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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 @ http://fs-ne.ws/XYbX30gQDeB

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Salesforce’s VP of Product Management Chet Chauhan, explains why for those companies seeking to embrace a vision of outcome-based services at the heart of their business future, the platform approach is vital...

Servitization is very much top of mind right now, particularly in manufacturing circles - but also in the wider business landscape as well.

A lot of companies are seeing that their products are getting commoditised and have rightly identified that the path to much-needed differentiation is through enhancing the service experience. Whether they are business to business, business to consumer or even something more complex like business to business to consumer, we are seeing companies of all different types focussing on services as a way to get closer to their customers.

It is an approach that yields multiple benefits - companies adopting such an approach get to see how their customer base is using the products, meaning more tailored and better-targeted marketing and sales efforts - but also they can gain insight into how they can better improve those products and feed that insight back into their R&D teams.

However, the fact still remains that for most companies the initial steps on a path towards a servitized business model often tend to stem from companies feeling the pressure to get closer to their customers - a pressure that is in itself driven by the fact that customer service has widely become one of the key differentiators between businesses today.

Senior business leaders across the globe are asking “as our products become more and more commoditised how do we differentiate on additional services that we can introduce to our offering?”

Field service has played an intrinsic role in the quest for improved CSAT standards in recent years, and with so many customer touch points becoming digitised, that is only likely to increase in the future.So let’s try to unpack some of this and explore what the future of field service looks like on an intelligent platform.

So the first thing to consider really has to be ‘How do you get closer to your customers?’

It is only at this point that we can really start to consider the next important consideration, which is ‘How do you deliver a better customer experience?’

Of course, field service has played an intrinsic role in the quest for improved CSAT standards in recent years, and with so many customer touch points becoming digitised, that is only likely to increase in the future.

However, the smart companies embracing servitization see that for the approach to be truly effective, i.e. for it to be more than just a shift in revenue from product to services, but to actually become a genuine paradigm shift that simultaneously makes your customer relationships more profitable and longer lasting, they need much better capabilities to connect to with customers across the whole journey within the organisation.

This concept needs to not only sit on the service side of the business but also be understood from the sales and marketing perspective as well. When an organisation understands this and wants to fully manage the whole customer journey seamlessly - this is when the importance and value of a common technology platform really come to the fore.

Over the last few years, we’ve seen some very important technologies emerge which are having and will continue to have a significant impact on field service delivery.

Firstly, Cloud Computing really drove down costs whilst offering the ability to offer infinite opportunities in terms of scaling businesses. IoT is perhaps the technology that has grabbed the most headlines in 2017 with a some excellent IoT platforms appearing including our own, that allow you to constantly connect to your assets. Mobile has of course been around for many years now but again the technology is keeping pace with other advancements, meaning our engineers and technicians are increasingly more empowered even when working in highly remote areas.

Over the last few years, we’ve seen some very important technologies emerge which are having and will continue to have a significant impact on field service delivery.However, it is another big technological trend that we are now seeing really bring everything together and that is Artificial Intelligence (AI). In a sensorised world of IoT & Big Data AI really is critical. When you have a hundred million sensor events being recorded every hour, a human simply cannot comprehend meaning from that level of information - they will simply drown in the data. Yet, AI can deal with such quantities of data very well and then turn that data into insight, the insight into actions and then it is in actions that we will find value.

We need to think of all of these technologies as being integral elements of an ecosystem rather than being individual technologies - and this is why we are seeing the common technology platform become vital. If you are to adopt a truly servitized business model then you absolutely need to be able to orchestrate the full life-cycle of service and customer interaction in one place.

Indeed, we are already beginning to see examples of these types of forward-looking developments appear in a number of different sectors.

We are seeing many companies connecting their assets - though really this is only the first step in the process. It is when Artificial Intelligence is introduced to take this data and turn it into insight and action that things really begin to get exciting.

In fact, some of our clients are now using multiple layers of AI across their entire service cycle. Often there will be one core AI to draw insight from the vast sets of data across a whole fleet of assets. Something like IBM’s Watson can transmit that data into our own Field Service Lightning platform the second AI, Salesforce’s Einstein takes over as it is designed to handle the more specialist needs of a service call.

The basic premise is that an AI like Watson will assess the data, figure out where it needs to take action and will then communicate directly with Salesforce.The basic premise is that an AI like Watson will assess the data, figure out where it needs to take action and will then communicate directly with Salesforce.

