Not all AI is equal...

Feb 13, 2018 • FeaturesAIArtificial INtelleingenceFuture of FIeld ServiceMArne MArtinservicepowerCustomer Satisfaction and Expectations

Marne Martin, CEO of ServicePower explains why Artificial Intelligence is going to be a fundamental part of the future of field service and why not all AI is on an equal footing...

In business, we are all now fully aware of the importance of collecting data. However, we are also painfully aware of just how easy it is to get overloaded by the sheer volumes of data we can collect.

An often quoted example that puts the sheer amount of data being generated around us into some sort of context is that a Boeing 787 will generate around 40TB per flight. If you were to play 40TBs of mp3s back to back it would take you 78 years to listen to every file. Yep, those data lakes are deep and quite frankly it’s no wonder some companies are beginning to drown in them.

And this is where Artificial Intelligence (AI) comes into the question - and why it is set to play such an important role within the field service sector.

Ours is a sector in which excellence is being built on data.Ours is a sector in which excellence is being built on data. We are embracing IoT with both arms because it has the power to bring costs down for the service provider whilst increasing service standards for the customer. However, for us to fully see the promise IoT offers we need to turn to AI to help us make sense of all that data.

However, not all AI is equal.

It is often overlooked in conversations but there are very distinct different types of AI. You can have Algorithms that only do one thing. For example, in a law firm, they may have an AI algorithm that sorts through documentation for testimony in trails. Things like this are what are generally viewed as purpose-built AI algorithms, that are all about establishing simple efficiencies. Basically, an AI which is implemented by people and organisations who are searching across large data sets for tightly determined results.

Whilst it is by no means a simple task to develop and deploy such an algorithm when it comes to looking at AI in field service we are talking about a much more complex beast entirely.

For a start let’s just consider the various different types of service and touch points within the service cycle that AI can touch.

To begin with there are three obvious different areas of a field service business:

  • Call centre activities
  • Back office activities
  • Field service activities

Then there are the various different types of information that needs to be factored in as well. For example, on any given service call we would be looking at a minimum for information on:

  • The asset
  • The customer
  • Any service history
  • Component level information
  • Any complexities to service
  • Warranty details

All of these elements only serve to create more complexities in the data - so AI designed to work its way through such levels of complexity is by default going to be a more sophisticated piece of programming.

However, the reason why AI is so important in field service is that we want a product that is flexible and configurable to how our field service businesses evolve and how we want to deliver service. The issue is if you are trying to cross-section a lot of data without AI algorithms that are configurable you are going to be wasting way too much time trying to build software that is one dimensional.

For example, you might build something that says if I get this preventative maintenance alert I am always going to do this. That might be OK for today but it might not fit with your business in a couple of years time.

For the requirements of field service organisations the power of a truly good AI algorithm is all about how robust is its ability to configure different processes.Then you’d have to sit back down with your IT group and your developers and kick off another two-year project on coding some other stuff. By then you’re way behind your competitors - who were able to just adjust some of the parameters on their AI algorithm.

This is why I firmly believe that for the requirements of field service organisations the power of a truly good AI algorithm is all about how robust is its ability to configure different processes.

The volume of the data that is coming out now and the direction that most businesses want to move in mean that we are now well and truly living in a Big Data world and we need to get used to it.

So we need AI to process the sheer amount of data but also we specifically need configurable AI services that will enable us to have the type of service experience that works for our brands and for our customers.

This is why we have been so focused on the development of AI at ServicePower and we were so pleased to be awarded a US patent for the AI algorithms that we’ve incorporated into our latest Customer Experience service solution - which you can see a demonstration of in our recent webinar available @

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