Wasting $157K on Manual Reports? Field Service Reporting in Odoo 18

HVAC company has 47 field technicians. Dispatch sends technician to customer site (AC repair). Technician completes job. Drives back. Fills paper form: Customer name, service performed, time spent, parts used. Submits to office. Office clerk types data into Excel. Takes 15 minutes per form × 247 jobs weekly = 61.75 hours data entry. Customer calls: "How was my service?" Manager checks Excel. Can't find record (clerk hasn't typed yet, or typo in customer name). Manager: "I'll call you back." Searches paper forms in filing cabinet. Takes 20 minutes. Finds form. Calls customer. Customer unhappy: "Service done 3 days ago. No follow-up?" Another scenario: Manager needs report: "How many jobs completed this month? Average time per job? Which technician fastest?" Clerk manually counts Excel rows. Filters by technician. Calculates averages in calculator. Creates charts in PowerPoint. Takes 4 hours monthly. Data wrong (missed 23 jobs, Excel formula broke). CEO: "Our technicians efficient?" Manager: "I think so?" (No real-time visibility). Customer satisfaction unknown (no feedback collected). Technician overtime disputed: "I worked 12 hours." Timesheet says 8 hours (no proof). Annual cost: $87K data entry + $47K lost customers (poor follow-up) + $23K disputed overtime = $157K field service chaos.

Odoo 18 Field Service fixes this: Create task (customer, service type, location). Assign to technician (mobile app receives task). Technician arrives, completes work, marks task "Done" in app. Auto-trigger: Send customer rating email (automation rule). Customer rates service (emoji: happy, neutral, sad). Feedback auto-saved in task chatter. Real-time reporting: Task Analysis dashboard. Filter by technician, date, service type. Metrics: Tasks completed, time spent vs estimated, progress, working days. Graphs: Bar, line, pie charts (auto-generated). Export to spreadsheet (one click). Pivot tables (drill-down analysis). Manager sees: Which technician busiest, average completion time, customer satisfaction scores. All real-time. No data entry. No paper forms. Here's how to use Field Service Reporting in Odoo 18 so you stop losing $157K annually to manual field service chaos.

What Field Service Reporting Does

Complete field service tracking: Create tasks → Assign technicians → Complete work → Auto-request customer ratings → Analyze performance → Real-time dashboards → Export reports.

Step 1: Set Up Customer Rating Automation

Auto-send rating requests when technician marks task "Done." Collect customer feedback without manual follow-up.

1. Go to Field Service → All Tasks
2. Switch to Kanban View
3. Hover over any stage column header (e.g., "In Progress", "Done")
4. Click the gear icon ⚙️ next to the + icon
5. Select Automation from dropdown
6. Automation page opens

Step 2: Create Automation Rule

1. Click New button
2. Configure automation rule:
   • Name: "Send Customer Rating on Task Completion"
   • Model: Project Task (auto-selected for Field Service)
   • Trigger: On Stage Change
   • Stage: Select "Done" (or final stage)
3. Under Actions, click Add an action
4. Configure action:
   • Action Type: Send Email
   • Email Template: Select "Project: Task Rating Request"
   • Template auto-includes rating links (emoji buttons)
5. Click Save & Close

What Happens Now

• Technician marks task "Done"
• Automation triggers instantly
• Email sent to customer (registered email on task)
• Email contains: Service details + Rating request with emoji buttons
• Customer clicks emoji (😊 Great, 😐 Okay, 😞 Bad)
• Redirected to rating page
• Can add text feedback
• Rating + feedback auto-saved in task chatter

Step 3: Create Field Service Task

1. Go to Field Service → All Tasks
2. Click New
3. Quick-create form appears:
   • Title: "AC Repair - Customer A"
   • Customer: Select customer
   • Assigned to: Select technician
   • Planned Date: Service appointment date/time
4. Click Add to create (or Edit for full form)

Full Task Form Details

1. Click task to open full form
2. Add additional details:
   • Project: Field Service project
   • Worksheet Template: Select service checklist
   • Customer Address: Service location
   • Tags: "HVAC", "Repair", "Urgent"
   • Description: "AC not cooling. Customer reports strange noise."
   • Allocated Hours: Estimated time (e.g., 2 hours)
3. Technician receives notification (mobile app)
4. Technician navigates to site, performs service