If there is a break-fix scenario or if there is a maintenance scenario where an additional job needs to be added to the next preventative maintenance work order, that is all done in an automated fashion within Field Service Lightning.

The engineer can be automatically scheduled using our own AI (Einstein) to make sure the person scheduled has the necessary credentials. If it is a preventative maintenance scenario then it will look at when the next preventative maintenance job is scheduled, make sure that it’s within the time frame required, put the work order in and make sure the parts are ordered and will be on the truck on the day of the job.

So let’s just recap briefly to think about how this process comes together across all of the various technologies.

Firstly, you need to have the IoT element which in turn is dependent on Cloud Computing and Big Data. Then the various AI capabilities to initially read those events in order to begin automatically creating field service job and finally there is a need for the second AI to actually handle the setup and scheduling of both preventative maintenance and break-fix jobs.

Of course, reaching back to the customer and keeping them informed of the stellar service you are delivering is also key so we need to be connected to the contact centre solution as well. And let's not forget that the customer themselves will want to be on whichever channel they prefer - whether it be a mobile app, online portal or SMS and you need to facilitate that for them in whichever fashion they choose.

Many of our clients are already embracing the growing trend of outcome-based revenue models and field service is one integral element of thisSo all of this really needs to be running on a single dedicated platform for it to work seamlessly - yes, you can definitely bring together a number of different solutions and tools by having various integrations across the network, but the reality is that the cost of doing so would be prohibitive - that’s before you even consider the ongoing challenge of keeping everything updated and working harmoniously.

Indeed, the evident need for a common platform approach that can facilitate the seamless transfer of data and actions across different business divisions is the exact reason why we launched Field Service Lightning in the first place.

Our customers were coming to us and telling us ‘this is what we need to do.’ ‘This is the experience we want to deliver and we need you to add field service to your platform so we can orchestrate all of this.’ Many of our clients are already embracing the growing trend of outcome-based revenue models and field service is one integral element of this, as is sales and marketing and as are all other business units.

The key is being able to let the data and insights flow across the business as a whole and to achieve this you really need a platform that can bring together all of these various functions and technologies we’ve discussed in this article including AI, IoT, Mobile and of course FSM – you need all of that in a single place to make it work effectively, but the benefits of doing so will be felt across each and every department within your organisation.

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Artificial intelligence isn’t just the realms of Hollywood fiction these days and it could have a big impact on field service writes ClickSoftware Steve Mason...

With Ultron currently tearing up The Avengers and The Terminator set to reappear on screens this summer, artificial intelligence (AI) has once again become a big topic of conversation in the technology world. Whilst Hollywood does its best to present AI as a looming precursor to an apocalypse, those working with it now are having a more rational debate about the pros and cons on each side of harnessing the potential of AI.
 
For businesses, the pull of embracing AI is a powerful one. Much like the cloud before it, AI represents an opportunity to immediately tap into a resource. Cloud computing provided the option of upscaling and downscaling computing power in an instant. AI could potentially allow for businesses to tap into extra problem-solving capabilities. Combine both AI and the cloud, and suddenly businesses of all sizes have access to a bottomless pit of resource to call upon regardless of where they operate.

However, for the people working at these businesses, where would that leave them? Will jobs be at risk of machines coming in and taking them away? At a recent debate we hosted with leading academics in this area, the outlook was far less bleak. Instead of AI replacing humans in their entirety, instead merely help them add to their skill-set and challenge them to adapt to change.

 

 
Many of the mundane and monotonous, though hugely important, jobs that require the inputting and handling of data are not necessarily adding a great deal of value to businesses. During the debate it was argued that such time-intensive jobs can and should be handled by AI.
 
For example, any delivery or receipt of goods or services needs to have a trail to demonstrate its completion. This involves manually collecting and sharing that data to prove that is the case. Incorporating an AI function could significantly assist with this process by making the whole thing autonomous.
 
In its place, staff will be able to take on new roles and responsibilities. With that comes a more diverse range of skills needed.
Where some are worried AI could “hollow-out” the middle management of a business, it could well foster an environment where key employees in that middle role are given the opportunity to focus on developing new skills rather than having productivity eaten away by more of the routine tasks that are required of them.
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AI should be seen in the same way new equipment is. When PCs replaced typewriters, people simply began to produce more documents and take on further tasks. It was an adaption.
 
The same will take place as AI begins to be introduced. As has always been the case, it will be up to the individuals to work with the tools they are given and change what they do and how they do it to aid in the progress and success of the business.
 

 

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