An efficient Field Service management is fundamental to an organization’s ability to achieve customer satisfaction. Field Services hold an indispensable amount of significance for delivering services for your organization efficiently, effectively, and quickly. Amongst other tasks, Field Service schedules your appointments, assigns tasks to employees, plans routes, tracks working time, provides quotations, and designs custom worksheets. On the other hand, there is a dilemma when it comes to applying field services to organizations, especially for midsize organizations. This blog throws light on how to face that dilemma and eventually get the matter resolved.
It is a great logistical challenge to optimize field service and delivery organization. Large organizations have the benefit of expensive automation with Artificial Intelligence and Machine Learning tools. Putting in place, all this technology and capability for a mid-size organization is a dilemma. The return on investment is just not there.
A small group, up to 10 people, can be optimized without computing resources. But when you look at an organization of 50 to 100 people working with multiple complex routes and traffic, this problem requires machine intelligence. Unfortunately, these “machine learning” models are expensive to bring online and implement. The midsize organization, therefore, faces this dilemma that should it decentralize to look like a small company or try to optimize itself like a large enterprise?
The midsize market has until now been under served. The only solution has been to break down the organization into smaller groups, and then have a dispatcher optimize their particular span of control. Without smart automation, a mid-size organization cannot create a dispatch unit for more than 25 people and anything more than a handle full of delivery routes.
For this middle tier market segment, you need a cloud-based solution which allows a company to rent artificial intelligence and machine learning without having to go through the expense of acquiring and training a machine learning algorithm. It is difficult to bring the technology resources on board to maintain and manage such a system, so rent them part-time and share with others in a pool. Besides that, the skill set is not needed full time.
ComstarUSA working with its clients has customized Odoo to be a great fit for this market. Using the new field service management module as the base, we have created the ability to schedule appointments for various types of services using an easy-to-see color coded display which shows available slot by service type, week day, and service area. The delivery routing system has been optimized to define customer sequence within a route. This sequence once optimized does not need to be revisited. Field Staff, when on site, has full access to all sales orders, work orders, and installed equipment information. They can update equipment details, while at the client’s site, including the uploading of pictures.
This new capability optimized for a field organization of 25 to 100 engineers now puts the mid-tier company in a position to compete with large organizations and their multi-million-dollar AI engines. It is the best of both worlds, localized service personalized to the customer, and is made efficient by sharing resources from the cloud.
