March 31, 2021

3 Ways to Use Current Data to Improve Field Service Outcomes

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Field service companies generate masses of data from technicians, assets, equipment, customers, and logistics. If it’s not actively used to improve operations, that data becomes a figurative mound of untapped potential.

If you’re using paper-based methods or separate systems to house your data, you’re probably vastly overwhelmed at the amount of it. Investing in a field service management system gives you access to analytical reporting tools that centralizes and interprets the data for you.

But what good is having a tool if you don’t know how to handle the data within it? There’s a lot of potential there, but how can you take advantage of it to make your business run smoother and the customer experience better?

We’ve outlined 3 major ways to use the data you’re already generating to make insight-driven decisions and improve your field service outcomes. If you’re looking for a FSM software to house this data and give insight into how you can improve your operations, check out our Product Selection Tool. We’ll ask you a few basic questions to get an idea of what you’re looking for and then match you with five solutions we think you’ll love.

Which Field Service Management tool is right for you?

 

1. Schedule dynamically

First-come, first-serve is an extremely inefficient method, and both your customers and employees will feel the consequences of it. If you’re scheduling multiple appointments at any given time, the planning, scheduling, assigning, and forecasting of fieldwork can’t be done first-come, first-serve. Since there’s no data involved, it doesn’t take into account technician and part availability, cost, service priority, or job location.

Use the data provided by your FSM software, such as IndusTrack, to identify the best course of action for scheduling. This data takes into account:

  • The technician that is best-suited for the job, considering factors such as work skills, work areas, SLAs, and inventory
  • The optimal route for your field resources (more on this is a bit)
  • What parts are available and when
  • How the status of work in real time will be communicated to the customer (estimated time of arrival, delays, updates, etc.)

Using this data will ensure that the right field resource will be assigned to the right job at the right time with the right equipment. To make the most of dynamic scheduling, intelligently plan your routes, share the data with your team, and make the most of mobile data.

Route planning

Your workforce and their mobility is one of the most important factors in FSM. That’s why most FSM systems have extensive mobile features for scheduling, job management, and route planning.

Your current data can be used to plan intelligent routes. Route planning uses algorithms that consider the distance of the technician, accessibility, and geolocation data. It creates work rules based on scheduling priorities you’ve outlined and interacts with real-time traffic services to suggest the best route. Route planning minimizes the time your technicians are spending on the road, decreases delays, and improves overall efficiency.

Share the data

Big data is not just for top-level leaders within the FSM industry; every level of your business can use the insights your analytic reporting tool provides.

For example, dispatchers benefit from being able to see technician response and travel times. Parts managers benefit from knowing which time of year to keep parts in stock. Technicians benefit from knowing the skills needed for the job and the approximate time it will take to complete it. If you’re only sharing big data with high-level decision-makers, you’re missing the point behind making the most of the data in the first place.

Use mobile application data

Some of your most valuable data is sourced from your technicians on the front lines. Using a FSM system that has a mobile app, such as IFS, allows your mobile workforce to log all work order, scheduling, work estimate, checklist, and troubleshooting data they might encounter while on the field.

The beauty of gathering technician data is that it’s real-time data. The quicker the data is logged, the more accurate and valuable the resulting analytic reports are.

2. Be proactive about arising problems

By using predictive analytics technologies, including artificial intelligence and machine learning, you can define statistical models based on historical data. Combine this with the use of the internet of things (IoT), where connected devices sense each other, and your ability to predict and prevent problems before they emerge becomes a huge asset.

Predictive analytics will illustrate that you run low on a certain part when July rolls around. Instead of trying to compensate by overstocking that part for the entirety of the year, or stocking out only in July, you’ll know to stock more of that part only for that month.

As an added benefit, many FSM tools, such as Oracle Field Service Cloud, also provide early warning notifications and diagnosis of equipment issues days, weeks, or maybe months before failure. Monitoring your equipment can save loads of time and money on the front end.

Find inefficiencies

In addition to preventing arising problems, the technology built into your FSM system can find recurring problems or service bottlenecks, and subsequently isolate possible causes. Perhaps technicians are consistently double-booked for scheduled appointments, the same part has failed in multiple pieces of equipment, or a particular part of a work order is not being completed correctly. Your FSM system will alert you to these issues so you can make actionable decisions.

Using data to solve these problems eliminates subjectivity, reduces downtime, and saves time by spotting the exact pain point instead of sifting through what-ifs.

3. Create a better customer experience 

Customer satisfaction is critical to FSM success. A bad customer experience can lead to a bad online review, leading to a potential dip in new or returning customers. Using data can create new dimensions for customer satisfaction.

Make use of the predictive analytics we mentioned earlier to understand the needs of your customer base. It can access data about a client’s service history, equipment monitoring records, or other relevant issues and deliver it to the appropriate person.

With this data, a technician can arrive at a jobsite with a good idea of what the problem is, how to resolve it, and what parts are needed. This leads to less time spent on solving the problem, and an overall better customer experience than if the field resource went in with limited knowledge.

Consider qualitative data, too

Circling back to using mobile data collected from workers on the field, go beyond feeding only quantitative data into your intelligence platform—include qualitative data from your technicians, too. Your field resource is standing face-to-face with your customer. What is their body language like? Or the general tone of their voice about the service? Was it overall a positive or negative experience?

Including this exhaustive customer data will lend to creating better experiences for the future. If the customer was standoffish and made multiple comments about the technician being two minutes late, you’ll know this customer values timeliness. The next time a field resource is sent to that jobsite, they’ll know to get there early.

Need the right FSM tool to make the best use of your data?

If you aren’t aggregating your data in a field service tool, you could be missing out on valuable insights. Use our Product Selection Tool to get recommendations of the best FSM tool fit for your business.