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M obile Workforce Management is the practice of allocating and reacting to the activities of field resources through a permanent data connection to your operations software. To optimise a mobile workforce means these resources (people, stock, and vehicles) are balanced between meeting SLAs, such as appointment times, and an acceptable quality of work, such as a first-time fix. It is only through an optimised balance that a business provides a sensible, scheduled workload for their field force, whilst remaining competitive.

Amongst the hundreds of possible data points to assist this optimisation—inventory, operative skills, and job completion analytics, (the list is ever growing)—all would be rendered useless without geolocation. What is the power of data-driven positioning, how has it evolved into code, and what does it mean for decision making in mobile workforce management? Here we introduce the concept and look at an example solution.

THE BASICS: WHAT IS GEOLOCATION?

Geolocation in its rawest form is real-world location data. It has numerous use cases, covering planning, engineering, transport, logistics, insurance, telecommunications, and sales. Location-enabled field service apps are supplied data through a technical standard served by a Geographic Information System (GIS). This data feeds positioning into both applications of the scheduling relationship; dispatch (a scheduling server) and device (live field results). The combined business benefits of geolocation data is growing exponentially, with increased use of assistive devices in engineering, and the Internet of Things powering performance metrics for predictive maintenance.

WHAT IS GEOCODING IN MOBILE WORKFORCE MANAGEMENT?

However, solely using address data, such as a Post Code/ZIP Code is not optimal. It simply cannot account for the limitless variations that affect meeting a scheduled appointment time successfully. Intelligent scheduling conditions include road type, road length; even whether the address is on the left or right-hand side of the road or crosses a body of water.

Best-of-breed scheduling software, such as FLS VISITOUR, computes these additional properties in two ways. The first evolves multiple geolocation datasets into unique geocodes. The second is to combine those geocodes into one software. Simply put, to truly optimise scheduling, highly detailed location data becomes code, and the FLS VISITOUR GIS Server and Dispatching Server is uniquely, a single programme to process that code.

HOW DOES GEOCODING OPTIMISE MOBILE WORKFORCE MANAGEMENT?

A system missing location intelligence cannot define travel speed, realistic distance, or arrival times. Therefore, geocoding must be the basis for optimising the entire routing and dispatch process. FLS VISITOUR goes further. The PowerOpt scheduling algorithm consults many intuitive features built with geocodes, such as FLS Speed Profiles. Identifiers such as house numbers, junctions, one-way streets, and time-of-day driving data for trillions of journeys all contain geocode elements and are considered in routing results.

Tracking geocode data from mobile resources (people/vehicles in the field) into live maps allows planners to remove hard borders (patches) in favour of an overlapping radius. Old-fashioned service patches lead to unbalanced workloads for mobile workforces and inefficient routing when plans change. Scheduling within a radius results in less travel, a lower carbon footprint, and a happier field workforce.

Again, no reliance on third-party interfaces, such as calls to Google Maps, what3words, or even open source plugins, means scheduling within seconds, on one screen. More data built on geocode foundations, such as traffic jams and ongoing roadworks (like Britain’s 'Smart Motorways' effort) are instantly factored into scheduling results. Based on these parameters, FLS VISITOUR always calculates the fastest route, never the shortest. Reducing human involvement with administration means published routes can be clearly explained – and relied upon by your mobile workforce.