ARCHIVE FOR THE ‘future-of-field-service-2’ CATEGORY
The launch of Digital Vision for Mobility was marked with a keynote address by Atos UK & Ireland SVP for Strategy & Communications and former Transport Advisor to the Mayor of London, Kulveer Ranger, to an audience at University College London on 4 June.
Introducing the paper to illustrate the future of transport in London, the address to business management students underlined the profound transformation experienced across the mobility industry, underpinned and enabled by digital technology.
“Increasingly with population growth and denser metropolitan conurbations, we see the need to support the mass movement of people and goods with efficient, effective and integrated multi-modal public and personal transport systems,” said Kulveer Ranger. “Transport operators are beginning to rely heavily on data: harvested both from within their own networks and systems and from the personal mobile devices of individuals. To realise a vision of truly personal mobility, vast amounts of data will need to be aggregated. This will be a huge technological feat for innovative integrators and digital architects.”
The Atos Digital Vision for Mobility paper sets out how digital technology has transformed the UK’s transport sector and considers the role of AI, automation and blockchain in determining the mobility solutions of tomorrow for road and rail, broader public transport and logistics. Contributions from ITS-UK, Google, Siemens, KPMG, Worldline, TfL, MyTaxi and TechUK explain how data is being used as a driver for intelligent infrastructure and how developments like IoT can be strategically deployed to create more reliable services and more convenient access for transport users, including the rail network.
Commenting on the launch of the report, Adrian Gregory, Atos Senior Executive Vice President and CEO, UK & Ireland, said: “More change is now underway across the transport and logistics industry than at any time since the invention of the combustion engine. Vastly increased computing power and hyper-connectivity are helping to transform the operation and maintenance of vehicles and national infrastructure.”
Mark Ferrer, Operations Director – Digital Railway, Siemens Rail Automation UK, added: “Digital technologies are integral to the future of rail, enabling train operators and infrastructure owners to safely increase the capacity, reliability and efficiency of their networks and assets whilst increasing levels of passenger satisfaction. For operators and passengers, digital signalling and control systems together with advanced data and analytics are key to meeting intense demands while driving down costs – which can only be good for the UK’s economic future.”
Berg Insight estimates that global cellular IoT module shipments increased by 16 percent in 2018 to a new record level of 221 million.
Berg Insight estimates that global cellular IoT module shipments increased by 16 percent in 2018 to a new record level of 221 million.
Annual revenues grew faster at 24 percent, reversing the previous trend of decreasing average module prices. The 3GPP standards for LTE – Cat M and NB-IoT – will contribute substantially to growth in the next coming five years.
These new standards are designed to be less complex to limit power consumption and are priced more favourably to address the mass market and make it viable to connect entirely new applications. In the first half of 2019, several vendors announced 5G NR modules that will become available to developers in the second half of the year. Early adopters will include companies active in the PC, networking and OEM automotive segments.
The results of Berg Insight’s latest cellular IoT module vendor market share assessment show that the four largest module vendors have 61 percent of the market in terms of revenues. “Annual module revenues for the four largest market players Sierra Wireless, Sunsea AIoT, Gemalto and Telit increased by 13 percent to US$ 1.85 billion, with the total market value reaching approximately US$ 3.0 billion”, says Fredrik Stalbrand, Senior Analyst at Sweden-based IoT analyst firm Berg Insight. Sierra Wireless leads IoT module revenues, followed by Sunsea AIoT and Gemalto. Sunsea AIoT leads in shipments and Quectel is number two in terms of volumes and in fifth place in terms of revenues. Fibocom reported the highest growth of 122 percent during the year, reaching US$ 189 million in cellular module sales.
The year marks the first in which a China-based vendor ranks as high as the second largest cellular IoT module vendor by revenue and six of the top ten vendors were from China in 2018. Sunsea AIoT emerged as a new major industry player in 2017 through the acquisitions of Longsung and SIMCom, which had been the market leader by volume for three consecutive years. While there has been some consolidation among the larger suppliers, the long tail of companies with activities in the cellular IoT module market is growing. A number of new players have been attracted to the market, particularly in the emerging NB-IoT and LTE-M segment. Notable examples include the major Bluetooth LE SoC vendor Nordic Semiconductor and the Japanese electronics company Murata.
