Service policy changes cascade through open work orders, dispatch schedules, billing rules, and SLA commitments
The Impact Intelligence Verification Graph Engine (VGE) maps service operation dependencies across:
- Work orders, service appointments, and dispatch schedules
- Technician assignments and skill matrix rules
- Customer contracts, SLA tiers, and billing configurations
- Checklists, mobile workflows, and field procedures
Preview mode lets you model SLA revisions, pricing changes, and checklist updates before field deployment.
SLA cascades through open work orders
See every affected resource before updating a tier:
- Open work orders and scheduled appointments
- Customer commitments and coverage windows
- Invoice rules and service-credit exposure
Pricing changes propagate to active contracts
See which agreements are impacted by rate changes:
- Active work orders with unbilled labor lines
- Recurring service agreements and budget caps
- Customer quotes requiring regeneration
Checklist updates affect dispatched technicians
Preview field impact before updating procedures:
- In-progress work orders failing new closeout criteria
- Mobile app workflows requiring updates
- Retraining or redispatch requirements
Console preview
Change intelligence report
Seed change
SLA policy revision: P1 response window 4h to 2h - 14 open work orders
Change impact
29 of 160 nodes (18%)
across 4 domains
Severity hotspots
4
critical
NRE estimate
$38K – $78K
likely $56K
Schedule delta
+7d
critical path
Impact cascade / sample path
SLA commitment - 14 open P1 work orders
via service_management
6 dispatch schedules need replanning
via dispatch
3 technician certifications need renewal
via workforce
4 billing milestones affected
via billing
2 customer escalation paths updated
via customer_management
1 another SLA revision overlaps this service region
- └─ SLA-0412 Parts kit pre-staging policy change - Tier 1 accounts 3 shared nodes approved, pending
Verification pack / draft
- 14 work order SLA re-assessments
- 6 dispatch schedule replans
- 4 billing milestone adjustments
- 3 technician certification renewals
Cost estimate: NRE $38K – $78K (likely $56K)
- ├─ Technician overtime: $14K – $22K (P1 coverage gap during transition)
- ├─ SLA penalty exposure: $8K – $18K if response window breached during rollout
- ├─ Dispatch re-routing: $4K – $8K (14 open work orders reassigned)
- ├─ Schedule penalty: +7d delays regional rollout by 1 week
The problem
A service policy change seems straightforward until it touches open work orders, scheduled appointments, billing rules, and contract SLAs
Service and field operations involve complex dependencies between SLA tiers, work order lifecycles, dispatch schedules, billing milestones, customer contracts, and field technician workflows. A seemingly minor change to one component can cascade through the entire service delivery chain, affecting open work orders, scheduled appointments, billing accuracy, and customer satisfaction.
Hidden cost of blind changes
- SLA coverage change from 24x7 to 8x5: 45 open work orders fall outside new coverage windows, 12 dispatched technicians require schedule recalculation, 3 invoice rule configurations need threshold updates, service-credit exposure rises across 8 customer contracts
- Hourly rate change for premium tier: unbilled labor lines on 23 active T&M work orders require re-rating, 6 recurring service agreements exceed budget caps requiring approvals, 14 customer quotes need regeneration, entitlement price lists out of sync
- Installation checklist step addition: 34 in-progress installations fail closeout criteria, 9 mobile app workflows require updates, 5 completed work orders require additional documentation, grandfathering vs migrate decision needed per customer
- Dispatch territory reorganization: 67 scheduled service appointments cross new territory boundaries, 18 technician assignments violate skill matrix rules, 12 emergency response SLAs become unachievable, customer preferred-tech assignments break
Key capabilities
Active intelligence for services + field changes.
SLA cascade analysis
Trace SLA tier changes through open work orders, scheduled appointments, dispatch routing, billing milestones, and customer contract commitments to identify conflicts before deployment.
