Getting to a destination in the shortest time and with the least effort possible is an evolutionary imperative. With the emergence of the first roads, the standardization of the paths we take also begun. Thus, roads become not only the shortest possible route from A to B, but also had to become the simplest, fastest and which is often the most important imperative in today’s society, the cheapest. In modern times, the needs for travel optimization are so significant that any unforeseen journey is seen as a serious disturbance of the greater plan, and a traffic jam is seen as an inevitable experience, but still a greatly distressing one. Of course, all these factors affect the total time needed to reach a destination – and as we know, time is money.
What is the travelling salesman problem?
Here we come to a point where abstract sciences such as math comes into our everyday, practical life. The travelling salesman problem is simply defined as finding the best route (the route with the lowest travel costs) to move a person (a travelling salesman) visiting many cities while moving from one city to another, and visiting each city only once. In theory, until now, no algorithm has been found that would solve this task ideally, but in the age of computers, it’s become easy to obtain a completely satisfactory solution to this dilemma.
Of course, the travelling salesman is just a metaphor for an entire army of service repairmen, technicians, health workers, sales representative, insurance agents and others, whose job is to visit several locations every day, do their jobs there and eventually return to their homes, happy and satisfied.
In smaller businesses and organizations, the optimization of travel is usually done by the employee themselves, assessing how much time is needed to reach a location and do their job, and to return (or to travel to the next location). But what happens if we talk about systems with dozens of field workers, with hundreds of potential users, and with even more locations the employees need to reach in order to provide a certain service? Especially if we take into account various rules and obligations that we have towards our clients, such as the maximum time agreed upon for malfunction elimination, the need for urgent action in some cases, the need for spare parts and supplies…
On the other hand, let’s not forget that these jobs are performed by employees – people with all their objective and subjective needs and preferences. We need to allow these people a break during the working day, to lessen the effort required for traveling to a location, simply because this will allow them to be relaxed and to do their job better, and in the end, allow them to be more satisfied with their jobs. The third component, no less important, is to take into account the engagement of vehicles, equipment and machines that should also be used optimally.
How to solve the travelling salesperson problem?
For such complex organizations, there are software systems specializing in so-called Field Service tasks. They can better optimize field service tasks down to the smallest details. Such a system takes care of everything: the types of work orders, the necessary professional qualifications, the equipment needed and the staff available to fulfill a certain order. For each of these work orders, the system will prepare an appropriate timeframe and make a complete worker’s itinerary, taking into account employee capabilities and desires, the optimal route of travel and working hours of both the employee and the client.
The best systems, those using artificial intelligence and advanced optimization algorithms, can optimize hundreds of work orders for hundreds of users and locations at once. As a result of this optimization, companies get more work done in one day, with lower travel costs. At the same time, the personnel responsible for the distribution of employees by sites (dispatchers) have full control over the system, and can make necessary modifications and adjustments at any time, as well as redistribute field staff in case of emergency interventions, delays or similar unplanned situations. Also, field staff can use their smartphones to access all information on their work orders, user contacts and GPS positions of the locations they need to visit. What’s more, the system already provides them with an optimal route, taking into account the current traffic situation. After completing the task, the employee can send a complete report of the work done, the material used, photographs and they can even create a PDF document with a report on the task performed, using their mobile phone, with the client signature, as evidence of the job done.
And in the end…
More efficient field workers, better resource optimization and better coordination are just some of the benefits that a quality field service optimization system can bring. Each company has at least two similar goals: the first is the optimal use of resources, and the other is client satisfaction. If these two goals are aligned, it is much more likely that the company will get the profit it wants. A field service system can help you achieve this.
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