DYNAMICS 365 AGREEMENTS + OPTIMIZATION ENGINE
Salesforce Field Service generates work orders from Maintenance Plans against customer assets in Salesforce. Maintenance Work Rules produce booking dates, incident types, service tasks, products and services on a defined cadence; the Dispatcher Console renders the result and Enhanced Scheduling and Optimization can fill configured scopes. That covers a wide band of Maintenance Plan service work cleanly. At thousands of recurring stops, with SLAs that vary by Maintenance Plan or incident, with cadence drift to keep capacity balanced, and where the recurring program interacts with reactive break-fix for the same resources, work-order generation is no longer the same thing as optimization. eLogii’s engine models task and route template groups as constraint inputs to the optimizer.
Use Maintenance Plans to schedule recurring service for your customers. Maintenance Plans generate work orders ahead of time so service is performed on a defined cadence.
From help.salesforce.com/sf.pfs_maintenance_plans. Salesforce Field Service positions the Maintenance Plan and the customer asset as the spine of recurring service. Maintenance Work Rules generate work orders on the right cadence. Constraint-aware optimization across thousands of generated stops with interacting SLAs is its own decision layer. Verified June 2026.
Salesforce covers recurring service against the customer-asset base through Maintenance Plans:
The platform tracks the parent Maintenance Plan and the child work orders, holds time on the Dispatcher Console, manages the contract documentation, and runs the route calculation between assigned stops (or fills the board with Enhanced Scheduling and Optimization within a configured scope). The vocabulary is generation-first: produce the work orders from the Maintenance Plan, hold them on the Dispatcher Console, manage the contract paperwork, route between them.
What neither the Dispatcher Console nor Enhanced Scheduling and Optimization positions as the lead capability is constraint-aware optimization across the generated work orders at full scale. The recurring program at scale isn’t just a calendar problem; it’s an assignment problem where SLAs interact (Maintenance Plan anniversaries, quarterly preventive cycles, customer service contracts), cadences drift, skill requirements pin specific resources to specific assets, and capacity has to balance across the recurring program and the daily reactive break-fix.
The recurring programs that outgrow the Dispatcher Console are concrete:
In each case, the engine doesn’t replace Salesforce’s work-order generation from Maintenance Plans. It optimizes what the generation produces.
A commercial maintenance service organization running monthly, quarterly and annual PMs across a portfolio of customer sites. Fifty-five engineers in the field. Around 3,500 recurring work orders per month generated from Maintenance Plans, plus daily reactive break-fix for the same engineers. SLA windows vary by Maintenance Plan: anniversaries pinned to fixed dates, calibration on a hard 6-month cycle, regulatory inspections within calendar months, commercial programs at four-week intervals.
Salesforce Field Service generates the recurring work orders cleanly: stops appear on the Dispatcher Console at the right cadence, Salesforce Field Service mobile app carries the job sheets and PM checklists, completion data flows back to Salesforce reports and CRM Analytics. The planning task that grows past the dispatch surface is the balancing: reactive break-fix for the same engineers landing on top of recurring work orders; cadence drift to keep capacity even across the month; SLA windows that need protection from the optimizer rather than from a dispatcher spotting them in time. Enhanced Scheduling and Optimization can be configured for a single territory and a stable scope, but expanding it to span the Maintenance Plan program plus reactive break-fix across multiple territories turns brittle. Template-group optimization absorbs cadence drift within rules, protects SLA-locked stops, balances against reactive, and outputs one plan that’s already reconciled across the book. The Maintenance Plan and customer-asset data model stays in Salesforce Field Service; eLogii owns the optimization across it.
The workaround is the same as for the wider planning problem: the dispatcher carries it, with Enhanced Scheduling and Optimization in a supporting role within a scope. The generated work orders appear on the Dispatcher Console; the dispatcher assigns them to engineers, balances against reactive break-fix, allows cadence drift to keep capacity even, and signs off on the day. At small recurring books, this is straightforward. At several thousand recurring work orders a month, with SLAs and cadences interacting, the dispatcher becomes the optimizer. The friction shows up as SLA misses on specific Maintenance Plans, drive-time creep on the recurring book, and over-reliance on the one or two dispatchers who know the recurring rules best.
