Most field service organizations track KPIs – but few track them by design. Metrics often live in silos: executives focus on revenue, managers on SLA compliance, and technicians on closing tickets.
In our Field Service KPI Framework, we outlined how every service organization’s performance revolves around three dimensions – Strategic, Customer, and Operational KPIs.
This article builds on that foundation by translating those categories into role-based dashboards:
- Strategic KPIs → owned by executives to steer profitability and long-term direction
- Customer KPIs → tracked by managers to ensure reliability and satisfaction
- Operational KPIs → managed by dispatchers and technicians to drive daily efficiency
Together, they form a single, connected performance view where strategy, experience, and execution reinforce each other. It’s also the foundation for our upcoming KPI of the Month series, starting with First Time Fix Rate (FTFR) next month.
The Hierarchy of Field Service KPIs
A well-structured KPI hierarchy ensures that every decision, from boardroom strategy to field-level execution, is guided by connected, reliable data. In high-performing service organizations, KPIs form an information cascade where insights flow top-down for direction and bottom-up for feedback.
At the strategic level, executives focus on outcomes – how service contributes to growth, profitability, and customer retention. Metrics like service revenue ratio, contract renewal rate, and customer lifetime value provide a macro view of performance and alignment with business goals. These data points define the “north star” for service transformation.
Moving down to the tactical level, service and operations managers use a blend of performance and experience KPIs, such as first-time fix rate (FTFR), mean time to repair (MTTR), SLA adherence, and CSAT/NPS. Their job is to translate strategic intent into measurable operational goals, detect patterns across teams or geographies, and act before small inefficiencies become systemic problems.
At the operational level, dispatchers and technicians deal in execution metrics. Schedule adherence, travel time, job completion rate, parts accuracy, and technician utilization indicate whether the system is functioning efficiently on the ground. This layer generates the real-time data that feeds upward, helping managers and leaders validate assumptions and refine strategy.
It also helps avoid a common pitfall: measuring activity without impact. By connecting the dots between levels, organizations move from data collection to data intelligence, where every insight leads to action and every role contributes to transformation. For a deeper view of how these layers align with strategic, customer, and operational KPIs, refer to the Field Service KPI Framework. In the below sections we cover how the KPIs stack up by role.
Executive Dashboard (VP of Service, COO, CFO)
Executives care about outcomes- profitability, growth, and brand reputation. Their KPIs must combine financial performance, customer trust, and service scalability. The visual below highlights the most critical KPIs for service and operations leaders. These executive-level metrics connect strategy with execution, measuring how effectively field service contributes to growth, profitability, and customer loyalty. Aligned with the broader KPI framework, they balance strategic, customer, and operational priorities to help leaders make informed investment and transformation decisions.
| Primary KPIs | Calculation | What it Shows | Why it Matters |
|---|---|---|---|
| Service Revenue Growth | (Current − Previous Period Service Revenue) ÷ Previous Period Service Revenue × 100 | YoY or QoQ profitability trend for the service business | Reflects progress toward servitization and recurring revenue models |
| Cost to Serve (CTS) | Total Service Delivery Cost ÷ Number of Jobs (or Assets Serviced) | Average cost to deliver a service per asset or job | Critical efficiency metric; reveals if costs are scaling with revenue |
| Service Gross Margin | (Service Revenue − Service Delivery Cost) ÷ Service Revenue × 100 | Profitability of service operations after direct delivery costs | Links operations to P&L impact; a key leadership metric |
| Contract Attach Rate | (Number of Assets Under Service Contracts ÷ Total Installed Base) × 100 | Percentage of installed base covered by service contracts | Indicates success in building recurring service revenue and loyalty |
| Customer Satisfaction (CSAT / NPS) | CSAT: % (Satisfied Customers ÷ Total Surveyed) • NPS: % Promoters − % Detractors | Measures customer trust, loyalty, and perceived value of service | Leading indicator of renewals and long-term relationship health |
Cost to Serve and Service Margin should ideally move in sync.
A growing service business with stable or improving margins signals sustainable performance.
Secondary KPIs: First Time Fix Rate (FTFR), SLA compliance rate, predictive maintenance accuracy (AI KPI), service backlog value.
Service Manager Dashboard
Managers are the operational link between strategy and execution. They don’t just track performance but also control the levers that affect cost, efficiency, and customer experience. The visual below summarizes the key KPIs for service managers responsible for day-to-day delivery and customer experience. These metrics focus on operational efficiency, service quality, and customer outcomes. Together, they help managers translate strategic goals into measurable field performance and continuous improvement.
| Primary KPI | Calculation | What It Shows | Why It Matters |
|---|---|---|---|
| First Time Fix Rate (FTFR) | (Jobs fixed on first visit ÷ Total jobs) × 100 | % of jobs resolved on the first visit | Indicates process efficiency and training needs |
| Technician Utilization | (Job hours ÷ Total available hours) × 100 | % of time spent on active jobs | Core cost and workforce productivity driver |
| Mean Time Between Failures (MTBF) | Total uptime ÷ Number of failures | Average uptime between service calls | Reflects product/service reliability |
| Parts Availability Rate | (Jobs with all parts available ÷ Total jobs) × 100 | % of jobs completed without part delays | Impacts SLA adherence and repeat visits |
| SLA Compliance Rate | (Jobs within SLA ÷ Total jobs) × 100 | % of jobs completed within SLA | Key metric for revenue protection and reputation |
| Repeat Visit Rate | (Repeat jobs ÷ Total jobs) × 100 | % of jobs needing rework | Indicates root cause and diagnostic quality issues |
Managers should use these metrics not to police performance, but to identify systemic inefficiencies such as missing parts, poor data, or outdated processes that slow technicians down.
