IoT is rapidly propelling Field Service capabilities. What does that really mean for us?

There’s been a lot of talk in the service industries in recent years regarding the influence and impact that IoT (the Internet of Things) will have on productivity and information management. I believe that this is true, and the capabilities available to us now to ingest loads of data points and event triggers into our operating systems must be a good thing, right?  Well… maybe. 

In field service specifically, the applications are actually very real and useful.  Monitoring elevators, air conditioners, heavy equipment and plant, and other electro-mechanical assets to ‘predict’ failure, and rectify the issue in a controlled way is great.  No-one wants an unscheduled outage; no elevator company wants a ‘trapped passenger’, and no air conditioning company wants a legionella outbreak or a failed system on a 110 degree F day in the summer.  IoT applications can absolutely be used in these scenarios to collect, track, predict and respond to alerts and messages from a wide array of connected devices.

But is this approach always a good thing?  Sometimes it may not actually be that useful.  At this time I’m reminded of the old saying… “Just because you can doesn’t mean you should”.  You see, just because you have the ability to capture, ingest, process, trend analyse, and report on potentially millions of data points, should you?  Maybe not. You can easily run the risk of being overwhelmed by the sheer volume of data, such you could lose sight of the usually simple and obvious indicators of the majority of maintenance needs. 

Our advice is always… “simple is best”.  We humans all too often complicate matters as a first order of business, before really understanding how we can solve a problem, or assess a need simply.  Don’t do this!  Search for a simple approach, whilst relentlessly keeping your service goal in mind.  Yes, of course employ IoT and connected field service capabilities, but please think carefully about just how much data you really do need to ingest; how many complex algorithms you really need to interpret the messages, and how complex the responses to the alerts needs to be. Do it, but don't drown yourself in complexity and data volume.

I’m also now reminded of the famous quote by Albert Einstein… “Everything should be made as simple as possible, but not simpler”.