The extra time spent on admin and coordination to manage a blended workforce can be a real drain on your efficiency. Alleviating this administrative burden and saving time in field service will be crucial for resource optimisation and keeping delays from dragging down the customer experience.

Photo: Thomas Åberg

One typical cause of administrative burden is when several different parties and systems are involved. This may result in project managers, contractors, sub-contractors, service technicians, and others working in silos. Time is wasted with duplicated documentation and out-of-date information, with more admin time spent searching for the right versions. Assigning the right resource to the right place at the right time is even more challenging and complex with a blended workforce.

The solution

A single digital collaboration hub

Effective case and field service management solutions eliminate these challenges by providing a single digital collaboration hub that is easily interoperable with all the different systems used. This creates a transparent and constantly updated digital flow between everyone involved. As a result, several administrative bottlenecks and inefficiencies are eliminated and the back office can track and drive case progress, which saves time and creates a better customer experience. The software should also facilitate the exchange of information with real-time reporting from the field, easy chatting, and sending attachments like maps or images from the site. This prevents many inefficiencies resulting from manual paperwork and delayed communication while creating transparency between the administrator and the worker performing the field service.

Automation-driven optimisation

Powerful case and field service management solutions keep field service operations running smoothly by always having a plan B. This is dependent on efficient resource management, which entails ensuring that the planning, scheduling, and assignment of all resources are optimised in every situation. Advanced machine learning algorithms can be used to automatically analyse your entire schedule in real-time and generate plans for minimising costs and environmental impact while maximising service response. This optimisation can use numerous parameters, including geography, availability, capability, skills, cost, location, and priority.

Reduced individual dependency

One of the ways optimised resource planning helps prevent bottlenecks is by reducing dependencies on individual workers. This makes it possible to load balance a case within a team, have a technician fill in for another who is sick and keep everyone in the loop on regulatory requirements.