This fact led me to wonder how AI could be applied to field operations and what impact it might have. There is already a significant level of automation in a successful mobile workforce management (MWFM) implementation, largely in the automatic scheduling of work to field resources. This, plus the additional effectiveness enabled by software dispatch tools, has increased the number of field resources that a single dispatcher can manage. A 1:50 ratio is typical in the communications industry, and many companies have targets well beyond that figure.
On the other hand, many field service companies have much worse dispatcher/technician ratios, even when using the same MWFM software as the companies who have improved their ratios. One key reason, I believe, is that dispatchers are disincentivised to support and collaborate with an automatic scheduling system; their livelihoods are at stake. So, dispatchers actively find issues with automatic assignments (even when there are none) to show that the dispatcher role is still essential. Clearly this is a management problem, but of the kind that are often the most difficult to resolve. But, I digress; this a topic large enough to warrant its own article.
At present, the main reason that dispatchers are still required is to handle jeopardy situations, or where rapidly changing weather conditions mean that the planned schedule is no longer applicable. One can envisage building rules into today’s scheduling algorithms to make them flexible enough to handle all such events, but the complexity of the rule-base that would be needed and the difficulty of testing and debugging the behaviour precludes such an approach. Is this where AI technology could be applied to MWFM? Could it enable a system that learns how to handle unplanned situations and need not be programmed; a system that, in this restricted environment, makes decisions as well as a human being? If this were possible, one can imagine that dispatchers would all but disappear; perhaps dispatcher/technician ratios of 1:500 or more are possible.
This is, therefore, another example of AI being a threat to white collar jobs. In contrast, the work of the field technicians, with its combination of manual effort, diagnosis of physical assets and interaction with customers, is not likely to be replaced by AI in the near future, although the rollout of smart devices will no doubt have some effect. It will be interesting to see how field staff reacts to job assignments mediated by artificial intelligence. A flexible and agile workforce would no doubt handle this better than most. In any event, I, for one, would welcome our new scheduling overlords.