Support Request – Validation Rule for Disaggregated Beneficiary Data

General
1

Dear ActivityInfo Support Team,

I hope you are doing well.

I am currently working on a form in ActivityInfo and would like to implement a validation rule to ensure data consistency between total beneficiaries and their disaggregation.

Specifically, I would like to prevent users from submitting the form if the following condition is not met:

  • Total number of females = number of women + number of girls

  • Total number of males = number of men + number of boys

I have attempted to apply a validation rule directly using a logical expression, as well as through a calculated field (boolean and text-based), but the validation does not seem to block submission as expected.

Could you please advise on:

  • The correct approach to enforce this type of validation in ActivityInfo

  • Whether a calculated field is required or if this can be done directly in the validation rule

  • Any best practices for handling such consistency checks across multiple fields

For your reference, the fields used are:

  • Number_of_female

  • Number_of_male

  • Number_of_women

  • Number_of_girls

  • Number_of_men

  • Number_of_boys

This validation is critical for ensuring data quality and alignment with donor reporting requirements.

Thank you in advance for your support.

2

Hello Ibrahime,

For your specific scenario, you should apply the following validation rules to your total fields:

  • For the Number_of_female field: Use the formula: Number_of_female == Number_of_women + Number_of_girls

  • For the Number_of_male field: Use the formula: Number_of_male == Number_of_men + Number_of_boys

The Number_of_female and Number_of_male fields will be marked as invalid if these conditions are not met, and the record cannot be submitted.

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There may be other approaches to achieve this using a combination of calculated fields and validation rules; however, though the above approach is the simplest.

You can also read further in the article about record validity, which may help improve data quality.

Let us know if this helps.