Work order impact mapping
Visualize how service configuration changes propagate through open work orders, service appointments, technician assignments, parts reservations, and billing milestones across the work order lifecycle.
Billing milestone and invoice-rule propagation
Preview how pricing, SLA, or service package changes affect billing milestones, invoice hold rules, time tracking rules, and revenue recognition for active work orders.
Dispatch schedule validation
Check territory changes, technician availability updates, or SLA revisions against scheduled service appointments, route optimization, and emergency response commitments.
Checklist revision impact
Identify in-progress work orders, mobile app workflows, and field technician procedures affected by installation, maintenance, or inspection checklist updates.
Customer contract traversal
Map service changes across recurring agreements, master service contracts, warranty terms, and entitlement policies to prevent SLA breaches and billing disputes.
Time tracking rule changes
Analyze how labor rate, overtime policy, or billable activity changes cascade through active timesheets, work order budgets, and payroll integrations.
Warranty and entitlement verification
Preview how warranty policy, parts coverage, or labor entitlement changes affect open claims, scheduled maintenance, and customer self-service portals.
How it works
From change signal to verified action.
Define the service change
Specify the SLA tier, pricing model, service checklist, dispatch territory, or warranty policy you're planning to modify, along with the scope (specific customers, service types, or geographic regions).
Traverse service dependencies
Impact Intelligence performs an impact traversal across work orders, service appointments, technician assignments, customer contracts, billing rules, dispatch schedules, and field workflows to map every connection to your change.
Analyze work order lifecycles
The system evaluates how your change affects open work orders, scheduled service appointments, parts reservations, billing milestones, and technician productivity across the full work order pipeline.
Check SLA and contract commitments
Validate that your change doesn't violate customer SLA terms, recurring service agreements, warranty entitlements, or contractual response time commitments.
Preview billing and revenue impact
See how pricing, time tracking, or billing rule changes propagate through active invoices, time-and-materials work orders, fixed-price agreements, and revenue forecasts.
Identify dispatch and routing conflicts
Detect territory boundary violations, technician skill matrix mismatches, service appointment scheduling conflicts, and emergency response SLA failures caused by your change.
Generate field deployment guidance
Receive prioritized action lists: which work orders to update, technicians to notify, customers to contact, mobile app workflows to refresh, and billing rules to reconfigure.
Hybrid graph model
Impact Intelligence models service operations as a directed graph where SLA tiers, work orders, service appointments, customer contracts, dispatch schedules, billing rules, and field technician workflows form nodes. Edges represent dependencies like work order references, SLA commitments, invoice triggers, technician assignments, entitlement policies, and parts reservations. This structure enables precise impact analysis for service configuration changes.
Work order references SLA tier
Open installation work order references 4-hour response time commitment
Service appointment depends on dispatch territory
Scheduled service appointments constrained by technician service zones and travel time calculations
Invoice rule triggers on service milestone
Invoice generation fires when installation checklist reaches 'Customer Acceptance' step
Services + Field impact scenarios
Real change scenarios in services + field.
Impact Intelligence adapts to your domain’s change patterns, compliance frameworks, and verification workflows. These are representative output examples from the VGE computation pipeline.
