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Gain Deeper Service Insights With These Three Data Entry Best Practices

Get the most out of your service data by using these three actionable steps to encourage accurate data entry and create a data-driven field service culture.

Field service organizations can’t be truly data-driven without complete, high-quality data…but achieving that is not always a breeze. It’s a common challenge that many field service teams consistently face across industries.

The biggest obstacle to achieving high-quality data? Poor data entry practices.

In addition to overseeing service operations, field service leaders are now responsible for their team’s data entry strategies and processes. To help them, we’ve outlined three best practices that every service team should follow when entering and managing data. Here’s how service leaders can empower their teams to input the cleanest, most complete service information into their databases, ultimately resulting in stronger data analysis and improved service outcomes.

1. Prioritize free-form data entry over CRM dropdowns

Your employees’ notes and expertise are the most critical and useful data that you can collect. CRM dropdowns are a common data-entry tool because they can seemingly make the data-entry process easier. But, more often than not, these shortcuts lead to bad data and low-quality insights; they are limiting and can ruin an organization’s understanding of what is really happening. Dropdowns can be useful in some cases, but when it comes to symptoms, observations, and outcomes of a service event, encouraging your technicians to provide as much detail as possible will help in the long run.

Dropdowns also often create lazy behaviors. In a dropdown picklist, the two most common selections are almost always going to be the first option and “other”. Because of this, dropdowns are known to cause inaccurate data that lacks detail, leading to poor insights.

Encourage your technicians to enter an unlimited amount of free-form data (for example, detailed notes that include key observations about the job/service encounter, what they expected the issue was, which parts or processes were failing, what fix they put in place, any other challenges they faced). This is the most important data you can gather and it creates a much deeper level of understanding of what is happening in the field.

To get value out of these notes, consider implementing service intelligence tools that use ‘Service Language Processing’ to extract this detail and transform it into actionable outputs. The data scientists building and training these models are well-versed in the verbiage and terminology specific to the service industry, which further regulates the credibility and caliber of the insights an organization is able to derive.


2. Establish goals and standards for data entry

Data entry often gets put on the back burner but it’s important your teams understand the bigger picture. Train your workforce and explain what’s expected of them as it relates to data entry. Leaders who can develop a sense of ownership of the data in their technicians will benefit significantly. Your technicians need to understand that they are responsible for the data they enter and if it’s not entered correctly it can have a negative impact on the greater organization.

One way you can do this is to create rules around what data needs to be entered at the call center/customer service level before they can dispatch. When entering data, call center reps, technicians and teams should understand:

  • What data field must be filled out for a ticket to be closed?
  • What type of detail is expected in each field?
  • Which team is responsible for filling this detail in?

Make data entry a part of your tech’s incentive plan. Determining incentives based on the data they input is an effective way to hold techs accountable and ensure they enter data to company standards.


3. Review the data together in formal qualitative analysis meetings

Leaders should carve out time to perform qualitative analyses on a weekly or monthly basis with their technicians. These meetings should include a review of 4-5 service events where the technician uses the data to drive the conversation and walk you through how things went. Be sure to keep an ear out for information they give you about the visit that isn’t reflected in the data and encourage the tech to add it to the notes.

You don’t want your workforce to lose sight in the value of entering detailed, accurate information into your database. Use these meetings to reinforce the value of clean data and to make sure data entry is being completed to a satisfactory level. Lastly, always make sure to give your technicians an opportunity to give you feedback on the process.

Improve the caliber of your data and level up your decision-making ability!

Service leaders are responsible for the quality of the data being entered into their system.

By following these best practices, they can create data-entry habits for their technicians that lead to richer insights. To learn more about how service language processing tools are helping field service organizations transform technician observations into actionable data, visit aquant.io

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