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Route optimization is the fastest and most effective solution for field service businesses to achieve more efficient routes and reduce costs. Even though its benefits in minimizing drive time and mileage are well-documented, many companies continue to rely on manual route planning. This guide seeks to demystify route optimization from a practical perspective, especially for software platforms in field services and end customers needing a sophisticated AI scheduling algorithm. Additionally, we will explore the challenges associated with traditional route optimization and present how optimization AI for field service can resolve these issues.
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Route optimization is the process of identifying the shortest and most cost-effective routes between multiple destinations while adhering to real-world needs and business constraints. A human route planner may manage this task adequately for small-scale operations with a dozen addresses and a single driver. However, as a business grows and needs to handle multiple service orders daily with several field service employees, the complexity of route planning increases significantly.
Route optimization software addresses this challenge by analyzing all necessary information—such as addresses, time windows, driver or service team schedules, and vehicle capacities—and automatically generating highly efficient routes in seconds.
In field services, inefficient routes have a direct financial impact, affecting fuel consumption, vehicle maintenance costs, wages, and the number of service calls that can be completed each day. By reducing drive time, businesses can lower fuel costs and increase profitability.
Automating route optimization with scheduling software also enhances customer service by ensuring timely and accurate service delivery, solving service requests correctly the first time (first time right). From an employee perspective, AI-generated routing is beneficial as it ensures compliance with labor rules and maintains consistent schedules, even when the regular planner is on holiday.
Furthermore, there are broader social and environmental benefits. Route optimization helps alleviate traffic congestion and reduces fossil fuel consumption, contributing to a more sustainable future.
A comprehensive guide wouldn’t be complete without a bit of history. Here’s a brief journey through route optimization’s origins in academia.
For as long as humans have traveled, they’ve sought more efficient ways to do so. Early road builders followed animal tracks, utilizing routes that had naturally evolved over time. In 1736, mathematician Leonhard Euler addressed the Königsberg bridge problem, laying the groundwork for graph theory. Jumping ahead to 1949, the Traveling Salesman Problem (TSP) emerged, posing the question: What is the shortest possible route that visits each city once and returns to the starting point?
Since then, mathematicians and computer scientists have developed various methods to tackle routing problems. While finding an optimal solution for large-scale problems remains challenging, many heuristics and meta-heuristics offer practical solutions within reasonable timeframes.
Adding to the fascinating history of route optimization is the Car 54 contest by Procter & Gamble. Participants were tasked with helping the characters Toody and Muldoon from the TV show “Car 54, Where Are You?” find the shortest round trip route to visit 33 locations across the United States. The contest offered 54 prizes of $1,000 each and a grand prize of $10,000, highlighting the practical importance of route optimization in everyday business operations. This contest not only engaged the public but also emphasized the real-world applications of theoretical routing problems, encouraging innovative solutions that continue to influence the field today.
The Traveling Salesman Problem (TSP) led to many variations, including:
Academics continue to create numerous tailored algorithms to tackle these problems, often trading off perfect solutions for practical applicability. The Solvice team, for one, has contributed greatly to academic and operational research over the past years.
Large corporations like UPS and AT&T have invested billions in developing proprietary algorithms for route optimization. Solvice aims to democratize this powerful technology, making it easily accessible via an API to software platforms in scheduling and field services, as well as businesses facing intricate scheduling challenges that off-the-shelf software cannot resolve.
The algorithms required for effective route optimization must consider real-world factors. Real field service teams navigate road networks with varying traffic patterns and other nuanced human considerations, which academic theories often overlook.
Standard routing algorithms are not designed to handle more complex operations, such as executing different orders in sequence, combining multiple skills for one job, managing pickup and delivery tasks, or ensuring that specific personnel handle selected jobs. The concept of job relations provides a solution by feeding the solver with detailed information to schedule jobs in specific sequences, whether directly sequential, on the same route, by the same resource, or a combination of these factors.
By addressing these complexities, Solvice’s route optimization API can streamline even the most intricate field operations, ensuring efficiency, fairness, and satisfaction for both planners and field service teams.
In a survey of 11,246 businesses, 72% still plan routes manually. Manual planning makes sense for small businesses, but it is time-consuming and often less efficient.
Manual route planning heavily relies on the tribal knowledge of experienced personnel. This dependence can create vulnerabilities within the organization, as the absence of key individuals can lead to operational disruptions. When these knowledgeable employees are unavailable due to illness, vacation, or turnover, the entire planning process can falter, causing inefficiencies and delays that negatively impact service quality and customer satisfaction.
The experience of Solvice highlights the stark contrast between human planners and algorithm-driven solutions. Human route planners, despite their expertise, often produce routes that are significantly longer and less efficient than those generated by advanced algorithms. Solvice’s data indicates that algorithm-based route optimization can outperform human planners by approximately 30%. This improvement translates to substantial cost savings in terms of fuel consumption, vehicle wear and tear, and labor expenses.
Moreover, the efficiency gains extend beyond route quality. Algorithms can reduce the time required for scheduling from hours to mere minutes or even seconds. This dramatic reduction in planning time allows businesses to respond more swiftly to changing conditions and customer demands, enhancing overall operational agility.
Transitioning from manual to algorithm-driven route planning offers businesses a competitive edge. By leveraging the power of optimization AI, companies can achieve substantial cost savings, improve operational efficiency, and enhance service quality. This shift not only mitigates the risks associated with the reliance on key personnel but also positions businesses to thrive in a dynamic and demanding market environment.
