Example- Schedule Optimization
Summarize
Summary of Schedule Optimization
The Schedule Optimization feature enables admins to effectively configure the optimization engine for scheduling tasks. This helps ensure agents complete as many tasks as possible during their shifts while minimizing travel time between tasks.
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Key Features
- Batch Scheduling: Admins can configure the optimization to run overnight in batches or throughout the day based on specific events.
- On-Demand Optimization: Dispatchers can initiate optimization from Dispatcher Workspace, allowing for immediate adjustments to task assignments.
- Policies and Attributes: Various settings can be configured to prioritize maximizing task assignments while minimizing travel time.
Key Outcomes
By implementing Schedule Optimization, organizations can expect:
- Increased efficiency in task completion for agents.
- Reduced travel time, allowing agents to focus more on tasks.
- Flexible scheduling that can adapt to real-time demands and changes.
This configuration allows for a streamlined approach to task management, enhancing overall operational efficiency within ServiceNow environments.
This example shows three different ways admins can configure the optimization engine to schedule tasks.
Admins can configure Schedule Optimization to run overnight in batches to schedule a larger number of tasks or throughout the day at selected intervals based on events. Admins can also enable dispatchers to initiate Schedule Optimization from Dispatcher Workspace by configuring on-demand optimization.
In this example, the organization is ensuring that agents complete as many tasks as they can during their shift without spending a lot of time traveling between tasks. A policy is configured to maximize assignments and minimize travel time. On-demand optimization is enabled for the dispatchers who are assigned to this group of agents.
Admin Core Configurations for Schedule Optimization
| Field | Value |
|---|---|
| Qualifier type for Schedule Optimization | Assignment Group |
| Number of seconds used for task scheduling resolution | 1 |
| Maximum number of location points allowed in a map provider call | 300 |
| Field | Value |
|---|---|
| Name | Maximum Assignments |
| Active | true |
| Constraints | Default values |
| Overall objectives | Maximize travel time (weight 1) Maximize task assignments (weight 1) Maximize assignments to earlier shifts (weight 1) |
| Field | Value |
|---|---|
| Name | West coast config |
| Active | True |
| Travel estimate provider | Beans.ai |
| Default policy | Maximum Assignments |
| Straight line estimate config | West Coast |
| Tasks | State is one of: Pending dispatch or Scheduled |
| On Demand applicable policy | West Coast Dispatcher |
Batch Optimization Configurations
| Field | Value |
|---|---|
| Name | West Coast weekly |
| Schedule start date | 2023-12-01 |
| Run frequency | Every 7 days |
| Batch start time | 22:00 |
| Batch end time | 3:00 |
| Field | Value |
|---|---|
| Name | West Coast-Next 7 days |
| Active | True |
| Scheduling attribute configuration | West Coast config |
| Rank | 1 |
| Assignment horizon offset | 00 |
| Assignment horizon range | Days 7 |
| Optimization Batch | West Coast weekly |
| Start date | 2023-12-01 |
| Batch start time | 22:00 |
| Batch end time | 3:00 |
| Assignment group | San Diego North |
Intraday Optimization Configurations
| Field | Value |
|---|---|
| Name | West Coast |
| Active | True |
| Default scheduling attribute configuration | West Coast config |
| Default | False |
| Flow | Schedule intraday jobs (default) |
| Default processing window | Workday 9:00-5:00 |
| Assignment group | San Diego South - Enable On Demand = True San Diego North - Enable On Demand = True |
On-demand Optimization configurations
| Field | Value |
|---|---|
| On Demand applicable policy | West Coast Dispatcher |
| Field | Value |
|---|---|
| Assignment group | San Diego South - Enable On Demand = True San Diego North - Enable On Demand = True |