Using Big Data to Improve Field Service Operations | Blog | EnSight+

If you’ve read anything about operations or business improvement of late, chances are you’ve seen the mention of “big data.” There’s ongoing debate as to the origins of the term, but the most public story dates back to the 1990s, when a computer scientist named John Mashey supposedly coined the term. Despite this murky history, the definition of “big data” is clear.

Simply put, big data is large, complex data sets that are so voluminous in nature that traditional data-processing software can’t handle them. Big data is useful because more data points means more potential insights to glean. That’s what makes the promise of using big data so enticing for businesses like field service companies. Today, we’ll explore big data further, detailing a few of the top ways big data can help field service companies improve operations.

Streamline schedules and reduce inefficiencies

As mentioned, the reason why big data analytics provide leadership with a holistic view of operations at every level. With field service companies, this includes granularity such as the average mile-per-hour their fleet vehicles travel, to how long technicians spend at each appointment.

Related: Go Efficiency Hunting with Data Management

By reviewing that data, leadership can identify areas for improvement and reduce bottlenecks. For instance, technicians’ visit data may reveal that certain appointments always take less time than expected. To avoid technicians killing time in the truck waiting for their next appointment, schedulers can plan additional appointments or training sessions to better utilize the technician’s time.

Related: 5G Infrastructure and the Field Service Industry

Plan for the future

There’s no predicting the future, but big data is a useful planning tool. Big data and predictive analytics can be especially helpful when it comes to asset and inventory management. Let’s use company vans as an example. Most manufacturers recommend an oil change every three to five months, but this variation can effect maintenance schedules for individual vehicles. With big data, you can predict when that oil change is needed based on historical data. If your vehicles consistently need service every two months, that knowledge allows you to plan proactively.

Related: Prioritize Vehicle Health with Fleet Maintenance

The same concept applies to equipment and tools. Field service companies comb through data that illustrates how often equipment and tools are being replaced. Armed with this knowledge, company leadership can properly budget for purchases and hopefully avoid any unexpected surprises.

Make the right call when it counts

We’ve covered a few ways in which big data and analytics can assist field service businesses and operations. But what about employees themselves? Big data analytics can help improve employees’ working conditions, safety outcomes, and training as well. For example, reviewing historical data of technicians’ first-time fix rates can reveal correlations between current skills and training and time to complete a particular job.

Related: Field Service Management Guide to High First-Time-Fix Rates

Leadership can even incorporate rules when reviewing historical data. For example, assigning technicians to specific tasks based on a predetermined “passing grade” for first-time fix rates helps ensure tasks are completed on time and with proficiency. Providing employees with tasks that match their skills levels is a way to increase morale and provide opportunities for well-earned recognition.

Let EnSight+ supply you with the data you need

Big data and the field service management software from EnSight+ work hand in hand. EnSight+ is a cloud-based solution that helps companies like yours more effectively manage their mobile workforce. We’d be happy to discuss strategies for how to put your datasets to work. To learn more, book your demo today.


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