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title: Optimize Large Datasets in One Smooth Operation with Dynamic Scaling (Generally Available)
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locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/release-notes/260-0-0/rn_fieldservice_260_dynamic_scaling.md
canonical_url: https://help.salesforce.com/s/articleView?id=release-notes.rn_fieldservice_260_dynamic_scaling.htm&release=260&type=5
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description: Set up and manage large-scale global and in-day optimization effectively without splitting data due to system limits. Dynamic scaling intelligently structures data into geographical clusters, seamlessly balancing demand and capacity while accounting for all operational work rule constraints. This capability simplifies optimization management by enabling higher system limits, so you don’t need to manually define optimization groups and boundaries. It also prevents conflicts and overlaps that often occur with fragmented, parallel optimization runs. You can now easily select all service territories when you configure a scheduled optimization job without having to select each territory individually. Previously, you had to define boundaries between areas that needed to be optimized together, making workforce planning difficult. Lower system limits meant you had to reduce the number of service appointments or service resources processed in a single request, and configure multiple optimization jobs. This fragmentation was tedious and affected overall business performance.
products:
  - Cross Cloud Packages Solutions
release: "260"
---
# Optimize Large Datasets in One Smooth Operation with Dynamic Scaling (Generally Available)

Set up and manage large-scale global and in-day optimization effectively without splitting data due to system limits. Dynamic scaling intelligently structures data into geographical clusters, seamlessly balancing demand and capacity while accounting for all operational work rule constraints. This capability simplifies optimization management by enabling higher system limits, so you don’t need to manually define optimization groups and boundaries. It also prevents conflicts and overlaps that often occur with fragmented, parallel optimization runs. You can now easily select all service territories when you configure a scheduled optimization job without having to select each territory individually. Previously, you had to define boundaries between areas that needed to be optimized together, making workforce planning difficult. Lower system limits meant you had to reduce the number of service appointments or service resources processed in a single request, and configure multiple optimization jobs. This fragmentation was tedious and affected overall business performance.

**Where:** This feature is available in Lightning Experience and Salesforce Classic in Enterprise, Unlimited, and Developer editions with the Field Service managed package installed.

**How:** In Setup, go to Field Service Settings and verify that Field Service Enhanced Scheduling and Optimization is enabled. In the Field Service Admin app, go to Field Service Settings. Select **Optimization**, and then, in the Logic tab, select **Enable Dynamic Scaling**. Then select the **Scheduled Jobs** tab. For any job, you can select all service territories to be optimized in one group.

#### See Also

- [_Salesforce Help_: Set Up Optimization of Large Field Service Datasets with Dynamic Scaling](https://help.salesforce.com/s/articleView?id=service.pfs_enhanced_optimization_dynamic_scaling.htm&language=en_US)