Services + Field
Prevents SLA breaches, customer dissatisfaction, billing disputes, and emergency redispatch situationsTrigger
SLA tier revision
Impact
Update SLA documentation, hope open work orders don't breach commitments, manually check customer contracts for violations
Verification Pack
Preview which 45 open work orders, 12 dispatched technicians, 3 invoice rules, and 8 customer contracts are affected; receive prioritized remediation plan with customer notifications
Metrics
Prevents SLA breaches, customer dissatisfaction, billing disputes, and emergency redispatch situations
Services + Field
Prevents revenue leakage, customer billing disputes, contract violations, and finance reconciliation issuesTrigger
Pricing model change
Impact
Apply new rates to future work orders, discover unbilled labor on active T&M work orders is under old rates, manually reconcile customer quotes and recurring agreements
Verification Pack
See which 23 active work orders need re-rating, 6 recurring agreements exceed budget caps, 14 quotes need regeneration; generate customer communication templates and billing adjustment workflows
Metrics
Prevents revenue leakage, customer billing disputes, contract violations, and finance reconciliation issues
Services + Field
Prevents closeout failures, warranty claim rejections, customer disputes, and technician confusion in the fieldTrigger
Service checklist update
Impact
Push new checklist to mobile app, discover in-progress installations fail closeout criteria, manually retrain technicians and update documentation
Verification Pack
Identify 34 in-progress installations affected, 9 mobile workflows requiring updates, 5 completed work orders needing additional documentation; schedule technician retraining and customer notifications
Metrics
Prevents closeout failures, warranty claim rejections, customer disputes, and technician confusion in the field
Services + Field
Prevents appointment cancellations, SLA breaches, technician skill mismatches, and customer relationship damageTrigger
Dispatch territory reorganization
Impact
Redraw territory boundaries, reassign technicians, discover 67 scheduled service appointments cross new zones, manually reschedule and notify customers of technician changes
Verification Pack
Preview appointment conflicts, skill matrix violations, SLA failures, and preferred-tech disruptions; generate optimized reassignment plan with minimal customer impact
Metrics
Prevents appointment cancellations, SLA breaches, technician skill mismatches, and customer relationship damage
Services + Field
Prevents warranty claim disputes, customer trust erosion, parts cost overruns, and legal liability exposureTrigger
Warranty policy change
Impact
Update warranty terms in system, discover open claims no longer covered, manually review entitlements and notify customers of coverage gaps
Verification Pack
See which open claims, scheduled maintenance, parts coverage, and labor entitlements are affected; generate customer grandfathering strategy and policy transition timeline
Metrics
Prevents warranty claim disputes, customer trust erosion, parts cost overruns, and legal liability exposure
Impact Intelligence for Services + Field
Operational scale that makes impact analysis possible.
VGE runs on tenant-owned data: schema depth, API breadth, and deterministic telemetry that keeps change reviews consistent.
Domain providers
15+
5 cross-industry baseline + 10 domain-specific providers (composition structures, compliance, verification, 3D/geometric, procurement, inventory, capital assets, execution chains), each self-describing with SemVer and cost tiers.
Sync analysis
≤2s
Typical graph traversal (≤1K nodes) with batch-first providers and per-request caching.
Async analysis
≤30s
Complex traversals (≤10K nodes) with optional Redis acceleration and per-provider timing.
Impact demo
Impact Intelligence for Services + Field
Preview change impact, severity scoring, and verification packs before approvals.
Change impact
29 nodes
Projected change
Severity hotspots
4
Projected change
NRE estimate
$56K
Projected change
Schedule delta
+7d
Projected change
Sample finding
See every affected resource before updating a tier:
Impact cascade
Define the service change
Work order references SLA tier
Service appointment depends on dispatch territory
Invoice rule triggers on service milestone
API preview
Schema-stable endpoints for impact intelligence.
Impact Intelligence is designed as a tenant-owned API surface with preview-first semantics, deterministic run snapshots, and export-ready results.
Preview vs apply
Every request can run in preview mode to generate impact results without mutating data. Apply mode uses idempotency keys to persist verification packs safely.
View developer docsPOST Start impact analysis
Seed an impact analysis for an SLA revision, pricing change, or dispatch territory reorganization.
POST /api/v1/change-controls/{id}/impact/runThe change request (created separately) carries the change details: SLA tier P1-EMERGENCY coverage changed from 24×7 to 8×5, scope limited to region NE-METRO, affecting service contracts MSA-4401 through MSA-4418.
