Field technician scheduling is an area in which many organizations still have significant room for improvement before achieving an optimal balance between customer satisfaction, technician utilization, and company profitability.
According to an Aberdeen Group survey of 220 companies, the top-performing organizations (BIC – Best in Class) focus on three main areas when managing their field service operations:
- Daily scheduling, dispatching, and routing – dynamic scheduling
- Strategic planning -demand forecasting and resource planning
- Workforce management – hiring, training, and technician compensation models
In addition to improving customer satisfaction and retention, companies that provide field services can increase profitability by focusing on opportunities to generate additional value through improved service and greater operational efficiency.
Simply increasing technician workload is only a partial solution. An underutilized technician represents a significant financial burden for the company, while an overutilized technician can negatively affect performance by arriving late to customer appointments or increasing the rate of repeat service calls due to insufficient time to resolve the issue properly on the first visit.
Many factors influence technician scheduling decisions. However, BIC companies generally focus on assigning the technician whose skills are best suited to the task and ensuring that the technician is equipped with the appropriate tools and parts required to resolve the issue – “Make Part a Part.”
This article presents the key parameters organizations should focus on when scheduling and dispatching technicians, without requiring changes to their existing information systems. Based on our experience implementing these methods across different companies, they can significantly increase the percentage of service calls completed each day.
The direct result is increased revenue and, no less importantly, a stronger reputation for providing customers with fast, high-quality service. Operational strategy encompasses the decisions that, over the long term, shape the capabilities of each operational function within the organization and determine its contribution to the overall strategy, while balancing market requirements with available resources.
When examining the main factors affecting service levels and operating costs, several have a particularly significant impact, including daily operations management, planning service “slots” (technician arrival windows), scheduling and calendar infrastructure, and forecasting capabilities.
Daily Operations Management
Daily operations management involves the function responsible for dispatching and scheduling, including the dynamic dispatch and reassignment of service calls throughout the day. Effective management of this function has a direct impact on operational output. It is therefore recommended to define clear performance metrics for daily operations and assign responsibility for achieving them based on geographic areas and defined measurement frequencies.
Several key metrics should be monitored, including completion rate, technician utilization rate, percentage of appointments completed within the scheduled time window, travel time and fuel costs, and overtime rate.
Some of these metrics can also be defined as shared team or regional metrics. Organizations can also establish joint targets for technicians and dispatchers, creating shared objectives between the two functions directly responsible for planning and completing service calls.
Planning Time Windows and Allocating Time
One of the key challenges in workforce planning and technician scheduling is determining the appropriate service time windows, or “slots.” There is an inherent tension between the customer’s perspective and the operational requirements of the technician and the scheduling system.
The narrower the appointment window, the more convenient it is for the customer, since it reduces the amount of time they are required to remain at home waiting for the technician. From the technician’s perspective, however, narrower time windows increase the likelihood of arriving late, reduce scheduling flexibility, and ultimately reduce the efficiency of the system as a whole.
The challenge, therefore, is to find an approach that balances these two needs and creates a satisfactory outcome for both sides – minimizing the customer’s waiting time while maintaining sufficient flexibility in technician arrival times.
Based on our experience, several approaches can address this challenge and achieve high levels of satisfaction for both customers and technicians
Dynamic Scheduling
The traditional approach to scheduling service calls is to create the schedule one day in advance, with limited ability to respond immediately to changes as they occur. Dispatchers do not always have full visibility into the service calls technicians are currently handling or are expected to handle throughout the day.
A more dynamic approach enables managers and dispatchers to respond to these changes in real time and assign other service calls when capacity becomes available.
Based on our experience, 5%–10% of service calls are canceled during the day, while approximately 20%–30% do not take the amount of time originally planned. These variations create gaps in the daily schedule and frequently result in underutilized technician capacity.
To address this issue, organizations can incorporate a controlled level of overbooking to compensate for expected cancellations, while dynamically adjusting schedules throughout the day to optimize technician utilization.
Forecasting
The absence of a structured forecasting model, and reliance instead on memory or intuition, is common in long-established organizations. Those responsible for forecasting typically consider factors such as demand patterns from the previous year, seasonality, and local events.
However, forecasts are also influenced by additional considerations, including budget constraints, existing agreements with subcontractors, and technician availability. These factors are often incorporated into the forecast intuitively, which can affect its accuracy and overall quality.
In most cases, implementing a professional, data-driven forecasting model can improve planning capabilities by tens of percent, resulting in a corresponding improvement in operational efficiency.
In summary, comprehensive optimization that considers all of these factors in the context of market conditions, competition, and the specific needs of the industry can provide greater operational flexibility, higher service levels, and a better customer experience – while also improving the effectiveness of resource utilization.