In summary, embracing algorithm-based route optimization is a strategic move that drives significant improvements in efficiency, cost management, and customer satisfaction, while also ensuring that operations remain resilient and adaptable in the face of personnel changes and evolving business needs.
Intelligent Route Optimization considers human elements of route planning, ensuring driver satisfaction and practical route efficiency.
Traditional algorithms often overlook the impact of time-of-day traffic on route efficiency. Intelligent Route Optimization leverages AI to predict traffic patterns and optimize routes accordingly. By incorporating real-time traffic data, this advanced approach ensures that routes are planned with the most accurate and up-to-date information, minimizing delays and improving overall efficiency.
Service teams thrive on well-organized, non-overlapping routes. Intelligent Route Optimization creates clean clusters, avoiding the frustration of overlapping paths. This not only keeps drivers happier but also ensures that routes are practical and easy to follow. Clean, well-defined routes enhance operational efficiency and employee satisfaction, making daily tasks more manageable and predictable.
Familiarity with routes significantly boosts driver performance. Intelligent Route Optimization integrates driver experience into the planning process, ensuring that drivers are assigned to routes they know well. This approach enhances efficiency without compromising on the effectiveness of the routing plan. By aligning routes with driver familiarity, businesses can achieve smoother operations and higher productivity.
Equitable distribution of drive time and working hours is crucial for maintaining employee satisfaction and operational fairness. Intelligent Route Optimization ensures that routes are balanced, preventing scenarios where some drivers are overloaded while others are underutilized. Balanced routes contribute to a fairer workplace and more satisfied employees, fostering a positive and productive work environment.
Accurate geocoding is essential for precise routing. Intelligent Route Optimization employs smart geocoding techniques to ensure that addresses are correct, eliminating the frustration and inefficiency caused by incorrect routing. Accurate geocoding not only enhances route efficiency but also improves customer satisfaction by ensuring timely and accurate deliveries.
Route optimization in field services presents a unique set of challenges compared to delivery routes, as it must account for numerous operational constraints. These constraints stem from the diverse range of jobs that need to be performed on the road. Field service teams handle everything from straightforward tasks like window cleaning, lawn care, snow removal, HVAC maintenance, pest control, and plumbing repairs to more complex, team-organized activities such as tree care, landscaping, general contracting, and painting. The most intricate schedules are found in healthcare, where mobile health practitioners coordinate activities, such as nurses preparing for a doctor’s visit or physiotherapists following up on various health-related appointments.
In delivery routing, jobs are typically short and straightforward. However, in field services, the time required to complete each task significantly impacts the overall schedule. The duration of service tasks must be carefully planned to ensure efficient and timely operations.
While delivery jobs mainly involve pickup and delivery, field services require the scheduling of jobs in sequence, direct sequence, within the same route, and other complex patterns. Properly managing these job relations is crucial for maintaining an efficient and cohesive schedule.
In delivery services, the identity of the delivery person is often irrelevant to the customer. In contrast, field service customers, such as patients, typically prefer consistency in the personnel they interact with. For example, patients often want the same physiotherapist for every visit to ensure continuity of care and build trust.
Field services demand high flexibility to accommodate urgent interventions and last-minute customer requests. Unlike delivery services, field service management requires a system that not only provides batch routing solutions but also suggests the optimal times to add new orders in real-time.
Modern field service management solutions must offer customers an interface to book service appointments that integrate seamlessly into the existing schedule. This feature enhances customer satisfaction by providing convenience and ensuring that bookings are optimally inserted into the service calendar.
Implementing route optimization software with Solvice is a straightforward process. Here are three easy steps to get started with Solvice’s APIs:
1. Connect:
Register: Begin by registering for a test account on the Solvice platform to gain access to the APIs.
2. Request:
• Create JSON File: Prepare a JSON file that outlines your request, including:
• Orders: List of all service or delivery orders.
• Resources: Details about your available resources, such as vehicles and drivers.
• Preferences: Any preferences you have, such as route preferences or time windows.
• Constraints: Specify any operational constraints, such as maximum driving time or vehicle capacities.
3. Optimize:
• Generate Routes: Use the API to submit your request. The software will process the information and create optimized routes.
• Response: Retrieve the optimized routes generated by the software.
• Explanation: Access the detailed explanations provided by the solver to understand the rationale behind the routing decisions.
By following these simple steps, you can leverage Solvice’s powerful route optimization capabilities to enhance your field service operations, reduce costs, and improve overall efficiency.
With numerous options available, selecting the right software for your business is crucial. For instance, Capterra lists 329 route-planning solutions and 1021 field service management platforms. It's essential to ensure that the software you choose integrates all the features you need for your operations. Here’s a handy checklist to guide you:
By using this checklist, you can ensure that the software you select meets your business’s specific needs and helps streamline your operations effectively.
Working APIs for solving routing problems can be daunting, but with the right documentation and an easy-to-use API, you can get a long way even without technical guidance from the supplier.
Take, for example, the Solvice platform. The solver has six endpoints. You give the input, and the API gives you the output for an optimization routing request.
The solver has three action endpoints (POST requests):
And three endpoints for retrieving information (GET requests):
Optimized routes have significant environmental benefits. Here are five ways route optimization helps the environment:
Route optimization is far superior to manual route planning, reducing drive time by 20%-40% and significantly increasing the profitability of field services businesses. Intelligent Route Optimization ensures practical and human-friendly routes, making it a powerful tool for businesses of all sizes. Consider adopting a route optimization API like Solvice to streamline operations, save costs, and contribute to a greener planet.
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