Step 4: Complete Task & Trigger Rating

1. Technician completes work
2. Opens task in mobile app (or desktop)
3. Fills worksheet (if configured):
   • Parts used
   • Actual time spent
   • Service notes
4. Changes task stage to Done
5. Automation triggers
6. Customer receives email:
   • Subject: "How was your service?"
   • Body: "We completed AC Repair at your location. Please rate our service."
   • Emoji buttons: 😊 😐 😞

Step 5: Customer Rating Process

1. Customer opens email
2. Clicks emoji (e.g., 😊 Great)
3. Browser opens rating page
4. Rating page shows:
   • Service details (task name, date, technician)
   • Selected emoji (pre-selected based on click)
   • Text field: "Add your feedback (optional)"
5. Customer types: "Technician arrived on time. Fixed issue quickly. Very professional."
6. Clicks Send Feedback
7. Rating saved

View Rating in Task

1. Go to task in Odoo
2. Open Chatter (message log at bottom)
3. Rating appears:
   • Customer name
   • Rating: 😊 (5 stars)
   • Feedback text
   • Timestamp
4. Visible to managers, dispatchers
5. Tracked in reporting

Step 6: Access Field Service Reporting

1. Go to Field Service → Reporting → Task Analysis
2. Dashboard opens with default view
3. Shows all field service tasks with metrics

Step 7: Analyze Task Metrics

Available Measures

• Count: Total number of tasks
• Allocated Hours: Total estimated time
• Hours Spent: Actual time logged by technicians
• Remaining Hours: Difference between allocated and spent
• Progress (%): Task completion percentage
• Working Days: Days from task creation to completion
• Days to Assign: Time from creation to technician assignment
• Days to Complete: Time from assignment to completion
• Customer Rating: Average satisfaction score

Group By Options

• Assigned to: See performance by technician
• Customer: Track services per customer
• Project: Analyze by service type
• Stage: Tasks in each status
• Date: Daily, weekly, monthly trends
• Tags: Service categories (HVAC, Plumbing, Electrical)

Step 8: Use Filters & Search

Example Filters

1. This Month's Tasks:
   • Click Filters
   • Select "Creation Date → This Month"
   • Shows only tasks created in current month
2. Specific Technician:
   • Search bar: Type technician name
   • Press Enter
   • Shows only that technician's tasks
3. Completed Tasks:
   • Filter: "Stage = Done"
   • Shows finished tasks only
4. High-Rated Services:
   • Filter: "Customer Rating ≥ 4 stars"
   • Shows satisfied customers

Step 9: Visualize Data with Charts

Bar Chart Example

1. Click Bar Chart icon
2. Configure:
   • Measure: Count (number of tasks)
   • Group By: Assigned to (technician)
3. Chart shows: Tasks per technician (bars)
4. Visual comparison: Who's handling most tasks

Line Chart Example (Trend Analysis)

1. Click Line Chart icon
2. Configure:
   • Measure: Count
   • Group By: Date → Week
3. Chart shows: Tasks completed per week (line graph)
4. Identify trends: Busy seasons, slow periods

Pie Chart Example (Distribution)

1. Click Pie Chart icon
2. Configure:
   • Measure: Count
   • Group By: Tags (service type)
3. Chart shows: Percentage breakdown by service type
4. Example: HVAC 45%, Plumbing 30%, Electrical 25%

Step 10: Export to Spreadsheet

Export Chart

1. Create desired chart (bar, line, pie)
2. Click Insert in Spreadsheet button
3. Popup appears:
   • Create new spreadsheet
   • Or select existing spreadsheet
4. Click Confirm
5. Chart inserted into spreadsheet
6. Accessible from Documents app

Export Pivot Table Data

1. Switch to Pivot View
2. Configure rows/columns:
   • Rows: Assigned to (technician names)
   • Columns: Stage (To Do, In Progress, Done)
   • Measures: Count, Hours Spent
3. Pivot table shows: Cross-tabulation (technician × stage × metrics)
4. Click Insert in Spreadsheet
5. Data exported with formatting

Pivot Table Actions

• Flip Axis: Switch rows and columns
• Expand All: Show detailed breakdown
• Download: Export as Excel file (offline analysis)

Real-World Reporting Examples

Example 1: Technician Performance

Example 2: Average Completion Time

Example 3: Customer Satisfaction

Example 4: Overtime Analysis

Real-World Impact

FAQs