Example - Schedule Optimization
Summarize
Summary of Schedule Optimization Example
This guide details the configuration methods for the Schedule Optimization engine, enabling ServiceNow admins to efficiently manage task scheduling for agents. The optimization can be set to run overnight in batches, throughout the day based on events, or initiated on-demand from the Dispatcher Workspace. The goal is to maximize task completion while minimizing travel time for agents during their shifts.
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Key Features
- Batch Scheduling: Enables scheduling a larger number of tasks overnight. Admins can configure the frequency, start, and end times for batch processing.
- On-Demand Optimization: Dispatchers can activate optimization as needed, allowing for immediate task assignment adjustments.
- Intraday Scheduling: Configured to manage tasks during the day with specified processing windows for optimal agent performance.
Key Outcomes
By utilizing these configurations, organizations can effectively ensure that their agents complete more tasks within their shifts. The policies put in place allow for a focus on maximizing task assignments while reducing travel time, resulting in improved overall efficiency in task management.
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 |