Request
{
"detect_collisions": true
}Response
{
"schema_version": "vge.graph_result.v1",
"run_id": 387,
"nodes": [
{
"node_ref": {
"resource_type": "work_order",
"resource_id": 90214,
"display_name": "WO-90214 - HVAC compressor replacement",
"display_code": "WO-90214",
"status": "Dispatched",
"tags": [
"P1-EMERGENCY",
"NE-METRO",
"MSA-4401"
]
},
"severity": 0.94,
"depth": 1
},
{
"node_ref": {
"resource_type": "service_appointment",
"resource_id": 40821,
"display_name": "SA-40821 - HVAC compressor site visit (WO-90214)",
"display_code": "SA-40821",
"status": "Scheduled - 2024-03-15 09:00",
"tags": [
"P1-EMERGENCY",
"NE-METRO",
"Tech J. Rosales"
]
},
"severity": 0.92,
"depth": 2
},
{
"node_ref": {
"resource_type": "dispatch_schedule",
"resource_id": 7031,
"display_name": "Route NE-METRO-07 - Tech J. Rosales (CERT-HVAC-401)",
"display_code": "DSP-7031",
"status": "Active - 6 appointments today",
"tags": [
"NE-METRO",
"8×5 coverage window"
]
},
"severity": 0.91,
"depth": 2
},
{
"node_ref": {
"resource_type": "billing_rule",
"resource_id": 5580,
"display_name": "BR-P1-RESP - Response time SLA invoice trigger",
"display_code": "BR-P1-RESP",
"status": "Threshold Mismatch",
"tags": [
"P1-EMERGENCY",
"24×7 window → 8×5 window"
]
},
"severity": 0.89,
"depth": 2
},
{
"node_ref": {
"resource_type": "customer_contract",
"resource_id": 4401,
"display_name": "MSA-4401 - Greenfield Medical Campus",
"display_code": "MSA-4401",
"status": "Active - P1 response clause §4.2",
"tags": [
"P1-EMERGENCY",
"NE-METRO",
"Penalty exposure"
]
},
"severity": 0.87,
"depth": 3
}
],
"edges": [
{
"source": {
"resource_type": "sla_tier",
"display_code": "P1-EMERGENCY"
},
"target": {
"resource_type": "work_order",
"display_code": "WO-90214"
},
"edge_type": "GOVERNS",
"provider": "service_management",
"label": "SLA commitment - 14 open P1 work orders"
},
{
"source": {
"resource_type": "work_order",
"display_code": "WO-90214"
},
"target": {
"resource_type": "service_appointment",
"display_code": "SA-40821"
},
"edge_type": "DISPATCHED_VIA",
"provider": "dispatch",
"label": "Route NE-METRO-07 exceeds 2-hr travel window"
},
{
"source": {
"resource_type": "work_order",
"display_code": "WO-90214"
},
"target": {
"resource_type": "billing_rule",
"display_code": "BR-P1-RESP"
},
"edge_type": "TRIGGERS",
"provider": "billing",
"label": "Response time invoice trigger references 24×7 coverage threshold"
}
],
"stats": {
"node_count": 29,
"edge_count": 43,
"provider_counts": {
"service_management": 14,
"dispatch": 8,
"billing": 4,
"contract": 3
},
"truncated": false,
"collisions": {
"collision_count": 0,
"collision_severity": "NONE"
}
}
}GET Retrieve impact snapshot
Get the full change impact with severity scores across open work orders, service appointments, dispatched technicians, billing rules, and customer contracts.
GET /api/v1/change-controls/{id}/impactResponse
{
"run_id": 387,
"status": "COMPLETED",
"summary": {
"node_count": 29,
"severity_hotspots": 4,
"severity_breakdown": {
"critical": 4,
"high": 9,
"medium": 11,
"low": 5
},
"top_affected_resources": [
"14 open P1 work orders fall outside new 8×5 coverage window",
"8 dispatch routes need schedule adjustment for 8×5 SLA",
"4 invoice rule triggers reference superseded 24×7 coverage threshold",
"3 customer contracts with P1 penalty clauses at risk"
]
}
}GET Explain proof path
Trace why a specific work order, SLA commitment, or billing rule is impacted, auditable at every dependency hop.
