Note: Labor Analytics is currently in Beta. During this phase, access to the functionality is available only to Beta customers.
Enabling and Accessing the Labor Analytics Module
To provide your team with access to the Labor Analytics module, follow these two main steps: configuring role permissions and managing user licenses via the Add-on screen.
1. Granting Role-Based Permissions
The first step is to ensure the module is visible in the system for specific user groups. To do this:
Navigate to Settings > Role.
Select the Role you wish to authorize.
Go to the Analytics tab.
Locate and check the Labor Analytics permission.
Save your changes.
Once this is done, the Labor Analytics menu item will appear under of the Analytics menu for all users associated with that role.
2. User Authorization and License Management (Add-on Screen)
After the role permissions are set, you must manage the individual user access within the Add-on section:
User Limit: The Labor Analytics add-on allows authorization for up to 5 users. You can select and manage these specific users directly from the Labor Analytics card in the Add-on screen.
Summary of Access
Visibility: Controlled via Settings > Role > Analytics.
Seat Allocation: Controlled via the Add-on screen (up to 5 users).
LABOR ANALYTICS DASHBOARDS :
A. AVERAGE TASK ANALYSIS (Dashboard 1)
1. Dashboard Objective: What is Measured?
This dashboard is designed to measure labor efficiency within the warehouse operation.
Core Metric: Tasks Per Hour. This metric shows how quickly and efficiently operators complete tasks during their shifts.
Metric Formula
The metric is calculated by dividing the task count by the operator’s operational shift duration, not the sum of individual task durations:
Tasks Per Hour = {Total Completed Task Count} / {Total Operational Labor Hours}
Detailed Metric Definitions
2.1. Total Task Count
Definition: The total count of unique task numbers that are in a completed state, based on the selected
Measurement Datefilter.Important Note: This count does not take into account the quantity of items within a task. If a task is completed, it counts as one task, regardless of whether it contained 1 or 100 items.
2.2.Operational Labor Hours (Total Labor Hours)
Definition: The total time elapsed between the minimum start time (
min_start_time) and the maximum finish time (max_finish_time) for all tasks completed by each operator on a given day.
3. Looker Dashboard Filters and Usage
When opening the dashboard, the following filters are used to restrict the analysis and focus on the desired operation:
Measurement Date: The main starting date for the analysis. All comparisons are based on this selected day.
Task Type Parameter: Allows restricting the analysis to specific task types (Pick & Pack)
Warehouse Code, Job Type: Narrows the analysis by warehouse and job type.
4. Metric Tiles and Comparison Logic
Each tile on the dashboard displays the Tasks Per Hour value and presents the percentage change compared to the previous period.
5. Monthly Average Chart
Title: Monthly Average Tasks Per Hour (12 Months)
Goal: To track the efficiency trend on a monthly basis.
Calculation: Each column shows the monthly average obtained by dividing the total completed tasks for that month by the Total Labor Hours, summed up separately for each day within that month.
B. ASSOCIATE TASK ANALYSIS (Dashboard 2)
1.Calculation Logic
The calculation logic for Tasks Per Hour in this dashboard is identical to the logic used in the Average Picks Analysis dashboard.
It calculates efficiency by dividing the total completed tasks by the operational labor hours (calculated from the minimum start time to the maximum finish time) for each associate.
2. Dashboard Tiles
This dashboard consists of two main bar charts that breakdown performance by associate:
A. Today
Description: Displays the Tasks Per Hour performance for all associates who worked on the specific single date selected in the Measurement Date filter.
Purpose: Allows for a quick comparison of daily performance across the workforce for the selected day.
B. Last 30 Days
Description: Displays the average Tasks Per Hour performance for all associates who worked during the 30-day period ending on the selected Measurement Date.
Calculation Note: To ensure accuracy, the total labor hours are derived by calculating the working hours for each day separately within the 30-day period and then summing them up.
Purpose: Helps evaluate associate performance over a longer period, smoothing out daily variations to identify consistent trends.
C. PERFORMANCE QUADRANT ANALYSIS (Dashboard 3)
1.Dashboard Purpose
This dashboard uses a scatter plot to segment associates into four distinct performance categories based on the selected time period. It helps identify top performers, associates needing coaching, and those with high potential but low volume.
2. Understanding the Chart Axes
Each dot on the chart represents an individual Associate. The position of the dot is determined by two key metrics calculated over the selected Measurement Date range:
X-Axis (Horizontal): Represents Efficiency (
Tasks Per Hour). Moving to the right indicates higher speed.Y-Axis (Vertical): Represents Volume (
Total Completed Tasks). Moving upwards indicates a higher quantity of work completed.
3. The Four Performance Quadrants
The chart divides the area into four quadrants to categorize associate performance:
Top Performance (Top-Right): Associates with both High Volume and High Efficiency. These are the most productive members of the workforce.
High Efficiency / Low Volume (Bottom-Right): Associates who work fast but completed fewer tasks total (possibly due to fewer hours worked or part-time shifts).
High Volume / Low Efficiency (Top-Left): Associates who completed a large number of tasks but at a slower pace. They are hardworking but may need training to improve speed.
Low Performance (Bottom-Left): Associates with both Low Volume and Low Efficiency. This quadrant typically indicates a need for immediate performance review or training.
4. Time Selection & Filtering
The analysis relies heavily on the Measurement Date filter, which offers flexible time selection options:
Presets: Standard periods such as "Last 30 Days" or "Last 90 Days" can be quickly selected.
Custom Range: A specific start and end date (e.g.,
2025/11/11 - 2025/11/15) can be defined to analyze performance during a particular peak season or work week.
D. ASSOCIATE ANALYSIS (Dashboard 4)
1.Dashboard Purpose and Logic
The primary goal of this dashboard is to compare assocaite’s own performance . This clearly indicates whether an associate's workload volume is increasing or decreasing.
1.1.Comparison Logic (Scenario Example)
For the most accurate comparison, it is recommended to use "Last XX Days" filters. There is no way to not listing other date filters unfortunately.
Current Date: November 19
Selected Filter: Last 7 Days
Current Period: November 13 - November 19 (The selected 7 days)
Previous Period: November 6 - November 12 (The immediately preceding 7 days)
The system compares the number of completed tasks between these two date ranges.
2. Understanding the Table Columns
The analysis table provides the following details for each Associate:
# of Picking Tasks Completed: The total number of picking/packing tasks completed in the Current Period (e.g., Nov 13-19).
# of Picking Previous Task Completed: The total number of tasks completed in the Previous Period (e.g., Nov 6-12).
Vs Previous Period (%): The percentage change between the two periods.
Average Picks Per Hour: The associate's average hourly picking/packing speed during the current period.
3. Important Usage Note
To obtain an accurate and meaningful "previous period" comparison, it is recommended to use dynamic ranges such as "Last 7 Days" or "Last 30 Days" in the Measurement Date filter.