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Ten Tips for Field Service Organizations Getting Started with AI

Ten Tips for Field Service Organizations Getting Started with AI

Artificial intelligence (AI) is dominating technology trends. The excessive hype can be confusing, leaving organizations wondering if they are doing all they should or if they are at risk of falling behind the competition. For field service organizations (FSOs), AI’s transformative impact is still being defined, as organizations scramble to understand potential use cases and best practices. This blog provides some tips for launching your AI strategy.

The current state of AI adoption

According to Technavio, the field service software market is expected to grow by $1.46 billion by 2028. This massive increase is driven by the fact that many of the challenges the industry faces can be addressed by replacing on-site management with cloud-based software. This allows technicians to self-manage their jobs, improves workforce productivity, and guarantees efficient customer service. 

Current Challenges in the Field Service Industry

AI is very much on the minds of technology leaders, including those in the field service industry. A 2023 survey found that 70% of organizational leaders believe the benefits of AI outweigh the risks – but only 15% of them feel prepared for the demands ahead. So if you have concerns, you’re not alone.

Field service organizations face intense pressures

Companies that perform field service are especially vulnerable to today’s market pressures, giving them extra motivation to consider AI applications.

  • Nearly two-thirds of consumers will immediately stop doing business with a brand once they receive poor customer service. (Microsoft)
  • After more than one bad experience, around 76% of consumers say they would rather do business with a competitor. (Zendesk)
  • 1 in 6 shoppers walk away from a purchase due to bad customer experience. (Emplifi)

What's realistic and practical?

FSOs need to set realistic expectations. AI will not solve all business problems overnight. It is a process of adapting and learning. Practical applications, like schedule optimization, provide a smart place to start.

 

Ten tips for field service organizations getting started with AI:

  1. Start with specific projects. Projects do not need to be mammoth to be effective. Choose an initiative that is easy to enact with high pay off, like optimizing scheduling, shortening the call-to-dispatch time, or increasing first call resolution rates. Insights and automation from AI will help each of these use cases.
  2. Ensure data accuracy. You will likely need to do a data cleanup before you undertake AI initiatives. Data needs to be accurate, accessible, and able to be searched and organized in meaningful ways. A knowledge base, powered by AI, is one of the easiest ways to allow employees to look up answers to their questions.
  3. Integrate AI into existing workflows. Automate key processes across business units and focus on practical applications, like giving customers a very narrow arrival window, based on projected travel times.
  4. Trust an industry partner. Turn to a reliable vendor, like ServicePower, that can help you overcome the stress of development and be your guide during the learning curve. Let your vendor partner focus on research, and you can focus on your day-to-day operations—and what you do best.
  5. Strive for continuous process improvement. Focus on practical use cases, like scheduling, that you can continue to refine as you make improvements and apply insight. AI-driven reporting and KPI-tracking help you measure incremental gains.
  6. Automate processes. Streamline workflows and processes, removing unnecessary steps, redundancies, manual data entry, and time-consuming calculations. A modern, cloud-based field service management solution builds automation into the solution, allowing you to save time across the organization.
  7. Empower employees. Give employees, from call center agents to dispatchers and technicians, access to real-time data and tools to help them make well-informed decisions based on insights and rule-based recommendations.
  8. Identify risks and noncompliance. A modern field service solution with built-in intelligence will help you monitor for exceptions that need a closer look. Data that falls outside of the guardrails you set will be escalated to appropriate managers for review.
  9. Focus on the customer experience. Shortening call-to-dispatch times and improving first-time fix rates are two important key performance indicators (KPIs) that will impact customer satisfaction. Schedule optimization—which provides reliable field worker ETAs-- is another way to provide quick, responsive service.
  10. Focus on savings and achieving return on investment (ROI). Improving workforce productivity means a technician may be able to complete more service calls per day, generating more revenue. Reducing extra trips to the customer’s location can save on fuel costs. Savings such as these, and more, will help you achieve ROI.

Concluding thoughts and take-aways

The topic of AI is complex with many factors to consider. Plus, functionality and use cases continually evolve, with new applications rapidly emerging. To remain competitive, field service organizations must stay attuned to trends and best practices. ServicePower, with schedule optimization insights, can help you launch a practical AI strategy.

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