A required field and a validation rule both stop a bad save, and they stop different things. Required means the field cannot be empty. A validation rule means the value has to make sense against a condition you define. Choosing wrong produces either data that arrives too late or data that arrives fabricated.
The mechanical difference
| Behavior | Required field | Validation rule |
|---|---|---|
| Checks | Presence of any value | A condition you write |
| Timing | Every save, always | Only when the condition applies |
| Can depend on stage | No | Yes |
| Can compare two fields | No | Yes |
| Can reject an implausible value | No | Yes |
| Failure message | Generic | Written by you |
What only a rule can enforce
The requirements that keep pipeline data honest are almost all conditional.
- Competitor and loss reason required at closed-lost, not at creation. - Close date required to fall within the current fiscal year unless a documented exception field is set. - Amount required to be greater than zero before an opportunity reaches proposal. - Next step required to carry a future date on any deal forecast to commit.
Each of these is unanswerable at record creation and knowable later, which is exactly the case a required field handles badly.
Over-enforcement produces fiction
A field made required before the answer exists gets filled with whatever passes the check. Close dates land on the last day of the quarter because the picker defaults there. Competitor fields fill with NA. Amounts default to a round placeholder that never gets revised.
That data then flows into reporting as though it were observed. Default close dates in particular corrupt quarterly distribution and make deal slippage analysis unreadable, since a date nobody chose cannot slip in any meaningful sense. Presence-based enforcement measures whether reps clicked past a block, not whether the record is true.
A rule of thumb
Make a field required only when the answer is known at the moment the record is created, which in practice means account, owner, and stage. Everything else belongs in a conditional rule tied to the stage where the answer becomes knowable, which is the same logic behind required fields by stage.
Then keep the rule set small. Every rule is friction at save time, and friction pushes reps toward the shortest value that clears it. Protect the fields the forecast reads, write the error message so it says what to do rather than what failed, and let the rest stay optional. Paired with sound CRM validation rules on amount and date logic, that combination gives sales forecasting inputs worth modeling instead of inputs that merely exist.
Frequently Asked Questions
What is the difference between a required field and a validation rule?
A required field checks for presence and nothing else, so any character satisfies it. A validation rule evaluates a condition and blocks the save when the condition fails, which means it can require a field only at a specific stage, compare two fields to each other, or reject values that are present but implausible.
When should you use a validation rule instead of making a field required?
Whenever the requirement depends on context. Fields needed at proposal stage but unknowable at discovery, close dates that must fall inside the fiscal year, and amounts that must be positive all need conditional logic. A blanket required field forces reps to invent values early, which produces worse data than leaving the field empty.
Why do required fields produce junk data?
Because the block happens before the answer is known. A rep who must enter a competitor at record creation types NA or picks the first option, and that value persists through the deal and into your reporting. Presence checks measure compliance rather than truth.
How many validation rules should a CRM have?
Enough to protect the fields the forecast reads, and no more. Every rule adds friction at save time, and reps route around friction with placeholder values. Prioritize rules on amount, close date, stage progression, and the qualification fields your process depends on.
Put these metrics to work
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