk of extreme assumptions creeping in unnoticed.
Reviewing bound warnings
When you see values flagged as outside bounds:
Confirm whether the value is truly unusual or simply reflects a new reality.
If the value is correct and likely to continue, update the bounds.
If the value is a typo or misunderstanding, correct it.
Using bounds as a review tool improves model quality and oversight.
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