Field Service consists of “workers in the field” who perform various types of tasks. These can include things such as installation, repair, or maintenance of hardware. However, as technology continues to evolve we see the field service landscape evolving as well and expanding into other verticals such as education and healthcare. For the purpose of this post I am going to refer to “Field Service” as any service or task that is performed outside of company walls for a customer where a worker is required to physically visit the customer to complete the job.
Field Service Management (FSM) is simply how an organization decides to manage all of the different pieces of completing work in the field. This is no small task and requires organizations to track a lot of data to ensure they are delivering a quality service to their customers. Data that is frequently tracked in FSM can be seen in the list below:
As you can see in the list above there is a lot of communication between field and office workers that needs to take place alongside a lot of data collection. This puts a lot on the plate of workers in the field who must relay this information, but are also required to complete the field service of interest while delighting customers in the process. This leads to a myriad of challenges in FSM. I am going to look closer at the challenges with Data Accuracy and 1st Time Fix Rate as I believe these major challenges can be solved with elegant implementation of voice technology in existing FSM software.
According to a PwC survey of over 1,000 senior executives, highly data-driven organizations are three times more likely to report significant improvements in decision making. However, data is only valuable if it is accurate and accessible. In-the-field workforces have been around for decades and as a result many teams have relied on manual methods for gathering and managing data. These processes usually involve legacy tech such as spreadsheets or quite literally writing notes on paper. With this type of process it is easy for data to be innacurate.
As a result of this you have seen companies from startups to big technology companies build FSM software that puts mobile technology at the center of the data management strategy. While these products have improved the data collection for workers in the field, with a lot of credit going to automating steps in the data collection process, there are still scenarios that require manual input from in-the-field workers. Examples of this could be getting customer feedback or inputing context specific information that relates to the job at hand. It is important that these data points are also tracked with a high level of scrutiny. They can play a significant role in data driven decision making, and given the manual process can lead to inaccuracies in the data.
The Fix Rate looks at how successful in-the-field workers are at completing their tasks when they show up to a service call. The goal is to have a high first-time fix rate, where you are able to solve the problem the first time you engage with a customer. According to Aberdeen Group, the “best-in-class” field service organizations achieve an 88% average first-time fix rate, with “average” organizations achieving 80% and “laggards” coming in at 63%. This should be a top priority for field service organizations as improving this metric can result in improvements to the company bottom line.
One of the leading causes for a bad first-time fix rate is lack of education or skills to complete the task at hand. When an in-the-field worker is confused about the task they have to complete, it can result in rebooking the service or spending too much time at a particular jobsite. Either way, lack of skills can be a real challenge when trying to improve a company's first-time fix rate. Organizations should also be looking to better educate their employees, but they should also explore how they can avoid rework on the spot when inevitable problems come up for in-the-field workers.
Customers need to be front of mind when completing field service work, however organizations also need to be mindful of their employees completing the work. One way of doing this is making sure organizations offer tools that enable workers to complete their job as efficiently and effectively as possible. There are a myriad of FSM software options in the market, but despite these tools there is still a lot of innovation that needs to be done to make sure these solutions are actually meeting the needs of in-the-field workers. Emergence Capital conducted a survey called “The State of Technology for the Deskless Workforce 2020”. There were two key insights I want to highlight: A) 60% of deskless workers believe there is room for improvement in the technology they use to perform their jobs. B) 75% of deskless workers spend most of their time using a piece of technology that isn’t crafted for their use case.
Voice technology is a perfect feature to improve existing FSM software. Since voice technology can easily be embedded into existing mobile applications, product teams can create Natural User Interfaces that take advantage of normal mobile features like swipe or type, but also allows for voice input where it makes sense for the end user. You can see the value of having voice input alongside a mobile app in the demo video below:
There are three main benefits that can be realized with an elegant integration of voice technology in existing FSM software. The first benefit comes from the efficiency of voice as an input vs typing. Smartphone speech recognition is 3x as fast as human typing, however the real efficiency with voice technology comes from eliminating the need for a conversational experience as seen with popular voice assistants like Alexa or Siri. Forcing a conversational experience on the end user eliminates the value that comes from having a mobile screen at our fingertips. The efficiency with voice tech can be unlocked by understanding where there is actual efficiency with using voice as an input vs just tapping something on your screen.
The second benefit with voice technology plays off of the value from efficiency. This benefit is improving the quality of data you are capturing. While many different pieces of data can be tracked automatically, there are still different data points that will need to be updated manually by in-the-field workers. To expand on the insights from the Emergence Deskless Workforce research mentioned above, the leading cause of dissatisfaction stems from inefficiencies with the technology workers use. If workers are not enthusiastic or engaged with the software they use for data collection you are destined to get inaccurate data. There is a big incentive for workers to find technology that actually makes them more efficient and voice technology provides this incentive if implemented properly. This mix of efficiency and engaged users leads to a recipe for accurate data collection.
The third and final benefit focuses on improving the first-time fix rate using voice technology. Organizations with an in-the-field workforce are ultimately going to be performing some type of in person service call, maintenance, check-in, etc. Voice technology enables companies to have an additional modality to access company documentation, instruction manuals, best practices, or any other resource of interest that might help an in-the-field worker complete their task the first time they show up at a service call. Voice technology allows workers to use natural language to both find answers to questions efficiently and also take advantage of the mobile screen for instances where the worker may need step-by-step instruction or visuals to reference.
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