Understand the pulse of your employees and customers
Posted: Sat Dec 28, 2024 10:46 am
Voice of customer and voice of employee activities often are established for the primary benefit of the organization (i.e., increase sales/margins, increase retention rates). In this new era of AI, field service organizations will need to listen to the needs and concerns of customers and employees. As AI becomes more pervasive across industries, field service organizations must tackle the elephant in the room around AI – privacy, and job displacement. Too much of the discussion around AI in the B2B world has been the fear that it will replace jobs or result in IP theft. This view of potential negatives neglects to amplify all of the potential positive outcomes of what AI can offer, Educating customers and service employees about the value of AI and how these technological capabilities can improve the service experience, customer outcomes, and employee productivity is crucial to adoption and comfort. Without understanding customer and service employees’ fears about AI, organizations will struggle to maximize the opportunities that will come with this innovative technological advancement.
Shift the KPI that measure success in the field. The promise of AI in field boost your business with our doctor database service revolves around improved operational efficiency, predictive/prescriptive service outcomes, and improved productivity of the team. However, there is a bit of a gap between the current metrics that are being measured and what should be measured in the AI era. If AI is to improve the speed of service, technicians should be measured on the value they are providing to the customer and not on how many more jobs they can complete. The improved speed of issue resolution as a result of AI providing better answers to the reason for failure should allow the humans on the service team to focus on the customer. This shift in what role a field service technician can play in customer outcomes is profound, no longer is the technician solely in place to turn a wrench but to prioritize customer engagement. Therefore, the KPI that matter aren’t work orders closed in a given day but experiential and value based. These new metrics may be more difficult to measure but will tell a better story of customer impact, future revenue opportunities, and lifetime value.
Highlight the positive and address the (potential) negatives. Right now, there are too many field service technicians that can efficiently get on site in front of a customer or asset but fail to resolve the issue on a first visit. Issue resolution is becoming more and more complex as assets are smarter, supply chain networks struggle with resiliency, and the field force ages out. The ability to have the right part, right skills, right insights, at the right time is becoming a fairy tale for too many service organizations. On the front line is the field service engineer who has to advise a customer or operator in need that service cannot be completed resulting in assets, products, and equipment remaining down. Service leaders must communicate to the field service team both the in office planning/dispatching teams and the engineers in the field the ability for AI to drive insights and efficiency while reducing non-value added task work. The skepticism of technology from service teams has preceded the AI era, but the AI conversation brings with it the fear of machines taking over to the detriment of the humans. However, fear comes from a lack of communication, visibility, and buy-in around strategy and execution. AI can enable service workers to be the expert in a time of customer need and also free up their time from rote administrative tasks. AI must become an opportunity for the service team and not a murky monster.
Shift the KPI that measure success in the field. The promise of AI in field boost your business with our doctor database service revolves around improved operational efficiency, predictive/prescriptive service outcomes, and improved productivity of the team. However, there is a bit of a gap between the current metrics that are being measured and what should be measured in the AI era. If AI is to improve the speed of service, technicians should be measured on the value they are providing to the customer and not on how many more jobs they can complete. The improved speed of issue resolution as a result of AI providing better answers to the reason for failure should allow the humans on the service team to focus on the customer. This shift in what role a field service technician can play in customer outcomes is profound, no longer is the technician solely in place to turn a wrench but to prioritize customer engagement. Therefore, the KPI that matter aren’t work orders closed in a given day but experiential and value based. These new metrics may be more difficult to measure but will tell a better story of customer impact, future revenue opportunities, and lifetime value.
Highlight the positive and address the (potential) negatives. Right now, there are too many field service technicians that can efficiently get on site in front of a customer or asset but fail to resolve the issue on a first visit. Issue resolution is becoming more and more complex as assets are smarter, supply chain networks struggle with resiliency, and the field force ages out. The ability to have the right part, right skills, right insights, at the right time is becoming a fairy tale for too many service organizations. On the front line is the field service engineer who has to advise a customer or operator in need that service cannot be completed resulting in assets, products, and equipment remaining down. Service leaders must communicate to the field service team both the in office planning/dispatching teams and the engineers in the field the ability for AI to drive insights and efficiency while reducing non-value added task work. The skepticism of technology from service teams has preceded the AI era, but the AI conversation brings with it the fear of machines taking over to the detriment of the humans. However, fear comes from a lack of communication, visibility, and buy-in around strategy and execution. AI can enable service workers to be the expert in a time of customer need and also free up their time from rote administrative tasks. AI must become an opportunity for the service team and not a murky monster.