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Find & Clean Up Unused Fields in Salesforce

Salesforce Data Quality Guide

Unused fields in your Salesforce instance can significantly impact the effectiveness of your Salesforce org. A cluttered UI filled with unused fields makes it difficult for users to quickly locate and update the information they need. This can result in data inconsistencies, delays in business processes, inaccurate reporting, and reduced productivity.

Cleaning up unused fields is essential to streamline your Salesforce processes and improve the overall health of your org. Unused field cleanup simplifies the user experience, reduces frustration, and improves data quality. Most importantly, it makes Salesforce easier to use for everyone. Users can get their jobs done faster, and leaders can trust that the data is accurate for decision-making.

During your analysis, you may discover three kinds of unused fields:

  • Empty fields that were never populated
  • Essentially empty fields: Fields filled predominantly with default values
  • No longer used fields

Don’t Be Fooled by Defaults: Identify All Unused Fields with Net Fill Rates

The fill rate of a field, also known as the population rate, indicates the percentage of time a field contains a value. While fill rate offers a starting point, it often hides fields masquerading as in-use when they are not.

Consider this: many Salesforce fields have a default value. If a field is fully populated but solely with the default value, is it truly utilized? To combat false positives in field utilization reporting, Cuneiform gives you the most comprehensive data analysis, calculating both gross fill rate and net fill rate for each field.

Identify Rarely or Never Used Fields

Identifying unused fields is the first step towards decluttering Salesforce, improving data quality, and enhancing performance. Native data profiling provides an automated field audit to quickly uncover unused fields in your Salesforce objects.

Start by profiling your object and reviewing fields with low fill rates and net fill rates. In Cuneiform start with fields with 0% Net Populated Records. These are your initial candidates for removal. After you work through the initial cleanup, expand to fields with low net population rates (e.g. less than 15%).

When considering which fields to remove, evaluate their relevance, impact on data accuracy, and alignment with current business processes. Review the Description and Data Owner to get a quick sense of the field’s purpose. Also, look at metadata dependencies for additional insight into the fields’ usage. Note: Cuneiform’s Dependency Count uses the Salesforce Metadata tooling API (beta) which only provides results for custom fields.

As you work, use Data Classification to keep track of candidates for removal. Change the Field Usage of each potentially unused field to “DeprecateCandidate.” This will make managing the fields easier throughout the cleanup process.

Salesforce field utilization report

Identify Inactive Fields and Fields with Declining Usage

As business processes evolve, so does the data you collect. If your org is more than a few years old, there’s a good chance that you have inactive fields in addition to empty fields. Assess field population rate across time horizons to uncover fields that have become irrelevant or are trending that way. Fields that are no longer in use (or are trending that way) are good candidates for cleanup.

Cuneiform for CRM makes it easy to spot these fields with comparative profiling capabilities. Compare profiling results from all time to results from only recent data (e.g. last two years). Alternatively, create secondary time-based data profiling definitions.

Engage your data governance process to decide the data retention policy for data in inactive fields. Archive any required historical records before deleting the inactive fields.

Compare Salesforce field usage across time periods
Compare Salesforce field usage for different time periods to find more clean up opportunities.

When 0% Population Doesn’t Mean Deletion

Do not assume that all zero percent populated fields should be deleted. Consider extending the value set for Field Usage to categorize these fields (i.e. Integration, Transient) and save time in the future.

  • Automatically populated fields: These can indicate a potentially broken automation or integration.
  • Newly introduced fields: Do users have necessary access and training on these fields?
  • Fields used at quarter/year-end: If the field was created after the last quarter or year-end, it is expected to be empty.
  • Transient fields: Occasionally an integration or calculation process relies on temporarily populating a field.

Best Practices for Removing Unused Fields from Salesforce

Follow best practices for removing unused fields. This will help guarantee a safe and efficient process, avoiding any surprises or user interruptions.

  1. Communicate with stakeholders: Inform all stakeholders, including your users and management, about the upcoming field cleanup process. Share a report of all fields marked as candidates for deprecation and any metadata dependencies to solicit their feedback. This ensures transparency and allows for any necessary discussions or considerations.
  2. Remove access to unused fields: After the feedback period, remove user access to these fields by removing field-level security for all users/profiles. Notify users and wait another week or two for users to report issues
  3. Test the impact: Create a sandbox to test deleting the fields. This allows you to assess any potential issues or dependencies that may arise from the removal.
  4. Back up your data: Before removing any unused fields, back up your data for all fields marked as DeprecateCandidate. This ensures that you have a copy of the information stored in those fields in case you need it in the future.
  5. Delete unused fields: If there are no issues reported by users, it is safe to delete the unused fields. First remove unused fields from all reports, dashboards, flows, and triggers. Then delete the unused fields in Salesforce Setup.

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