Secondary KPIs: Cost per Work Order (CPWO), Remote Resolution %, Training Hours per Technician.
Dispatcher & Planner Dashboard
Dispatchers are often the hidden cost controllers. They influence travel, time, and customer responsiveness -the biggest operational cost levers. The visual below outlines the essential KPIs that guide dispatchers in optimizing schedules, technician utilization, and response times. Rooted in the operational layer of the KPI framework, these metrics ensure the right job reaches the right technician at the right time while balancing resource efficiency with customer satisfaction.
| Primary KPIs | Calculation | What It Shows | Why It Matters |
|---|---|---|---|
| Schedule Adherence | (Jobs completed as per planned schedule ÷ Total scheduled jobs) × 100 | Accuracy of dispatch planning and execution | Improves labor efficiency; reduces overtime or idle technician time |
| Response Time | Time from service request creation to technician arrival | Speed of service response | Directly affects customer satisfaction and SLA compliance |
| Travel Time per Job | Total technician travel time ÷ Number of jobs | Average travel time between customer locations | Indicates route efficiency; impacts fuel and labor costs |
| Reschedule Rate | (Number of rescheduled jobs ÷ Total jobs) × 100 | Frequency of jobs requiring rescheduling | Highlights planning or parts readiness issues; major cost driver |
| Technician Distance-to-Job | Average distance between technician start point and assigned job | Geographic efficiency of technician–job matching | Supports territory optimization; reduces fuel, time, and emissions |
Enabling dispatchers with AI-assisted scheduling tools helps to predict best-fit technician assignments, reducing travel and improving FTFR. Even modest optimization can reduce cost-per-job by 10–15%.
Secondary KPIs: Job Acceptance Rate, Emergency Dispatch %, On time arrival rate.
Field Technician Dashboard
Technicians are the frontline value creators and their KPIs should enable, not control them. The visual below highlights the core KPIs that define technician performance and on-site service excellence. By empowering technicians with clear goals and the right data, organizations strengthen both efficiency and customer trust.
| Primary KPI | Calculation | What It Shows | Why It Matters |
|---|---|---|---|
| Job Completion Rate | (Completed jobs ÷ Assigned jobs) × 100 | Tasks completed per schedule | Measures reliability and accountability |
| First Time Fix Rate (Personal) | (First-visit fixes ÷ Personal total jobs) × 100 | Individual success on first visit | Reflects skill level and diagnostic capability |
| Average Repair Duration | Total repair time ÷ Number of jobs | Efficiency per job | Helps identify training or process gaps |
| Parts Usage Accuracy | (Accurate part uses ÷ Total parts used) × 100 | Correct parts used vs planned | Avoids rework and waste |
| Safety Compliance | % of jobs completed without safety violations | Adherence to safety protocols | Essential for compliance and trust |
| Customer Feedback Score | Average CSAT/NPS from closed jobs | Direct customer satisfaction metric | Links service quality to customer experience |
Use KPIs to equip technicians with data such as access to service history, AI-guided troubleshooting, or parts visibility, and not to micromanage performance.
When technicians feel trusted, FTFR and customer satisfaction both improve naturally.
The Emerging Layer: AI & Predictive KPIs
AI-based metrics are still nascent, but they’re shaping the future of service performance tracking. For mature organizations, these “readiness KPIs” can be monitored in parallel. These AI-driven field service KPIs help organizations assess predictive accuracy, optimization success, and data maturity, ensuring that AI not only automates, but also improves business outcomes.
| AI KPI | Purpose |
|---|---|
| Predictive Accuracy | How close AI forecasts are to actual failures — the foundation of proactive service. |
| Scheduling Optimization Success | Measures how effectively AI assigns the best-fit technician, balancing skills, location, and SLA priorities. |
| Data Coverage (%) | % of assets with usable, high-quality data available for prediction — a key enabler of model reliability. |
| AI Retraining Frequency | Indicates how often AI models are refreshed to maintain accuracy as conditions change. |
| Customer Sentiment Prediction Accuracy | Tracks how precisely AI anticipates satisfaction or churn, enabling proactive engagement. |
| Service Outcome Confidence Score | Reflects AI’s confidence level in its own recommendations — valuable for prioritizing human oversight. |
Treat these as development metrics, not operational goals. Over time, they’ll become integral to the service P&L just like CTS or FTFR.
Building a Balanced Service Dashboard
To build a truly effective dashboard:
- Blend financial, operational, and customer metrics, not just activity counts.
- Apply a top-down visibility structure:
- Executives: business outcomes
- Managers: process control
- Dispatchers: operational flow
- Technicians: enablement and performance
- Review KPIs quarterly not daily, to identify meaningful trends.
- Foster transparency across roles: each team should see why their metrics matter upstream.
Building a balanced service dashboard isn’t about tracking more metrics, it’s about tracking the right ones. When every KPI tells a connected story, data becomes direction, and service teams become true growth drivers.
