Identify and mitigate performance risks due to high record counts in Salesforce

Why monitor record counts on Objects?

Salesforce Objects (aka SObjects) with a significant number of records can cause significant performance impact to your Org due to data skew, sub-optimal configuration, and default Salesforce technical limits (you can read more about those limitations here). Keeping your data volumes under control is also one of Salesforce’s Well-Architected principles. Key performance issues include:

• Slow Queries: Large datasets take longer to process and retrieve results.
• Delayed response on Save: Creating or updating records taking longer than expected, or timing out potentially causing loss of data or failed business process automation.
• Search Delays: Indexing can be slower, degrading the user experience.
• Inefficient Reporting: Complex reports with large data volumes experience long processing times.
• Data Skew: Uneven data distribution can cause extended locking issues during mass updating of records and record sharing recalculations.
• Storage Problems: Excessive record volumes consume the inclusive data storage which may need additional licensing to resolve.

To prevent these issues, regular monitoring and proactive management of objects is recommended.

By the end of this guide, you’ll understand how to monitor and optimize record counts to prevent these issues.

When to investigate record counts on Objects?

When should you investigate record counts on objects? Regular monitoring of object record counts and their ownership profile is critical to preventing the performance challenges outlined earlier for business users, such as slow queries and data skew. Proactively identifying risks ensures your Salesforce Org runs smoothly and avoids disruptions. In this section, we’ll explore detailed insights into where monitoring becomes essential and how Elements can help streamline this process. Here’s when to do so:

• Regular Monitoring: Continuously review objects exceeding strict resource limits of 10,000 (check record ownership), 50,000 (check queries accessing without filters), and 2,000,000 (record indexing performance) records and track growth trends periodically.
• Threshold Alerts: Set up alerts in Salesforce for objects nearing critical limits (e.g. 50,000 records) to take proactive action.
• Major Business Changes: Monitor objects after system upgrades, new processes, or campaigns that increase record creation.
• High-Volume Periods: Before peak events like sales promotions, seasonal demand, or end-of-quarter reporting, ensure the critical objects are optimized.

Object classification

To help you manage your data retention and storage policies effectively, you can leverage Elements.cloud’s Custom Metadata Views, Data Tables, and MetaFields which allows you to classify objects and forecast growth. The essential categorization on each of your objects in Salesforce are:

• Storage Duration: Classify how long the data needs to be stored (e.g. short-term, medium-term, or permanent).
• Retention Reason: Specify why data is stored (e.g., compliance standards or business needs).
• Archiving Strategy: Define whether to migrate, archive, summarize, delete, or retain data once it is no longer being actively used.
• Data Archiving Condition: Describes the conditions that can be used to decide which records to archive, summarize, migrate, or delete.
• Data Storage Risk: Track the current classification of an object based on its record count and data storage utilization (e.g. Healthy, Needs Monitoring, or Needs Remediation).
• Remediation Plan: Assign actions like index key fields through skinny tables and external IDs, migration to BigObjects or Data Cloud, remove unused data, and implement asynchronous processing or batch processing.

Document your data archiving policies

Your Org has plenty of standard and custom objects. But most of the time there is no specific policy or consideration for how much data we plan to store, for how long, and what to do with the data which is no longer needed.

Document Your Data Archiving Policies

Ensure your Org has a clear strategy for data storage and retention.

• For New Objects: When designing new objects, collaborate with stakeholders to define:
  • How long data will be stored.
  • Why the data is needed.
  • The archiving strategy for unused records.
  • A business owner for the data who can make decisions on retention.
• For Existing Objects: Review current storage practices with stakeholders and document:
  • Storage duration, retention reasons, and archiving conditions.
  • Examples like storing business-critical product risks for five years or archiving them three months after they are no longer required.

Review Data Policies:

Work with department heads or legal teams to evaluate and refine data storage policies:

• Ensure all objects have clear retention guidelines and archiving strategies.
• Include practical use cases to illustrate policies.
• Understand the regulatory needs including data privacy rules, and freedom of information requests

By maintaining well-documented archiving strategies, your Org can avoid unnecessary data accumulation and improve system performance.

Example: It is common for case records to accumulate quickly over time. For a business that sells their product or services as an annual subscription, up to 5 year deals. You may specify a condition that all case records need to be stored for up to 5 years. Or that they can be deleted within 3 months after the account churns and does not renew their contract.

Identify risky objects based on record counts

Once you’ve set up monitoring and tools, the next step is identifying risky objects and taking actionable steps to optimize them. Let’s break down this process into clear steps.

Step 1: Quick scan in Analytics 360

Watch this quick video from Brooke, Partner Success Manager and Salesforce expert, on how you can quickly identify objects with risky levels of record counts in your Org.

