Example- Schedule Optimization

  • Release version: Yokohama
  • Updated January 30, 2025
  • 2 minutes to read
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    Summary of Schedule Optimization Example

    This example demonstrates how ServiceNow administrators can configure Schedule Optimization to efficiently assign tasks to agents, minimizing travel time and maximizing task completions within shifts. It highlights three configuration methods: batch processing overnight, intraday scheduling at intervals, and on-demand optimization via Dispatcher Workspace. The goal is to ensure agents complete the highest possible number of tasks without excessive travel.

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    Key Configurations

    • Core Settings: Define qualifiers, scheduling resolution, and maximum location points for map integrations.
    • Policies: Set active policies that prioritize maximizing assignments, minimizing travel time, and assigning earlier shifts with equal weighting.
    • Scheduling Attributes: Configure travel estimate providers, default policies, applicable task states, and assign relevant groups.

    Batch Optimization

    Admins can schedule batch runs overnight to process a large volume of tasks. This includes setting the schedule start date, run frequency (e.g., every 7 days), and batch timing (e.g., 10 PM to 3 AM). Batch scopes define assignment horizons and active scheduling attributes for targeted groups.

    Intraday Optimization

    Allows scheduling optimization jobs during business hours (e.g., 9 AM to 5 PM) to handle task assignments throughout the day. This includes specifying active configurations, default scheduling attributes, and enabling on-demand optimization for specific assignment groups.

    On-Demand Optimization

    Enables dispatchers to manually trigger optimization from Dispatcher Workspace. This requires enabling on-demand settings in scheduling attributes and intraday configurations for relevant assignment groups, providing flexibility for real-time task management.

    Practical Benefits for ServiceNow Customers

    • Improves agent productivity by maximizing task assignments within shifts.
    • Reduces travel time between tasks, optimizing operational efficiency.
    • Offers flexible scheduling options: batch processing, intraday updates, and on-demand triggers.
    • Supports targeted configurations for different geographic regions or teams.

    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

    Table 1. Schedule Optimization Properties
    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
    Table 2. Policies
    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)
    Table 3. Scheduling Attributes
    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

    Table 4. Batch
    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
    Table 5. Scope
    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
    Note:
    Select schedule now when the form is complete

    Intraday Optimization Configurations

    Table 6. Intraday 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

    Table 7. On-demand values in Scheduling Attributes configuration
    Field Value
    On Demand applicable policy West Coast Dispatcher
    Table 8. On-demand values in Intraday configurations
    Field Value
    Assignment group

    San Diego South - Enable On Demand = True

    San Diego North - Enable On Demand = True