Routing Used for Workforce Scheduling Travel Time Calculations

Point-to-Point Predictive Routing

Point-to-point predictive routing predicts travel times based on historical traffic patterns and routes appointments using exact location coordinates. Traveling from A to B at 8 AM can yield a different travel time prediction than when leaving at 11 AM, due to anticipated traffic variations. Point-to-point predictive routing also supports calculating routes that include transport by ferries. Transport by ferry is calculated at a fixed rate of 5 kmh (or 3.1 mph). Point-to-point predictive routing uses exact coordinates for more accurate travel time.

The data used by point-to-point predictive routing is provided by Field Service Maps, which uses its own algorithms based on road type to determine travel speed for time calculations. Because the dataset is local on Salesforce infrastructure, point-to-point predictive routing performs calculations quicker, which improves transaction times. Field Service Maps data updates regularly for more efficient and reliable schedules based on the latest real-world road network changes. Updates can adjust travel time calculations for some service appointments already on your schedule, creating schedule overlaps or rule violations. Run in-day optimization to realign appointments.

Point-to-point predictive routing supports these features:

• Travel modes per territory, resource, or both for accurate routing calculations based on transportation type, toll road preferences, and the presence of hazardous materials. The default travel mode is set to car, using toll roads, and not carrying hazardous materials.
• Travel time buffers that define the additional minutes required for activities other than driving, such as finding parking, unloading technical gear, or walking time in a building complex. The additional travel time is added to new service appointments when they’re scheduled or to preexisting appointments if the schedule changes. Buffers can also be defined per territory.

Aerial Routing Fallback

When Workforce Scheduling can’t calculate travel time with point-to-point predictive routing, the engine falls back to aerial routing to estimate travel time. Aerial routing uses the straight-line distance between two points and the configured travel speed. A route can be unfeasible with predictive routing if travel mode limitations apply, a location is more than 1.5 kilometers from an official road, or data coverage is partial. For example, a resource drives a truck but the route doesn’t allow trucks. Or, the assigned asset is located 2 kilometers from a road or in a new neighborhood.

The travel source used to calculate the travel time to the service appointment, resource absence, or home base appears in the Estimated Travel Time From Source and Estimated Travel Time To Source fields on the assigned resource or resource absence record.

Routing Considerations

Review some routing considerations.

• The Maximum Travel from Home work rule always uses aerial routing calculations regardless of point-to-point predictive routing.
• The routing dataset is regularly updated to enhance accuracy. As a result, travel times in preexisting schedules can experience minor adjustments and cause slight overlaps or gaps. However, the scheduling engine is designed to efficiently resolve any such conflicts.
• Point-to-point predictive routing is used regardless of the travel distance.
• Service resources must have their home base location geocoded so that the scheduling engine knows the resource’s start and end points.
• Service appointments must have their location geocoded for travel time to be calculated. If there’s no address (geocoding), no travel time is added to the schedule and the appointment can be done from anywhere.
• When you drag a service appointment onto the Gantt to be scheduled, the routing calculation depends on the chosen start time. The time of day can affect typical road speed measurements, for example.
• If you define Travel From Home (minutes) as part of the Service Resource Availability work rules, resources can travel before the start of the work day. This additional time is considered when calculating the departure time.
• If the engine can’t calculate travel time via point-to-point predictive routing, it uses aerial routing to estimate travel time. A route can be unfeasible with predictive routing if travel mode limitations apply, a location is more than 1.5 kilometers from an official road, or data coverage is partial. For example, the dispatcher wants to manually assign the work to Alan, as he’s the only available resource. Alan drives a truck, but the route that Alan is assigned to doesn’t allow trucks. Or, Alan is assigned to maintain an asset that’s located 2 kilometers from a road or in a new neighborhood. The travel source used to calculate the travel time to the service appointment, resource absence, or home base is automatically shown in the Estimated Travel Time From Source and Estimated Travel Time To Source fields for the assigned resource or resource absence.
• If the last service appointment of the day is at the same address as the service resource’s home base, the Approximate Travel Time From (Minutes) value on the Assigned Resource object is calculated on the second-to-last appointment. The Approximate Travel Time From (Minutes) value for the last appointment is zero.
• Point-to-point predictive routing is supported for both optimization and scheduling operations for travel of more than 100 kilometers.
• The availability of point-to-point predictive routing in a region depends on the map coverage level for that region.
• The routing dataset is regularly updated to enhance accuracy. Travel times in existing schedules can experience minor adjustments and cause slight overlaps or gaps. The scheduling engine is designed to efficiently resolve these conflicts.
• Check which territories are fully covered by point-to-point predictive routing in the list of navigable countries.