In field service, technology has forever changed customer expectations. Slow responses to service requests are not acceptable and have a big impact on overall customer experience. According to Bain & Company, a customer is 4 times more likely to defect to a competitor if the problem is service-related rather than price- or product-related. And in highly competitive industries, like communications and insurance, customers have many options of who they choose to do business with.
With the right technology and real-time data insights, field service organizations can enhance customer experience and build loyalty. Predictive field service uses artificial intelligence, machine learning, and data science to increase schedule accuracy and ultimately deliver better service to customers. The Internet of Things (IoT) also plays a key role in predictive field service, connecting companies to customers. Being able to accurately forecast resource demand, job duration, and future issues can help service organizations to establish themselves as a reliable and trusted partner—and deliver real benefits to customers.
Resource Capacity Planning = Consistent Experience
Demand and availability of resources fluctuate in field service for many reasons—storm recovery, seasonable variability, vacations, or even a marketing campaign. When it comes to resource capacity planning, field service organizations need a balance of the right number of people, with the right equipment, skills, and parts, available in the right place at the right time. Driven by predictive analytics, capacity planning enables organizations to make informed decisions during scheduling and dispatch, so there are always enough resources to address work requests. Service delivery can then be predictable, and customers can receive a consistent experience—even in times of higher demand.
Predictive Job Duration = On Time Delivery
When a customer requests service, they will most likely ask how long it will take for the job to get done. Predictive job duration calculates the most accurate time it will take for a technician to complete a job based on historical and current data, including: job requirements (tools and resources), customer background (existing or new), technician profile (individual skills and experience) and environmental (weather and traffic). Scheduling that uses predictive analytics can help field service organizations to provide an accurate answer on job duration and maximize workforce productivity. Delivering a job on time as promised inspires trust and confidence in customers—enhancing their overall experience.
Predictive Maintenance = More Uptime, Less Downtime
For customers, field service doesn’t have to be a break-fix relationship. IoT is transforming predictive field service, connecting customer equipment to field service organizations 24/7 through IoT-enabled sensors. Field service professionals automatically receive alerts from the systems they’re monitoring, allowing them to mitigate potential issues before they cause disruption. Simpler fixes rather than large-scale repairs save money and time for both customers and field service providers. Customers appreciate that minor issues can be detected and resolved before they escalate, which means less operational downtime for them and more likelihood that they will remain loyal customers.
Benefits for Customers = Business Growth Opportunities
With predictive field service, field service providers can deliver a better overall customer experience though capacity planning, predictive job duration, and proactive issue resolution. The more satisfied customers are, the better the chances of them becoming loyal customers. Strong customer relationships can help drive business growth. Get started with predictive field service today.