IoT Alone Is Not Enough
Jun 17, 2019 • Features • Management • future of field service • IoT
Whilst the Internet of Things is undoubtedly set to become a hugely prominent part of field service delivery in the coming years, it shouldn’t be viewed as a technology in isolation writes Kris Oldland...
I’ve written and spoken about the importance of IoT in field service for many years now. In the past I’ve often compared it to the
mobile revolution, outlining my case for why I think IoT will ultimately have a far bigger impact in our sector than mobile. Now this is not to underplay the importance of mobile in field service.
Mobile was undoubtedly a huge leap forwards in terms of how field service companies were able to deliver efficient field service maintenance. The streamlining of workflows that mobile allowed has seen field service companies be able to do more with the same or even less field service technicians than they could have even imagined possible in the days of triplicate paper documentation and the mighty pen.
Equally, the introduction of increasingly intelligent mobile applications has given field service engineers greater insight into each job they undertake, better support options for when they face an unusual fix and the easy processing of job completion and on site customer feedback.
All of which have seen field service companies become able to truly leverage the often untapped potential of the field service technician as a genuine, trusted, brand ambassador. In many respects the introduction of mobile was a true revolution. That is until we compare it to the potential of IoT.
In this context, actually what mobile brought to the table was the ability to do the things that we always knew were important in terms of service efficiency and customer satisfaction, better. We didn’t revolutionise our fundamental approach to field service when we introduced mobile into the mix.
We just did things exponentially more efficiently. However, whilst the advent of IoT will bring even more efficiency gains, as our engineers become forearmed with the knowledge of exactly which parameters of the asset they are about to work upon are falling outside of acceptable norms, there is the opportunity for a much more radical shift in thinking that IoT presents in addition to this. This is of course, the shift away from traditional break-fix, service level agreement-based service contracts and into the brave new world of guarantees of uptime, truly predictive maintenance and advanced services. This is the true revolution.
However, IoT alone is not enough for us to harness the disruptive force of such a revolution. Much like Cloud before it, it is perhaps the foundational technology upon which we can build even greater innovations.
Machine Learning Is Crucial For Iot Success
One of the throw away phrases that you will invariably hear at conferences, read in articles and discuss in board rooms in pretty much any industry vertical right now ,is that ‘data is the new oil or gold’. I politely disagree with that assertion. Data, as an entity in it’s own right, is quite frankly almost worthless. It has no use-value.
It is without agency and it is without utility. Insight that can be found from mining such data however, is something of truly massive value. When people comment that data is the new currency, they are generally referring to insight. This is why the data scientist was widely posited to become the ‘rock star’ of the twentieth first century not too long ago.
The ability to not only know how to surface insight from data, but more importantly understand exactly which direction your interrogation of that data should go to discover insights that yields true competitive advantage , is a fairly uncommon skill set that blends the analytical and the creative thought processes into one holistic discipline. Yet, as machine learning matures, I see a world where the role of the data scientist will be much more of an initial consultant, someone to make sure a business understands the methodology of data science.
Someone who outlines to them, the whys and the hows, basically lining up the ducks into a row, before setting the AI to do it’s thing. The technology is improving so rapidly now that the actual implementation of such data interrogation programs is likely to sit with senior business execs, rather than senior IT execs driving it.
The value of the human input will not be within the data analysis itself, but in guiding what areas of the business performance should be being measured. The reality is that the sheer volume of data and the speed at which it is generated means that truly utilising and embracing IoT means simultaneously adopting a machine learning strategy at the same time.
Augmenting Augmented Reality
Another technology I have championed for some time now is Augmented Reality (AR) which offers up in the short term at least, a very realistic solution to both the ageing workforce crisis and also the need for field service organisations to reduce the time and costs of training new field service engineers and get them being productive parts of the field workforce as swiftly as possible.
For a long time I have posited the benefits of being able to hold onto the tribal knowledge of an older engineer by allowing them a more convenient support role where their experience can be ‘dialled into’ by the less experienced, newly qualified engineers. This ability to provide ‘see-what-I-see’ over the shoulder remote support is an obvious solution to the two issues I mention above, and I am somewhat surprised that as yet we haven’t seen as large a take up as I would have anticipated - although I do feel we are pushing at an open door in this regard and such developments will inevitably become common place eventually.
