Block Schedule Analytics gives you powerful visibility into how blocks and rotations are being used across your organization. With this feature, you can quickly identify gaps, trends, and optimization opportunities within your schedules.
Two Types of Analytics
Block Schedule Analytics is divided into two main areas:
Associate Analytics: focused on individual associate-level data and rotations within blocks.
Block Analytics: focused on analyzing patterns and data across entire blocks within the schedule.
Creating Block Analytics
If you want to analyze specific conditions within a block, such as identifying how many empty rotations exist in Block 1, you’ll need to create a custom statistic.
Step 1: Create a Statistic
Navigate to the block you want to analyze (e.g., Block 1).
Click Create Statistic, located below the block.
3. (Optional) Assign a color and icon to help visually identify the statistic later.
Defining the Statistic Logic
Once you’ve started creating a statistic, you’ll define the logic that determines what the system should analyze.
For example:
Set the logic to count blocks with empty rotations.
Confirm your criteria.
Click Create.
At this point, the system will generate a code for the statistic.
Viewing Analytics Across All Blocks
After the statistic is created:
The analytic will appear for every block, across all blocks in the organization, not just the one where it was created.
This allows you to compare patterns and identify empty rotations consistently across the entire schedule.
Understanding Total Analytics
The Total Analytics view adds the data and:
Counts all empty blocks across rows and columns
Provides a high-level summary of empty rotations throughout the schedule
This makes it easier to spot systemic gaps and prioritize scheduling improvements.