How Productivity is Measured ?

We360.ai measures productivity by analyzing the active time spent on apps and websites that are mapped as productive. Here’s a crucial note: even if an app or URL is labeled as productive, if the employee is idle (i.e., no keyboard or mouse activity), that time is counted as idle time, not productive. The same logic applies to unproductive or neutral apps. This distinction ensures that time is only considered productive when employees are actively engaging with their work.

Example Scenario:

Let’s say an employee is attending a virtual meeting. While the meeting app (such as Google Meet, Zoom or Microsoft Teams) is mapped as productive, the employee may not be actively using their keyboard or mouse during the meeting. In this case, the time spent in the meeting will be considered as idle time, even though the meeting is a crucial part of the employee's job. This creates a gap in the analytics, as it shows the employee as being idle, despite participating in a productive activity.

Solution: Advanced Categorization Layers

To solve this issue and provide more accurate productivity tracking, We360.ai introduces an extra layer of categorization. This new feature allows for more refined tracking based on how time is spent, making it particularly useful for situations like meetings where active engagement isn’t always required.

Four New Categorization Layers:

1. Default:

1. This is the system's standard behavior. Only the active time spent on a mapped app/URL is counted as productive, unproductive, or neutral. Idle time is not considered.
2. Best for: Daily work where active engagement (keyboard/mouse usage) is necessary.
   

2. Focus Time:

1. This categorization considers all time spent (whether the employee is active or idle) on an app/URL as productive, unproductive, or neutral. This is ideal for apps where continuous activity isn't required, such as meetings.
2. Best for: Meeting tools and apps where employees are engaged but not necessarily typing or clicking.
   

3. Drop:

1. When an app or URL is categorized as Drop, it will not be tracked at all. All time spent on this app/URL is considered offline time and won’t be included in productivity analytics.
2. Best for: Personal or irrelevant apps that shouldn’t be tracked (e.g., media players, personal chat apps).
   

4. DLP-Redaction:

1. Similar to the default category, this option tracks active time but redacts the app name and URL for privacy reasons. Active time spent on the app/URL is still categorized as productive, unproductive, or neutral, but the details of the app are hidden.
2. Best for: Sensitive apps or websites where tracking is necessary but privacy is a concern (e.g., HR or confidential systems).
   

Why This Matters

These advanced categorization options allow businesses to get a clearer, more accurate picture of how time is spent across their organization. By distinguishing between productive, unproductive, and neutral time more effectively, managers can identify bottlenecks, optimize workflows, and ensure that employees' contributions are accurately reflected in the analytics.

For example, by using the Focus Time categorization for meeting apps, employees who attend crucial but passive meetings will no longer be penalized in productivity reports. Similarly, the Drop category helps filter out apps that are irrelevant to work, providing cleaner, more accurate data.

Conclusion

The advanced productivity mapping and categorization in We360.ai provides businesses with a powerful tool for analyzing employee time more accurately. By understanding how time is spent on apps and websites—whether employees are active or idle—you can make better decisions, improve productivity, and ensure that your analytics reflect the true efforts of your team.