What This Feature Does for You
Historical comparisons help you catch data entry errors before they become problems. Instead of discovering inconsistencies later in your reports, you can now spot and fix potential issues right as you're entering data. This saves time, reduces errors, and gives you confidence in your ESG data quality.
How to Access Historical Comparisons
When you're entering data for Scope 1, 2, or 3 carbon emissions in the Collect Data section, look for the "Compare historical data" button below your data entry options. This button only appears for data points where you have previous submissions from earlier reporting periods.
Note: If you don't see this button, it means you're reporting on this data point for the first time, so there's no historical data to compare against yet.
Understanding Your Historical Data View
When you click "Compare historical data," you'll see your previous entries from all available years and reporting periods. This gives you context to assess whether your current data entry looks reasonable compared to your past submissions.
The historical data view initially defaults to the most recent data submission.
Upon changing submission comparison to a different time period, this selection will be remembered for this particular question.
Smart Period Comparisons
The system automatically adjusts for different reporting frequencies. For example:
If you previously reported quarterly but are now entering monthly data, you'll see the monthly equivalent of your quarterly submissions
If you reported annually last year but are now reporting quarterly, the system shows the appropriate quarterly breakdown
This ensures you're always comparing like-with-like, even when your reporting cadence changes.
Spotting and Handling Data Outliers
As you enter numerical data, the system automatically checks if your entry falls significantly outside your historical range. Specifically, if your new entry is 25% higher or lower than comparable previous submissions, you'll see a visual alert.
Outliers aren't always errors. They might indicate:
Legitimate business changes: New facilities, changed operations, or seasonal variations
Reporting improvements: More accurate data collection methods
Actual errors: Typos, wrong units, or misplaced decimal points
What to do: Review your entry and ask yourself:
Does this change make sense given what happened in my business this period?
Am I using the right units (tonnes vs. kilograms, etc.)?
Did I enter the number correctly?
If the change is legitimate, you can proceed with confidence. If something seems off, double-check your data before submitting.
Copying Data from Previous Periods
For data that hasn't changed significantly or follows predictable patterns, you can bulk-copy rows from previous submissions and then modify only what's different.
How to Copy Previous Data:
In the historical comparison view, find the previous submission you want to copy
Click the “Copy previous data” button
The data will populate in your current period's entry fields
Edit any values that have changed for the current period
Submit as normal
When Copying is Useful:
Facility data that remains relatively stable
Recurring purchases or activities
Baseline operations that don't vary significantly period-to-period
Why This Helps Your ESG Reporting
This feature shifts quality control from reactive to proactive:
Catch errors early: Fix issues during data entry instead of discovering them later
Build confidence: See your data in context to feel confident about accuracy
Save time: Copy stable data and focus your attention on entries that have genuinely changed
Learn patterns: Understand your organization's ESG trends over time
Getting the Most from Historical Comparisons
Use it as a sense-check: Historical data should inform your current entries, not constrain them. Legitimate business changes should be reflected in your data.
Pay attention to patterns: If you consistently see outliers in certain areas, it might indicate a need for process improvements or additional training for data collectors.
Document significant changes: When you have a legitimate outlier, consider adding notes to explain the variance for future reference and audit purposes.
Need help?
If you have questions about interpreting your historical data or would like guidance on handling outliers, our support team is here to help at support@keyesg.com. We're excited about this improvement and believe it will give you even more confidence in the accuracy and consistency of your ESG data.