How To Go From Insight To Action Using Dispatch Analytics For FSM Operations


Kevin Urrutia




July 10, 2024

Only adopting digital tools for automating your field service business is not enough. It’s almost rare for you to automate a workflow and then expect it to work 100% the way you want it to.


But how does one know what your current automated workflow can get better?


This is where analytics come into the picture.

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For field service businesses, using analytics for scheduling and dispatching automation can hold a goldmine of insights. Dispatch analytics helps you optimize dispatch processes, enhance resource allocation, and ultimately deliver superior customer service — read more to learn how.

How does dispatch analytics work?


Usually, your dispatch software may include an additional analytics feature to help you capture data and gather insights. Or else, you can choose field service management software with integration capabilities to use third-party analytics tools for analyzing dispatch data.


At its core, dispatch analytics involves collecting, analyzing, and interpreting data related to dispatching activities. This includes a range of metrics across response times, technician availability, travel distances, job durations, and customer satisfaction ratings.

How does dispatch analytics help make smarter decisions?


You can implement dispatch analytics in three key areas of scheduling and dispatching operations:


1. Improve efficiency of dispatch


One key aspect where dispatch analytics proves invaluable is in enhancing dispatching efficiency.


It analyzes historical data on job types, locations, and technician skills to optimize dispatch schedules. It results in minimizing travel time and maximizing productivity.


Dispatch analytics enables real-time optimization of dispatch schedules. As new service requests come in and circumstances change throughout the day, dispatchers can dynamically adjust schedules to accommodate emerging priorities.


For example, if a high-priority emergency arises, dispatch analytics can identify the nearest available technician with the appropriate skills and reassign them to address the issue promptly.

2. Resource optimization


Dispatch analytics helps you optimize your inventory management workflows where it ensures the most required resources are well-stocked as per demand.


Dispatch analytics also analyzes workload distribution patterns over time and identifies opportunities to redistribute tasks more evenly. Doing so helps prevent overburdening certain individuals while underutilizing others.

3. Predictive maintenance for assets and customers


Dispatch analytics enables organizations to adopt a proactive approach to maintenance through predictive analytics.


This means dispatch software will analyze equipment performance data and identify early warning signs of potential failures. Then you can dispatch technicians to address issues before they escalate into costly breakdowns.


You can do the same for customers, wherein if you provide any equipment maintenance services, you can anticipate breakdowns and prompt them to book your services.


How do you implement dispatch analytics for your field service business?


While the benefits of dispatch analytics are clear, the successful implementation of such systems requires careful planning and execution.


Here are some key steps to consider:

Step 1: Integrate and centralize data


The first step is to ensure seamless integration of data from various sources. Consider your CRM systems, IoT devices, customer feedback collection tools, and more for the same. Then choose a dispatch software of field service management solutions to consolidate disparate data streams into a centralized analytics platform.


With this, you will have good visibility into incoming data to ensure your analytics are accurate.

Step 2: Decide on performance metrics


You must mark your key performance indicators across dispatch operations so that you can measure and compare them for improvement. These may include KPIs such as response times, on-time arrivals, job completion rates, first-time delivery rates, or net promoter scores. Then, based on your current KPIs, strategize on how you can improve them.

Step 3: Choose a suitable dispatch software with an analytics feature


Choose a dispatch or FSM software that provides advanced analytics features using machine learning and predictive modeling. This helps further enhance the effectiveness of dispatch analytics.




It helps anticipate future demand, optimize resource allocation, and even identify emerging service trends before they become apparent through traditional analysis methods.


Step 4: Plan for continuous improvement


Finally, implementing a culture of continuous improvement is essential to maximize the value of dispatch analytics over time. For this, regularly review performance metrics and take feedback from both field service technicians and customers.

Zuper’s analytics help improve scheduling and dispatching


Zuper is a field service management software that provides AI-powered analytics solutions across field service workflows. This includes dispatch analytics features — book a demo to learn more about how it can help you make smart dispatch decisions.


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