GET /api/v1/change-controls/{id}/impact/explain?node_key=...Response
{
"run_id": 387,
"target_node_key": "billing_rule:5580:head",
"path_node_keys": [
"sla_tier:P1-EMERGENCY:head",
"work_order:90214:head",
"billing_rule:5580:head"
],
"path_edges": [
{
"edge_type": "GOVERNS",
"provider": "service_management",
"label": "WO-90214 committed under P1-EMERGENCY 24×7 coverage"
},
{
"edge_type": "TRIGGERS",
"provider": "billing",
"label": "BR-P1-RESP fires on coverage window threshold, currently set to 24x7, new tier requires 8×5"
}
],
"notes": "2-hop path: SLA tier → work order → billing rule. Invoice trigger BR-P1-RESP validates coverage window against a 24×7 threshold that no longer matches the revised 8×5 P1 commitment."
}GET Detect cross-change collisions
Find where concurrent service changes create overlapping impacts on shared work orders or dispatch territories.
GET /api/v1/change-controls/{id}/impact/collisionsResponse
{
"collision_count": 2,
"colliding_change_ids": [
383,
391
],
"collision_severity": "MEDIUM",
"top_overlapping_nodes": [
{
"node_key": "dispatch_schedule:7031:head",
"severity": 0.91,
"change_ids": [
387,
383
],
"display": "Route NE-METRO-07 - overlaps with CC-383 (dispatch territory boundary realignment)"
},
{
"node_key": "work_order:90218:head",
"severity": 0.86,
"change_ids": [
387,
391
],
"display": "WO-90218 - overlaps with CC-391 (parts kit revision for HVAC field installs)"
}
]
}POST Generate rollout readiness pack
Generate SLA cascade reports, dispatch reassignment plans, and billing rule updates in preview or apply mode.
POST /api/v1/change-controls/{id}/verification-pack/generateRequest
{
"mode": "preview"
}Response
{
"proposed_validations": [
{
"validation_type": "document_review",
"validation_meta": {
"description": "Verify 14 open P1 work orders can meet revised 8x5 coverage window. Flag at-risk work orders for expedited dispatch or customer notification",
"affected_nodes": [
"work_order:90214:head",
"work_order:90215:head",
"work_order:90218:head"
],
"sla_tier": "P1-EMERGENCY",
"response_window_change": "24×7 → 8×5"
}
},
{
"validation_type": "inspection",
"validation_meta": {
"description": "Recalculate 8 dispatch routes in NE-METRO region. Validate technician travel times against 2-hr response commitment",
"affected_nodes": [
"dispatch_schedule:7031:head",
"dispatch_schedule:7032:head"
],
"technician_certs_required": [
"CERT-HVAC-401",
"CERT-ELEC-301",
"CERT-PLMB-201"
]
}
},
{
"validation_type": "data_validation",
"validation_meta": {
"description": "Reconfigure 4 invoice rule triggers: update coverage window threshold from 24×7 to 8×5 for P1 penalty calculations and invoice hold logic",
"affected_nodes": [
"billing_rule:5580:head",
"billing_rule:5581:head"
]
}
},
{
"validation_type": "checklist",
"validation_meta": {
"description": "Review 3 master service agreements with P1 penalty clauses. Confirm contract language permits response window reduction or initiate amendment process",
"affected_nodes": [
"customer_contract:4401:head",
"customer_contract:4409:head",
"customer_contract:4415:head"
]
}
}
],
"proposed_external_acknowledgements": [
{
"target_type": "CUSTOMER",
"target_id": 4401,
"reason": "MSA-4401 §4.2 penalty clause references 24x7 response. Amendment required before enforcing 8×5 window"
}
]
}POST Compute cost estimate
Estimate one-time change costs (dispatch reconfiguration, documentation updates, contract renegotiation) and recurring impact (rate changes, SLA penalty exposure) with min/likely/max uncertainty bounds.
