With Workforce Analytics, organizations can benefit from better forecasting, reduced hiring costs, optimized recruiting, improved employee retention, and increased employee morale. Specifically, Workload Distribution allows our clients to analyze workload, capacity, and staffing, leading to a more comprehensive understanding of resource allocation.

This feature enables departments like HR to set benchmarks and track workforce data, ultimately optimizing business operations. By providing deeper insights into performance metrics such as headcount, hiring needs, company culture, employee retention, and satisfaction, Workforce Analytics empowers businesses to make informed decisions that enhance overall efficiency.

Workload Distribution offers valuable use cases across various sectors. In tech companies, it helps software development teams allocate resources more effectively by identifying which teams need additional attention or manpower. Call centers can use it to distribute call workloads more efficiently, optimizing productivity and meeting SLAs. HR departments benefit by ensuring fair and equitable workloads, fostering a positive work environment, and enhancing employee retention. Corporate management can leverage this data to identify underutilized staff and improve cross-team efficiency through better workload redistribution.

This feature is available exclusively in the Process Improvement or Enterprise plan.

Workload Distribution is accessible to Admins by default, while Managers require specific permissions to view this report.

To effectively analyze workload distribution within a team, we categorize employees into three groups: overutilized, optimally utilized, and underutilized based on utilization persentage.

These categorization values are customizable at the organizational level, allowing you to define thresholds that align with your specific team dynamics and expectations.

By categorizing employees, you can gain valuable insights into workload balance, identify potential bottlenecks, and make informed decisions to optimize resource allocation and enhance overall team productivity.

To calculate distribution, divide the number of employees in each category by the total team size and multiply by 100.

For deactivated employees, we'll display their utilization and contribution during the period they were active. If an employee was deactivated but had data from both active and deactivated periods, they will still be counted in the total distribution.

For merged employees, we'll show separate utilizations up until they were merged. If the selected period includes both pre-merge and post-merge data, both will be counted in the total distribution.

For employees switching teams, their contribution to each team and their utilization percentage will be considered for the selected period, reflecting their time in both teams.

Navigating to the Reports → Workload Distribution tab, you'll find the health trend graph, which visually represents average team utilization over time. Each line corresponds to a different team, and ongoing days are marked with dashed lines to capture the fluidity of daily utilization.

Settings button is a shortcut where Admins can adjust their preferred range for optimal and therefore for underutilized and overutilized.

When you click on a line in the graph to highlight a team, only that team will be selected in the team table. If you select another team in the table, it will appear on the graph above.

In the team table, we are sorting based on distribution taking in consideration first most overutilized team, then most underutilized teams and lastly, teams that are mostly optimal.

Hovering over the distribution section will reveal a popover displaying the exact number and percentage of team members, which aligns with the conclusion shown on the right-hand side.

Based on the distribution that is shown, some conclusions will be captured which will help you understand percentages and make the right choices and actions.

If you visit the Settings → Reports → Workload distribution tab, each organization can set their custom values for what they consider to be in the optimal range, while we are automatically, based on it, setting underutilized (values below) range and overutilized (values above).