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Universal Containers services customers in the public sector. When technicians are needed for repair jobs in government buildings, it is crucial that only technicians with the relevant security badge are selected for the job.
Which two configuration options can a consultant recommend to achieve the business requirement?
To filter resources based on strict criteria (like security clearance), you use Work Rules (Hard Constraints).
Option B is correct (Match Boolean): This is a simple, effective method for binary requirements. You place a checkbox on the Service Appointment (e.g., 'Requires Security Badge') and a corresponding checkbox on the Service Resource (e.g., 'Has Security Badge'). The Match Boolean Work Rule enforces that if the Appointment is checked, the Resource must also be checked.
Option E is correct (Extended Match): If the requirement is more complex (e.g., matching a specific type or level of badge), the Extended Match Work Rule is best. It allows you to match a field on the Service Appointment (or Work Order) to a related list or field on the Service Resource. For example, matching the 'Badge Type' required by the Government Account to the 'Badge Type' held by the Resource.
Note: While Skills (Option C) are also commonly used for this, the question specifically points toward Work Rule configurations (Boolean/Extended) often used for strict compliance attributes.
Universal Containers sells capital equipment that includes a 90-day warranty for repairs. They also offer a 'Preventative Maintenance Service Contract' for the purchase.
What data model and solution approach should a Field Service consultant recommend?
This option follows the standard Salesforce Field Service data model and best practices for the 'Lead-to-Cash-to-Service' lifecycle.
Option C is correct.
Assets: Standard automation (or CPQ) converts Opportunity Line Items into Asset records.
Warranties: Standard Asset Warranty or Entitlement records track the 90-day coverage.
Maintenance: If a recurring service contract is sold, the correct objects are Service Contract (the agreement) and Maintenance Plan (the schedule/generation engine). The specific assets covered are linked via Maintenance Assets.
Option A is manual and error-prone.
Option B recommends a custom object ('Capital Equipment') when the standard Asset object exists specifically for this purpose.
Option D puts lists on the Account, losing the granularity of which specific asset is covered.
Green Energy Solutions provide two types of services: 'New Installs' (high revenue, high priority with a 3 day SLA) and 'Inspections' (proactive, low priority activities due 3 months out). The company incurs a penalty for missing due dates which the service manager would like to avoid. However, not at the expense of a new install.
What should the consultant's recommendation be in such a case?
The goal is to prevent low-priority 'Inspections' from being ignored indefinitely until they miss their deadline, without permanently ranking them above high-value 'New Installs.'
Option B is correct (based on the scenario's specific constraints). By using automation to elevate the Inspection's priority to '1' (High) only when it is due 'tomorrow,' the system treats it as urgent only when necessary to avoid the penalty. Since 'New Installs' are also Priority '1', the two will compete on equal footing on that final day, ensuring the Inspection has a fighting chance to be scheduled alongside high-value work.
Option C (Dynamic Priority) is a standard solution for 'aging' work. However, the option states it caps the value at '2'. In standard SFS priority (where 1 is highest), a '2' will never beat a '1'. Therefore, the inspection would still likely be bumped by a New Install (Priority 1) even on its due date, leading to a penalty.
Option D ('Schedule Over Lower Priority') is used for emergency reshuffling, but does not inherently solve the prioritization logic between these two specific task types.
A Customer is outsourcing some of the maintenance work to third-party contractors (named contractors, not capacity based). Unlike internal employees who have consistent working hours (Mon-Fri, 8 am-5 pm), contractors' working hours vary from day to day.
The internal employees' availability is set with Operating Hours, while the contractors' availability is set with Shifts on top of these Operating Hours. As a result, on days where the contractor's workday ends at 4 pm, for some reason the contractors still show up as valid candidates for a visit scheduled to end at 5 pm.
What should a consultant change to prevent such behavior?
This issue arises because Salesforce Field Service calculates availability by combining Operating Hours AND Shifts. If a user has Operating Hours of 9-5, they are fundamentally 'Available' during that time. A Shift is typically used to add or extend availability (or define it if using specific settings), but standard Operating Hours often take precedence as the 'Base.'
Option A is correct. To have a resource's availability defined exclusively by variable Shifts, the best practice is to assign them a 'Shell' or 'Empty' Operating Hours record (one with zero time slots defined). With no base hours, the system looks only to the Shifts to determine when the resource is working. This ensures that if a Shift ends at 4 PM, the resource is truly unavailable at 5 PM.
Option B is administratively impossible (you cannot automate changing the STM Operating Hours record lookup daily without complex custom code, and it's not a standard practice).
What should a consultant recommend to help a customer with their initiative to reduce their carbon footprint?
Reducing a carbon footprint in field service is primarily achieved by reducing the fuel consumption and distance driven by the fleet.
Option B is correct. The Minimize Travel Service Objective calculates the travel distance/time for each potential appointment slot. By giving this objective the highest weight in the Scheduling Policy, the optimization engine will aggressively prioritize schedules that have the shortest routes, even if it means sacrificing other metrics (like 'ASAP' or 'Preferred Resource'). Shorter routes directly equate to less driving and lower emissions.
Option A (Remove ASAP) might help slightly by removing the urgency to book 'now' (which can cause inefficient routing), but it doesn't proactively optimize for low mileage like Option B does.
Option C (Maximum Travel Work Rule) is a hard limit (e.g., 'Don't travel more than 50 miles'). While it prevents extreme outliers, it doesn't optimize the routes within that radius.