However, this I feel is just the very tip of the iceberg in terms of AR in field service and it is when we add into the system a feed of real-time data from an asset, that we will see AR truly flourish. Imagine a field service technician being able to simply look at a device and to get a visual overlay of how that device is performing in real time. The engineer would be able to identify fault, pull up asset history, and access a knowledge bank of the most suitable action for maintenance within just a few moments.
Comparative Analysis Across The Fleet
Perhaps one of the most exciting potential applications of IoT with respect to maintenance and service, is the ability to offer additional layers of advanced services, which could yield newly created revenue streams. One such example could be the application of asset data analysis across a fleet of assets to allow your organisation to provide corrective changes to settings either at the individual asset level, the individual component level or even at the macro level across the whole fleet.
Take this a step further and through the anonymisation of key data sets across an entire install base of your assets, and then the analysis of the operational performance of the install base as a whole - you could be in a position to offer your customers a solution update that could improve productivity by X%. Whilst, admittedly we are still getting our heads around the practical regulatory challenges and big questions around who owns what data, with the waters becoming infinitely more muddied by ill thought out and poorly defined legislation such as GDPR or the Californian Consumer Privacy Act, there are already examples of companies leveraging data from across their whole install base to be able to provide just such intelligence to their customers for an additional cost.
Such solutions are dependent on high level operational performance analytics, which have evolved from the world of Big Data. Don’t Forget To Make It Safe Of course, it is always more preferable to talk about opportunity, but it must be remembered that with whilst in every great challenge we can find opportunity, so to does every new opportunity present a new threat - and the biggest threat of all in a world of data-breaches and connected assets is cyber-security.
The shift to the Cloud reinvigorated the discussion of cyber-security hugely. Many were initially reluctant to make such a move despite all the various benefits of doing so, because the Cloud felt just so much more penetrable and vulnerable than an On Premise solution that had the advantage of being visible, tactile and ‘real’.
The truth is the amount of resources cloud providers like AWS, IBM and Microsoft spend on protecting their cloud offerings are so mind blowing that no on premise solution could be as risk free. Microsoft for example spend over a $1Billion dollars a year and operate 3,500 professional security engineers plus a highly sophisticated AI to thwart the incredible 1.5Million attacks they get every day.
For this reason, I’ve always felt comfortable with the Cloud as being as close as we can get to secure - whilst nothing is ever 100% safe, choosing any of the big three Cloud providers gives you as good protection as your likely to get. However, with IoT at the moment I would hesitate to be just so confident in my prediction. A large part of this is down to the technology still being in something of a ‘wild-west-phase’ with protocols still being ironed out and at the same time a huge surge in consumer appetite for IoT products has driven costs of components down, with many coming out of China which adds an additional question around security against the global geopolitical landscape we find ourselves in.
Not only can IoT components be a weak point of entry to gain access to a wider network, but should the unthinkable happen, they also pose a huge risk in terms of cyber terrorism. If a device can be hacked and it plays a role in wider ecosystem of a factory - could it be conceivable that a cyber criminal could hold a business to ransom shutting them down until they pay up? As with anything the pros and cons of a new solution need to be weighed up, and for me the benefits of IoT in field service do still outweigh the cons, but it is certainly worth putting security at the top of a list of priorities when scoping out the potential of any IoT strategy.
Rubbish In, Rubbish Out.
Finally, just a quick point on building such a strategy. As mentioned earlier, it is important to think of IoT not as an IT project and it is too engrained within business to be viewed in such a way. However, it should equally not be seen as solely as a business solution either. Digital transformation is a significant focus for many companies right now, and if done correctly this should be a platform for embracing IoT - so it is important that your IT leaders within the business also play a major part in such endeavours. But the one thought I would put at the top of any strategy planning meeting would be to ask - what is it we are trying to achieve? I would then go one level deeper and ask ‘What is it that our customers are trying to achieve?’ Then ask the most crucial question that any business has in its arsenal - why?
That should give you the right path to tread down and from there the various different layers of technology that are suitable for the goal you are trying to reach will become apparent and you can plan accordingly. Skip this process though and you may as well go right back to the old adage of the computer - put rubbish in, get rubbish out.
