ActivTrak for BI - Potential False Activity Analysis helps organizations identify and investigate instances where ActivTrak's detection systems have flagged potentially artificial or automated input patterns. Available to customers with an ActivTrak paid plan and the ActivConnect API (Add-on), this report provides visibility into activities that may indicate testing scenarios, automated processes, or system anomalies that could affect the accuracy of your productivity data.
To access the Potential False Activity Analysis BI report, please refer to our platform-specific BI Template Setup Guides:
- Setup Guide: ActivTrak for Power BI - Potential False Activity Analysis
- Setup Guide: ActivTrak for Google Data Studio - Potential False Activity Analysis
- Setup Guide: ActivTrak for Tableau - Potential False Activity Analysis
Tip: Save this report in your BI workspace for quick access and consider sharing it with team leads responsible for data quality and user management.
Contents
- When to use ActivTrak for BI - Potential False Activity Analysis
- Navigating ActivTrak for BI - Potential False Activity Analysis
- Sharing and distribution
- Practical applications
- Learn more
When to use ActivTrak for BI - Potential False Activity Analysis
The Potential False Activity Analysis helps IT administrators and team managers maintain the integrity of workforce analytics data by identifying activities that may not represent genuine user work patterns. Use this report to:
- Investigate repetitive activity patterns that may indicate automated testing or macro usage
- Identify extended duration events that could signal system anomalies or non-human activity
- Verify that productivity metrics accurately reflect actual employee work
- Review flagged activities before making decisions based on analytics data
- Maintain compliance with data accuracy standards
Glossary: ActivTrak for BI - Potential False Activity Analysis
For a deep dive into each of the terms and metrics found in ActivTrak for BI - Potential False Activity Analysis, check out the supporting Glossary.
Navigating ActivTrak for BI - Potential False Activity Analysis
Filter settings
ActivTrak for BI - Potential False Activity Analysis can be customized using the filter dropdown menus at the top of both tabs of the report:
- Group: Filter data by specific teams or business units
- User: Select individual users to review their flagged activities
- Day Type: Choose between workdays and weekends to identify patterns based on expected work schedules
- Date: Select the time range for your analysis
Potential False Activity Analysis tab
Potential False Activities Count Trend
The Potential False Activities Count Trend chart visualizes the frequency of flagged activities over your selected time period. This trend line helps you identify:
- Spikes in potential false activity that may indicate testing periods or system issues
- Patterns that correlate with specific events, deployments or team activities
- Whether flagged activities are isolated incidents or recurring concerns
- Overall improvement or degradation in data quality over time
Monitoring this trend helps you distinguish between one-time anomalies and systematic issues that require investigation.
Potential False Activities table
The Potential False Activities table provides detailed information about each flagged event, including Date & Time, User, Title, and Activity.
This section also displays a PFA Events per User summary table. This is located in the top right corner of the report. This tab helps you understand the nature of each flagged event and determine whether it represents legitimate work or other scenarios requiring attention.
Extended Duration Events tab
The Extended Duration Events tab identifies activities that exceed defined time thresholds and may require investigation. Extended duration events can indicate:
- Applications left open but not actively used
- Automated processes running continuously
- System anomalies or frozen applications
- Testing scenarios that run for unusually long periods
Extended Duration Events Trend
A visualization showing the frequency of extended duration events over time, comparing User and Event Count.
Extended Duration Events - User Report
A detailed breakdown showing User, Extended Events Count, Total Duration Minutes, and Avg Duration Minutes per Event.
Note: Some users may show "Infinity" in the Avg Duration Minutes per Event column, indicating events that exceeded maximum tracking thresholds or remained active beyond the analysis period.
Sharing and distribution
Ensure the right teams receive this data quality information by leveraging BI's sharing capabilities:
- Export to PDF/PowerPoint: Create reports for IT leadership or data governance reviews
- BI service publishing: Publish the report to your organization's BI service for browser-based access by authorized personnel
- Email subscriptions: Set up automated email delivery through BI's subscription features for regular monitoring
- Mobile access: Enable on-the-go review through the BI mobile app
Tip: When sharing this report with stakeholders, emphasize that flagged activities don't necessarily indicate policy violations. Many potential false activities represent legitimate testing, development work, or automated processes that should be documented rather than discouraged.
Practical applications
Maintaining data accuracy
This report provides crucial quality assurance for your workforce analytics program:
- Verify data integrity: Identify and document activities that should be excluded from productivity calculations
- Establish baselines: Understand normal patterns of testing and automated activity within your organization
- Track improvements: Monitor whether data quality initiatives reduce the frequency of flagged activities over time
Identifying system testing activities
For organizations with development teams or IT departments conducting regular testing:
- Document testing periods: Correlate spikes in potential false activities with known testing schedules
- Separate testing data: Identify test user accounts or testing periods that should be filtered from production analytics
- Validate detection accuracy: Confirm that the system correctly identifies testing scenarios while avoiding false positives on legitimate work
Detecting automated processes
Help IT teams understand and manage automated activities:
- Identify bot accounts: Discover user accounts running automated scripts or processes
- Document legitimate automation: Create exceptions for approved automated activities that support business operations
- Investigate unauthorized automation: Flag potentially problematic automation that may violate usage policies or security standards
Tip: When investigating potential false activities, start by reviewing the Extended Duration Events report alongside the Potential False Activities data. Activities that appear in both reports often warrant closer examination, as they may indicate automation, testing, or system issues that require documentation or remediation.