POST /api/v1/change-controls/{id}/cost-estimateResponse
{
"estimate_id": 602,
"impact_analysis_run_id": 387,
"line_items": [
{
"cost_driver_type": "nre",
"description": "Route recalculation and technician reassignment: 8 NE-METRO routes require travel-time re-optimization for 2-hr SLA window",
"quantity": 8,
"unit_rate": 2800,
"cost_phase": "nre",
"min_cost": 18000,
"likely_cost": 22400,
"max_cost": 28000,
"confidence": 0.85
},
{
"cost_driver_type": "nre",
"description": "Customer contract renegotiation: 4 MSAs with P1 penalty clauses (§4.2) require amendment for 2-hr response commitment",
"quantity": 4,
"unit_rate": 4500,
"cost_phase": "nre",
"min_cost": 14000,
"likely_cost": 18000,
"max_cost": 24000,
"confidence": 0.72
},
{
"cost_driver_type": "nre",
"description": "SLA policy documentation, dispatch playbook, and technician field guide updates for P1-EMERGENCY tier",
"quantity": 1,
"unit_rate": 8200,
"cost_phase": "nre",
"min_cost": 6000,
"likely_cost": 8200,
"max_cost": 11000,
"confidence": 0.88
},
{
"cost_driver_type": "nre",
"description": "Invoice rule threshold updates: 4 triggers reconfigured, invoice hold logic revised, penalty calculation formulas updated",
"quantity": 4,
"unit_rate": 1850,
"cost_phase": "nre",
"min_cost": 5500,
"likely_cost": 7400,
"max_cost": 10000,
"confidence": 0.82
},
{
"cost_driver_type": "recurring",
"description": "Monthly incremental penalty risk: tighter 2-hr window increases expected P1 breach rate by 12% across NE-METRO contracts",
"quantity": 1,
"unit_rate": 3200,
"cost_phase": "recurring",
"min_cost": 1800,
"likely_cost": 3200,
"max_cost": 5400,
"confidence": 0.65,
"justification": "Historical P1 breach data for NE-METRO: 4.1% at 24×7 window, modeled 16.3% at 8×5 window across 14 active work orders"
}
],
"nre_range": {
"min": 43500,
"likely": 56000,
"max": 73000
},
"recurring_range": {
"min": 1800,
"likely": 3200,
"max": 5400,
"currency": "USD",
"description": "Monthly recurring SLA penalty exposure increase from tighter P1 response window"
},
"schedule_impact": {
"min_schedule_days": 5,
"likely_schedule_days": 7,
"max_schedule_days": 12,
"critical_path_nodes": [
"customer_contract:4401:head"
]
},
"confidence": 0.79,
"confidence_notes": "Estimate calibrated from your operational data. Contract amendment timelines are the primary uncertainty driver. MSA-4401 requires customer legal review.",
"justification_summary": "P1-EMERGENCY SLA coverage change (24×7 → 8×5) drives $56K one-time change cost: dispatch route re-optimization across 8 NE-METRO routes ($22.4K), contract amendments for 4 MSAs with penalty clauses ($18K), SLA documentation updates ($8.2K), and invoice rule reconfiguration ($7.4K). Customer contract amendment for MSA-4401 is the critical path at 7 days. Recurring monthly penalty exposure increases ~$3.2K due to reduced coverage window."
}GET Export impact graph
Export the full impact graph as JSON, CSV, or GraphML for connecting to FSM platforms, CRM systems, or billing tools.
GET /api/v1/impact-analysis-runs/{run_id}/export?format=graphmlPreview endpoints reflect the planned VGE surface. Final routes may adjust as the engine deploys to production.
FAQ
Common questions about Impact Intelligence for services + field.
How does Impact Intelligence handle field technician workflows?