The IoT does offer true revolution within field service, but every revolution requires planning.
I’ve written and spoken about the importance of IoT in field service for many years now. In the past I’ve often compared it to the
mobile revolution, outlining my case for why I think IoT will ultimately have a far bigger impact in our sector than mobile. Now this is not to underplay the importance of mobile in field service.
Mobile was undoubtedly a huge leap forwards in terms of how field service companies were able to deliver efficient field service maintenance. The streamlining of workflows that mobile allowed has seen field service companies be able to do more with the same or even less field service technicians than they could have even imagined possible in the days of triplicate paper documentation and the mighty pen.
Equally, the introduction of increasingly intelligent mobile applications has given field service engineers greater insight into each job they undertake, better support options for when they face an unusual fix and the easy processing of job completion and on site customer feedback.
All of which have seen field service companies become able to truly leverage the often untapped potential of the field service technician as a genuine, trusted, brand ambassador. In many respects the introduction of mobile was a true revolution. That is until we compare it to the potential of IoT.
In this context, actually what mobile brought to the table was the ability to do the things that we always knew were important in terms of service efficiency and customer satisfaction, better. We didn’t revolutionise our fundamental approach to field service when we introduced mobile into the mix.
We just did things exponentially more efficiently. However, whilst the advent of IoT will bring even more efficiency gains, as our engineers become forearmed with the knowledge of exactly which parameters of the asset they are about to work upon are falling outside of acceptable norms, there is the opportunity for a much more radical shift in thinking that IoT presents in addition to this. This is of course, the shift away from traditional break-fix, service level agreement-based service contracts and into the brave new world of guarantees of uptime, truly predictive maintenance and advanced services. This is the true revolution.
However, IoT alone is not enough for us to harness the disruptive force of such a revolution. Much like Cloud before it, it is perhaps the foundational technology upon which we can build even greater innovations.
Machine Learning Is Crucial For Iot Success
One of the throw away phrases that you will invariably hear at conferences, read in articles and discuss in board rooms in pretty much any industry vertical right now ,is that ‘data is the new oil or gold’. I politely disagree with that assertion. Data, as an entity in it’s own right, is quite frankly almost worthless. It has no use-value.
It is without agency and it is without utility. Insight that can be found from mining such data however, is something of truly massive value. When people comment that data is the new currency, they are generally referring to insight. This is why the data scientist was widely posited to become the ‘rock star’ of the twentieth first century not too long ago.
The ability to not only know how to surface insight from data, but more importantly understand exactly which direction your interrogation of that data should go to discover insights that yields true competitive advantage , is a fairly uncommon skill set that blends the analytical and the creative thought processes into one holistic discipline. Yet, as machine learning matures, I see a world where the role of the data scientist will be much more of an initial consultant, someone to make sure a business understands the methodology of data science.
Someone who outlines to them, the whys and the hows, basically lining up the ducks into a row, before setting the AI to do it’s thing. The technology is improving so rapidly now that the actual implementation of such data interrogation programs is likely to sit with senior business execs, rather than senior IT execs driving it.
The value of the human input will not be within the data analysis itself, but in guiding what areas of the business performance should be being measured. The reality is that the sheer volume of data and the speed at which it is generated means that truly utilising and embracing IoT means simultaneously adopting a machine learning strategy at the same time.
Augmenting Augmented Reality
Another technology I have championed for some time now is Augmented Reality (AR) which offers up in the short term at least, a very realistic solution to both the ageing workforce crisis and also the need for field service organisations to reduce the time and costs of training new field service engineers and get them being productive parts of the field workforce as swiftly as possible.
For a long time I have posited the benefits of being able to hold onto the tribal knowledge of an older engineer by allowing them a more convenient support role where their experience can be ‘dialled into’ by the less experienced, newly qualified engineers. This ability to provide ‘see-what-I-see’ over the shoulder remote support is an obvious solution to the two issues I mention above, and I am somewhat surprised that as yet we haven’t seen as large a take up as I would have anticipated - although I do feel we are pushing at an open door in this regard and such developments will inevitably become common place eventually.
"When people comment that data is the new currency, they are generally referring to insight..."
