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You can't improve what you don't measure, and in field service, it's easy to end up measuring the wrong things, or nothing at all. Without the right KPIs, problems like declining first-time fix rates, technician overtime, or shrinking margins can build for months before anyone notices the pattern.
Below are 12 field service KPIs worth tracking, why each one matters, and what a healthy number typically looks like for industrial service teams.
This measures the percentage of jobs resolved on the first visit, without needing a follow-up appointment. It's one of the clearest indicators of field service health, since every repeat visit costs money, delays the customer, and ties up a technician who could be on the next job. Leading teams typically aim for 75 to 85 percent or higher, depending on the complexity of the equipment involved.
Utilisation measures how much of a technician's paid time is spent on billable, productive work versus travel, admin, or idle time. Low utilisation usually points to scheduling inefficiencies or excessive travel time between jobs. Tracking this by individual technician also helps identify training gaps or workload imbalances across the team.
This is the time between a service request being logged and a technician arriving on-site. For industrial clients, slow response times can mean extended downtime and real financial impact, so this metric often ties directly into service level agreements (SLAs) and contract terms.
MTTR measures the average time it takes to fully resolve an issue once work begins, from diagnosis through to completion. A rising MTTR can signal that technicians lack access to asset history, documentation, or parts, all of which slow down diagnosis and repair.
This tracks how often jobs start and finish within their scheduled windows. Poor schedule compliance creates a ripple effect: one late job pushes back every appointment after it, frustrating customers and creating overtime costs. It's a useful early warning sign that scheduling assumptions (travel time, job duration estimates) need adjusting.
Closely related to first-time fix rate, this tracks how often a technician needs to return to the same job within a set window, often 30 days. A high repeat visit rate can point to rushed diagnostics, missing parts, or incomplete asset documentation, and it's often one of the most expensive hidden costs in field service operations.
This measures the volume of open, unscheduled work orders at any given time. A growing backlog signals that demand is outpacing capacity, whether that's due to technician shortages, inefficient scheduling, or seasonal spikes. Tracking backlog trends over time helps with both staffing decisions and customer expectation-setting.
This is the total cost, labour, parts, travel, and overhead, of completing an average work order. Tracking cost per job by job type or asset category can reveal where margins are thinnest, and where pricing, staffing, or process changes might be needed.
While much of field service KPI tracking is operational, customer satisfaction closes the loop on whether all that operational effort is actually translating into a good experience. CSAT is typically gathered through short post-service surveys and can be segmented by technician, job type, or region to spot patterns.
For industrial service teams managing critical equipment, this tracks the percentage of scheduled preventive maintenance completed on time. Falling behind on preventive maintenance is one of the clearest predictors of future breakdowns and unplanned downtime, so this KPI is often a leading indicator for equipment reliability more broadly.
This measures how often technicians have the parts they need on hand versus having to delay a job to source them. Parts shortages are a common, and often overlooked, driver of poor first-time fix rates and extended repair times, making this a useful metric to track alongside more technician-focused KPIs.
This ties field service performance back to the bottom line, tracking the total revenue generated per technician over a given period. It's a useful way to evaluate whether improvements in scheduling, utilisation, and first-time fix rate are actually showing up in financial performance, not just operational reports.
Tracking 12 KPIs is only useful if the data is easy to access, accurate, and reviewed regularly. Many industrial service teams struggle here not because they lack data, but because it's scattered across paper forms, spreadsheets, and disconnected systems, making it slow and error-prone to pull together a clear picture.
This is where a connected field service platform makes the biggest difference. When work orders, technician schedules, asset histories, and inspections all live in one system, KPIs like first-time fix rate, utilisation, and MTTR calculate themselves in real time, instead of requiring manual reporting at the end of each month. HINDSITE is built around this idea, giving service leaders visibility into the metrics that matter most, without adding extra admin work to get there.
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You can't improve what you don't measure, and in field service, it's easy to end up measuring the wrong things, or nothing at all. Without the right KPIs, problems like declining first-time fix rates, technician overtime, or shrinking margins can build for months before anyone notices the pattern.
Below are 12 field service KPIs worth tracking, why each one matters, and what a healthy number typically looks like for industrial service teams.
This measures the percentage of jobs resolved on the first visit, without needing a follow-up appointment. It's one of the clearest indicators of field service health, since every repeat visit costs money, delays the customer, and ties up a technician who could be on the next job. Leading teams typically aim for 75 to 85 percent or higher, depending on the complexity of the equipment involved.
Utilisation measures how much of a technician's paid time is spent on billable, productive work versus travel, admin, or idle time. Low utilisation usually points to scheduling inefficiencies or excessive travel time between jobs. Tracking this by individual technician also helps identify training gaps or workload imbalances across the team.
This is the time between a service request being logged and a technician arriving on-site. For industrial clients, slow response times can mean extended downtime and real financial impact, so this metric often ties directly into service level agreements (SLAs) and contract terms.
MTTR measures the average time it takes to fully resolve an issue once work begins, from diagnosis through to completion. A rising MTTR can signal that technicians lack access to asset history, documentation, or parts, all of which slow down diagnosis and repair.
This tracks how often jobs start and finish within their scheduled windows. Poor schedule compliance creates a ripple effect: one late job pushes back every appointment after it, frustrating customers and creating overtime costs. It's a useful early warning sign that scheduling assumptions (travel time, job duration estimates) need adjusting.
Closely related to first-time fix rate, this tracks how often a technician needs to return to the same job within a set window, often 30 days. A high repeat visit rate can point to rushed diagnostics, missing parts, or incomplete asset documentation, and it's often one of the most expensive hidden costs in field service operations.
This measures the volume of open, unscheduled work orders at any given time. A growing backlog signals that demand is outpacing capacity, whether that's due to technician shortages, inefficient scheduling, or seasonal spikes. Tracking backlog trends over time helps with both staffing decisions and customer expectation-setting.
This is the total cost, labour, parts, travel, and overhead, of completing an average work order. Tracking cost per job by job type or asset category can reveal where margins are thinnest, and where pricing, staffing, or process changes might be needed.
While much of field service KPI tracking is operational, customer satisfaction closes the loop on whether all that operational effort is actually translating into a good experience. CSAT is typically gathered through short post-service surveys and can be segmented by technician, job type, or region to spot patterns.
For industrial service teams managing critical equipment, this tracks the percentage of scheduled preventive maintenance completed on time. Falling behind on preventive maintenance is one of the clearest predictors of future breakdowns and unplanned downtime, so this KPI is often a leading indicator for equipment reliability more broadly.
This measures how often technicians have the parts they need on hand versus having to delay a job to source them. Parts shortages are a common, and often overlooked, driver of poor first-time fix rates and extended repair times, making this a useful metric to track alongside more technician-focused KPIs.
This ties field service performance back to the bottom line, tracking the total revenue generated per technician over a given period. It's a useful way to evaluate whether improvements in scheduling, utilisation, and first-time fix rate are actually showing up in financial performance, not just operational reports.
Tracking 12 KPIs is only useful if the data is easy to access, accurate, and reviewed regularly. Many industrial service teams struggle here not because they lack data, but because it's scattered across paper forms, spreadsheets, and disconnected systems, making it slow and error-prone to pull together a clear picture.
This is where a connected field service platform makes the biggest difference. When work orders, technician schedules, asset histories, and inspections all live in one system, KPIs like first-time fix rate, utilisation, and MTTR calculate themselves in real time, instead of requiring manual reporting at the end of each month. HINDSITE is built around this idea, giving service leaders visibility into the metrics that matter most, without adding extra admin work to get there.