Impact Intelligence connects to data from mobile workforce management systems to track which in-progress work orders, checklists, parts reservations, and technician assignments are affected by service configuration changes. When you update an installation checklist, the system identifies active installations using the old version, flags mobile app workflows requiring updates, and generates technician notification lists with training requirements. For dispatch territory changes, it previews service appointment conflicts, skill matrix mismatches, and route optimization impacts before redeployment.
Can it prevent SLA breaches when revising response time commitments?
Yes. Impact Intelligence traverses customer contracts, open work orders, scheduled appointments, and dispatch schedules to identify every SLA commitment affected by your change. If you change coverage from 24×7 to 8×5, the system flags open work orders that fall outside the new window, dispatched technicians whose service appointments can't be fulfilled in time, and customer contracts requiring amendment. You receive a prioritized remediation plan: which work orders to expedite, customers to notify, dispatch routes to recalculate, and contract terms to renegotiate.
How does billing analysis work for time-and-materials vs fixed-price work orders?
Impact Intelligence distinguishes between billing models and applies model-specific impact analysis. For time-and-materials changes (hourly rate increases, overtime policy updates), it calculates active timesheet impacts, work order budget overruns, and customer approval requirements. For fixed-price work orders, it checks scope change triggers, billing milestones, and profitability thresholds. When you change a labor rate, the system shows which T&M work orders need re-rating at the new effective date, which fixed-price jobs remain unaffected, and which recurring service agreements exceed approved budget caps.
Does it track warranty and entitlement coverage for open service claims?
Yes. Impact Intelligence maintains a warranty policy graph linking coverage terms, parts entitlements, labor allowances, and open service claims. When you revise a warranty policy (extending coverage periods, adding exclusions, or changing parts pricing), the system identifies affected open claims, scheduled maintenance under warranty, customer self-service entitlement checks, and parts procurement dependencies. You see which claims lose coverage, require customer approval for out-of-warranty billing, or need grandfathering under old policy terms.
How does it handle customer contract SLA tracking across recurring agreements?
Impact Intelligence models recurring service agreements, master service contracts, and SLA tiers as interconnected graph nodes. When you change an SLA parameter (response time, resolution window, coverage hours), the system traverses customer contracts to find every reference, including auto-renewal clauses, tiered pricing dependencies, and service-credit or penalty provisions. For a coverage change, you receive a report showing which contracts breach new terms, require renegotiation, face penalty exposure, or need customer notification with grandfathering options.
Can it optimize dispatch scheduling when reorganizing service territories?
Yes. Impact Intelligence connects to data from dispatch routing engines to preview territory reorganization impacts. When you redraw boundaries or reassign technicians, the system checks scheduled service appointments for territory conflicts, travel time violations, skill matrix mismatches, and emergency response SLA failures. You see which appointments cross new zones, which preferred-tech assignments break, which emergency response areas lose coverage, and which route optimizations become invalid. The analysis includes reassignment recommendations minimizing customer disruption and SLA risk.
How does it prevent revenue leakage from pricing model changes?
Impact Intelligence tracks billing milestones, invoice triggers, time tracking rules, and revenue recognition workflows for active work orders. When you change pricing (hourly rates, service package fees, parts markups), the system calculates revenue impact across open work orders, recurring agreements, and customer quotes. You see which work orders have unbilled labor at old rates requiring re-rating, which invoices require manual adjustment, which recurring agreements need repricing, and which quotes become invalid. The analysis includes revenue projection deltas and billing reconciliation workflows.
Does it support phased rollout of service configuration changes?
Yes. Impact Intelligence supports phased rollout strategies by customer segment, service type, geographic region, or work order status. You can preview impacts for each phase independently, schedule deployment windows to minimize disruption, and configure automated notifications for affected customers and technicians. For an SLA revision, you might roll out to new work orders immediately, migrate active low-priority work orders over 30 days, and grandfather premium customers under old terms. The system tracks rollout progress and flags phase-specific conflicts.