However, this I feel is just the very tip of the iceberg in terms of AR in field service and it is when we add into the system a feed of real-time data from an asset, that we will see AR truly flourish. Imagine a field service technician being able to simply look at a device and to get a visual overlay of how that device is performing in real time. The engineer would be able to identify fault, pull up asset history, and access a knowledge bank of the most suitable action for maintenance within just a few moments.
Comparative Analysis Across The Fleet
Perhaps one of the most exciting potential applications of IoT with respect to maintenance and service, is the ability to offer additional layers of advanced services, which could yield newly created revenue streams. One such example could be the application of asset data analysis across a fleet of assets to allow your organisation to provide corrective changes to settings either at the individual asset level, the individual component level or even at the macro level across the whole fleet.
Take this a step further and through the anonymisation of key data sets across an entire install base of your assets, and then the analysis of the operational performance of the install base as a whole - you could be in a position to offer your customers a solution update that could improve productivity by X%. Whilst, admittedly we are still getting our heads around the practical regulatory challenges and big questions around who owns what data, with the waters becoming infinitely more muddied by ill thought out and poorly defined legislation such as GDPR or the Californian Consumer Privacy Act, there are already examples of companies leveraging data from across their whole install base to be able to provide just such intelligence to their customers for an additional cost.
Such solutions are dependent on high level operational performance analytics, which have evolved from the world of Big Data. Don’t Forget To Make It Safe Of course, it is always more preferable to talk about opportunity, but it must be remembered that with whilst in every great challenge we can find opportunity, so to does every new opportunity present a new threat - and the biggest threat of all in a world of data-breaches and connected assets is cyber-security.
The shift to the Cloud reinvigorated the discussion of cyber-security hugely. Many were initially reluctant to make such a move despite all the various benefits of doing so, because the Cloud felt just so much more penetrable and vulnerable than an On Premise solution that had the advantage of being visible, tactile and ‘real’.
The truth is the amount of resources cloud providers like AWS, IBM and Microsoft spend on protecting their cloud offerings are so mind blowing that no on premise solution could be as risk free. Microsoft for example spend over a $1Billion dollars a year and operate 3,500 professional security engineers plus a highly sophisticated AI to thwart the incredible 1.5Million attacks they get every day.
For this reason, I’ve always felt comfortable with the Cloud as being as close as we can get to secure - whilst nothing is ever 100% safe, choosing any of the big three Cloud providers gives you as good protection as your likely to get. However, with IoT at the moment I would hesitate to be just so confident in my prediction. A large part of this is down to the technology still being in something of a ‘wild-west-phase’ with protocols still being ironed out and at the same time a huge surge in consumer appetite for IoT products has driven costs of components down, with many coming out of China which adds an additional question around security against the global geopolitical landscape we find ourselves in.
Not only can IoT components be a weak point of entry to gain access to a wider network, but should the unthinkable happen, they also pose a huge risk in terms of cyber terrorism. If a device can be hacked and it plays a role in wider ecosystem of a factory - could it be conceivable that a cyber criminal could hold a business to ransom shutting them down until they pay up? As with anything the pros and cons of a new solution need to be weighed up, and for me the benefits of IoT in field service do still outweigh the cons, but it is certainly worth putting security at the top of a list of priorities when scoping out the potential of any IoT strategy.
Rubbish In, Rubbish Out.
Finally, just a quick point on building such a strategy. As mentioned earlier, it is important to think of IoT not as an IT project and it is too engrained within business to be viewed in such a way. However, it should equally not be seen as solely as a business solution either. Digital transformation is a significant focus for many companies right now, and if done correctly this should be a platform for embracing IoT - so it is important that your IT leaders within the business also play a major part in such endeavours. But the one thought I would put at the top of any strategy planning meeting would be to ask - what is it we are trying to achieve? I would then go one level deeper and ask ‘What is it that our customers are trying to achieve?’ Then ask the most crucial question that any business has in its arsenal - why?
That should give you the right path to tread down and from there the various different layers of technology that are suitable for the goal you are trying to reach will become apparent and you can plan accordingly. Skip this process though and you may as well go right back to the old adage of the computer - put rubbish in, get rubbish out.
The IoT does offer true revolution within field service, but every revolution requires planning.
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