Step 2: Review and classify risky objects

Step 2.1: Create custom views of metadata

Start by creating a custom view of metadata in Elements for custom and standard objects. Pick name, API name, metadata type, description, record count to be included as columns. Also, add the six categorizations discussed earlier using MetaFields:

• Storage duration 
• Retention reason
• Archiving strategy 
• Data archiving condition
• Data storage risk 
• Remediation plan

Step 2.2: Classify objects exceeding 10,000 records

Flag objects with over 10,000 records as ‘Needs Remediation’ and investigate potential risks. Common issues and remediation actions are outlined below:

Issue	Impact	Remediation Plan
Ownership Skew	Records owned by a single user slow access changes (e.g., recalculations, bulk updates). This may be a result of automations, or a previous data migration or mass upload.	Redistribute ownership to balance workloads and represent actual data owners rather than systems.
Lookup Skew	Parent records linked to 10,000+ child records experience database locking during updates.	Optimise parent-child relationships, review data model design.
Account Data Skew	Large accounts with high volumes of related records (e.g., cases, contacts) result in slower processing and locking errors.	Split large accounts into an account hierarchy, or restructure relationships.

How to Investigate and Resolve:

1. Use analytics resources such as custom Salesforce reports or metadata exports to identify objects with potential risks.
2. Export detailed insights such as metadata views as a CSV file to filter mass updates and highlight objects visually.
3. Implement the remediation plans to address identified issues.

​Step 2.3: Classify objects exceeding 50,000 and 2 million records

Objects with over 50,000 records can exceed query limits and cause serious performance issues unless accessed correctly. Flag these objects as ‘Needs remediation’ and use Element’s metadata views or exports to identify them visually, review the queries used in automations to ensure they follow best practice selective queries, which are indexed.

Even when your queries are selective performance can suffer at over 2 million records and a large data volume strategy should already be in place.

You can export the list of objects as a CSV file and filter it in a spreadsheet.

Step 2.3.1: Identify objects that have a lot of records that can be archived

Earlier, you documented data storage policies for each object in your Org. Use this original report to identify if any large-data-volume objects contain records that can potentially be archived.

Filter your custom view of metadata to only contain objects that for ‘Archiving strategy‘ have value ‘is not equal to “Keep on platform“. This will show all objects where the archiving strategy is set to delete records, archive them off-platform, or store them in the big object.

Step 2.3.2: Identify actions to optimize performance on large-data-volume objects

For objects that have more than 50,000 records exceeding the common report limits, find any automations, like flows, apex classes, or apex triggers, that are tied to those objects. If there are no automations tied to those objects, then you are not facing any immediate challenges. But you should still consider taking action in order to prevent future challenges.

For objects with over 50,000 records and any flows, apex classes, or triggers dependent on them, review them one by one to identify any potential issues.

Issues to look for and how to remedy them

• SOQL Query Limits in Apex Classes: SOQL queries are limited to 50,000 records in Apex code. Exceeding this limit can cause failures or prevent a query from returning all relevant data.
  • Remediation plan: Optimize queries that are not selective, consider batch processing

• API Call Limits: Large datasets can strain API call limits, particularly during integrations or bulk operations.
  • Mitigation: Use Bulk API (to get data from the object in integrations) or Apply Batch Processing (for internal automations)

• Apex Trigger Execution Limits: Salesforce triggers process up to 200 records at a time. Large datasets may hit governor limits during bulk updates or complex transactions unless the Apex triggers are “bulkified”.
  • Mitigation: Review and optimize triggers to prevent these issues. (Note: code quality factors into this significantly– sub-optimal code can result in a need to throttle back from 200)

• Indexing and Selectivity: Non-selective queries can lead to full table scans, significantly impacting performance or being rejected by governor limits.
  • Mitigation: Index Key Fields and Optimize Queries

Step 3: Audit sources of data creation

• Should this object really have that much data?
• Should the number of records be accumulating that quickly?

These are the sorts of questions that are not often asked but are critical to monitoring and securing performance of your Org.

Here is what you need to do:

• Assess whether records are being created intentionally as part of a controlled process, and identify the systems or processes contributing to record creation.
• Identify anomalies in automated processes related to this object, and determine if automation should be adjusted to better manage record creation and lifecycle.

Determine the list of automations tied to an object and even identify apex classes or flows responsible for creating new data.

Review those automations and decide whether they are still needed, or are they legacy automations that support a long-forgotten or deprecated business process.

Step 4: Identify and resolve unusual data patterns

​Investigate spikes or drops in record creation to identify anomalies. These patterns often reflect business changes (e.g., marketing campaigns or customer behavior shifts) or outdated processes. Align actionable insights with your business strategy to detect and address suspicious activity.

For the selected object, right-click/use the context menu and select ‘Open adoption insights’. This will open a dashboard for the object with record population data for the selected time period. You can use the Record count over time chart to identify any suspicious data patterns.

Take action

After the review is finished, you will end up with a list of objects classified by data storage risk as ‘Needs remediation‘.

Custom views of metadata come equipped with many single and bulk operations. You can raise user stories and document tasks to index key fields, optimize queries, or any other identified remediation actions.

We propose that you filter your object list by remediation plan (e.g. remediation plan is ‘Archive old data‘) and then you can bulk-create stories for all objects with the same remediation plan. You will end up with multiple stories, each linked to a different object, specifying the needed remediation action.

You can then pick up those stories from your backlog and deliver them when there is capacity.

Summary

In conclusion, managing record counts in your Salesforce Org is not just about improving query performance but also about addressing critical risks that can impact your overall business operations. By implementing proactive risk management strategies, such as optimizing data storage, leveraging batch processes, and performing regular performance tuning, you can mitigate performance bottlenecks and ensure efficient resource usage. With these practices in place, your Org will be well-prepared to scale effectively and deliver lasting value.