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Field Service

Ever played Chess? Any good at it? All you have to do is move 16 pieces step by step around a board of 64 locations to meet your objectives. Easy! The objectives keep changing as the other side moves their pieces around as well, but still, how difficult can it be?

I have a portable Chess computer, I sometimes take it with me when I'm working away on assignments, to while away the evening hours in whichever hotel is temporarily home. With practice I am a moderate player, but I don't play sufficiently frequently to become better than moderate. Most people would agree that Chess is a difficult game, and that a computer can play it much better than they can.

Field Service Management is no different to Chess, but larger in scale. Imagine having to manage 100 pieces, with different attributes, on a much larger board - each piece to move an averageĀ of 5 moves a day, using minimum time and distance, so that 500 different locations are visited by the pieces during the day, and the pieces all complete the day by returning to the location from which they started. Played as a game of Chess it would be unthinkable, too complex, too many options, too many moves and too many objectives. But that is exactly what we expect the Field Service Management team to achieve. If you consider the Field Service Manager in your organisation, is he or she the world's greatest intellect - with the brain powerof ten Gary Kasparovs? No, he or she is another moderately bright person, like you or me, but lumbered with an improbably difficult job. 100 engineers would be a reasonable number for the field service staff of a small to medium sized service company, The complexity of the Field Service Management problem faced by a national utility with thousands of engineers is almost impossible to grasp.

Historically the problem has been solved by breaking it down into smaller problems - distributing it. For the SME this might mean dividing the country into 10 areas, each served by 10 engineers, each controller by an allocator who distributes the jobs amongst his or her engineers according to their skills, locations and availability. The allocators might be based at a central head office, or distributed amongst regional depots. They might also be responsible for receiving job bookings from customers, and / or providing some management function for the engineers. The distributed model works, it has worked for decades, it is tried and proven, and inefficient.

In the distributed model there are multiple areas, each with geographic boundaries which determine the capture and allocation of service jobs. A job in one set of postcodes will be allocated to team A, a job in another set of postcodes will be allocated to team C, which is adjacent to but south of team A. Each day there will be jobs close to the geographic boundaries, so that some jobs in the South of team A's area are actually very close to other jobs in the North of team C's area. Each team has to send a member to the boundary to service these jobs, when they could be more efficiently serviced by one team sending a member who crosses the boundary into the area served by the neighbouring team. Also, on a given day, area A might have 45 jobs to servicewhile area C has 55 job - team A therefore meets its targets with time to spare, while team C, overworked, misses targets and fails some customers. So the distributed model for Field Service Management works reliably, but not very well.

Modern computer systems have been used to overcome many of the human limitations in the Field Service Management problem. Just as with Chess computers, Field Service Management Systems can produce better, more efficient, higher quality and less costly solutions to the problem of getting the right engineers with the necessary skills (and spare parts) to attend service jobs within the agreed SLAs or appointment windows than people can. And because the computer systems have the processing power to address the whole field service force as one, instead of breaking it into smaller chunks, the systems can also eliminate the inherent inefficiencies of the distributed model, with no boundary constraints and optimal workload balancing. The best systems allow the problem to be recalculatd continuously through the day, automatically compensating for delays due to traffic problems or unusually complex and long service jobs, while allowing new jobs to be inserted into the equation in "real time", enabling jobs not due until tomorrow or the day after to be done today while an engineer is already in the same areas the new jobs.

The technologies used as components of automated Field Service Management include the Field Service Management system, Mobile Data, Vehicle Location, and Real-Time Scheduling. Each technology brings a set of benefits, and when employed together as an integrated suite the benefits are significantly magnified.

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