Recurring programs are modeled as task and route template groups feeding the optimizer. Each template carries the cadence, skill requirements, SLA windows and depot rules; the optimizer treats them as first-class inputs alongside the daily flexible work.
Salesforce Field Service stays in place as the system of record for the work order, customer asset, Maintenance Plan and inventory. Work-order generation from Maintenance Plans continues to run in Salesforce Field Service. eLogii reads the generated work orders, plus the reactive break-fix, plus the service resource / vehicle / territory model, runs the optimization across them, and writes back optimized bookings and ETAs.
Most teams complete the connector build in 3 to 5 weeks. Typical first wave: the recurring program that is leaking the most against SLAs today, or the contract book where cadence interactions are hardest.
30-minute custom simulation with your actual Maintenance Plan book, service resources and SLAs. Projected savings in drive time, SLA hit rate and dispatcher hours.
Yes, at the workflow layer. Maintenance Plans in Salesforce Field Service model recurring service against customer assets, generating booking dates and work orders at the right cadence with incident types, service tasks, products and services pre-populated, and entitlement validation tied in. The assignment and route between the generated work orders is then handled by the Dispatcher Console, with Enhanced Scheduling and Optimization filling configured scopes. What neither positions as the lead capability is constraint-aware optimization across thousands of recurring work orders with interacting SLAs, cadences and skill requirements, balanced against daily reactive break-fix for the same resources in one solver run. That decision layer is where eLogii adds value.
Maintenance Plan work-order generation: produce a list of work orders at the right cadence (monthly PMs, quarterly preventive, weekly commercial maintenance) against customer assets and incident types. Recurring program optimization: take the generated work orders, plus the daily reactive break-fix, plus the resource pool, plus the SLAs and cadences, and decide assignments and routes that respect all of them at once. Salesforce Field Service does the first cleanly. eLogii does the second, modeled directly through task and route template groups that feed the optimizer as constraint inputs.
When the recurring program runs to hundreds or thousands of work orders per month, when SLAs vary by Maintenance Plan or incident, when cadence drift (a stop shifting from week 1 to week 2 to keep capacity balanced) becomes a planning task, when Enhanced Scheduling and Optimization scopes can’t span the Maintenance Plan program plus reactive break-fix in one run, and when the recurring program interacts with daily reactive break-fix for the same resources. PM programs across hospital networks, multi-site PMs for industrial customers, recurring commercial maintenance contracts, inspection programs across regions: each of these hits the optimization decision layer rather than the work-order generation layer.
Through task and route template groups: weekly, monthly, quarterly and bespoke cadences are modeled directly as inputs to the optimizer. Each template carries skill requirements, time-window constraints, SLA targets and cadence rules. When the run happens, the optimizer balances the recurring program against the daily flexible work, protects SLA-locked stops, allows cadence drift within rules, and outputs one consistent plan. Bristow & Sutor routes 200,000+ recurring case visits per year on eLogii.
Custom integration against the Salesforce Platform REST API and eLogii’s REST API. eLogii reads Maintenance Plans and the generated work orders from Salesforce, plus the daily reactive break-fix and the service resource / vehicle / territory model. The optimization run considers them together. Bookings and ETAs are written back to Salesforce; The Salesforce Field Service mobile app picks up the assignments. Completion data flows back to the work-order record. Typical connector build: 3 to 5 weeks.
Last updated: June 2026. Salesforce Field Service scope is drawn from Salesforce Help: Maintenance Plans and the Salesforce Field Service overview. eLogii capabilities documented at elogiiapidocs.apidog.io.
Custom simulation
A 30-minute working session with our solutions team. We take a sample of your real jobs, depots, vehicles and SLAs, run them through the eLogii engine, and show you the projected delta against how you plan today. No slides, no generic benchmarks.