Previous investment in the 5G testbeds and trials programme has driven work in the healthcare, tourism, transport and broadcasting sectors. The latest investment will support similar work in the logistics and manufacturing sectors. Projects will trial ways which can help these sectors increase their productivity and output, boosting the UK economy. The trials could cover different manufacturing processes as well as across road, air, and sea based freight logistics.
The funding was announced by Digital Secretary Jeremy Wright at the 5G World Conference as part of London Tech Week. The latest round of investment is through the £200 million project to test 5G technology that’s up to ten times faster than 4G and able to support more than a million devices per square kilometre.
Wright said: “As part of our modern Industrial Strategy, we’re making sure that Britain has a telecoms infrastructure that is fit for the future. “5G is about more than mobile phone consumers having a fast and reliable connection anywhere in the country. It’s a vital piece of technology that can be used to improve the productivity and growth of our industrial sectors. That’s why we’re excited to develop new trials in areas such as manufacturing and logistics that can really benefit from 5G.” In addition to the new funding, the Government has confirmed that it will consult on proposals to simplify planning processes in England to both support the further roll-out of 4G and aid the faster introduction of 5G.
Hamish MacLeod, Director at Mobile UK, said: “Getting the planning system right for future 5G and today’s 4G networks is critical to ensure the UK continues to lead the world in digital connectivity. It is right that the Government has announced it is to look at simplifying planning processes and we stand ready to work in partnership to ensure this can happen as quickly as possible to aid the continued rollout of mobile networks.”
This is part of the Government’s long-term strategy for meeting its digital connectivity targets, outlined in the Future Telecoms Infrastructure Review. The plans involve tackling barriers to deployment and creating the right conditions for investment to deliver better network coverage that supports the way we live and work today. A key part of this is making new spectrum available to increase capacity for mobile connectivity.
The Ministry of Defence, in partnership with the Department for Digital, Culture, Media and Sport, has committed to making 168MHz of new spectrum available to facilitate the deployment of fixed and mobile networks. This means the Government has already exceeded its target to make 500MHz of public sector spectrum available for commercial use by 2020, and will continue to work with departments to explore opportunities for more spectrum to be made available.
Rapid early momentum and enthusiasm for 5G has led Ericsson to forecast an extra 400 million enhanced mobile broadband subscriptions globally by the end of 2024. The June 2019 edition of the Ericsson Mobility Report forecasts 1.9 billion 5G subscriptions – up from 1.5 billion forecasted in the November 2018 edition – an increase of almost 27 percent.
Other forecasts have also increased notably as a result of the rapid 5G uptake. 5G coverage is forecast to reach 45 percent of the world’s population by end of 2024. This could surge to 65 percent, as spectrum sharing technology enables 5G deployments on LTE frequency bands.
Communication service providers in several markets have switched on 5G following the launch of 5G-compatible smartphones. Service providers in some markets are also setting more ambitious targets for population coverage of up to 90 percent within the first year.
The strong commitment of chipset and device vendors is also key to the acceleration of 5G adoption. Smartphones for all main spectrum bands are slated to hit the market over the course of this year. As 5G devices increasingly become available and more 5G networks go live, more than 10 million 5G subscriptions are projected worldwide by the end of 2019.
The uptake of 5G subscriptions is expected to be fastest in North America, with 63 percent of anticipated mobile subscriptions in the region being for 5G in 2024. North East Asia follows in second place (47 percent), and Europe in third (40 percent). Fredrik Jejdling, Executive Vice President and Head of Networks, Ericsson, says: “5G is definitely taking off and at a rapid pace. This reflects the service providers’ and consumers’ enthusiasm for the technology. 5G will have positive impact on people’s lives and businesses, realizing gains beyond the IoT and the Fourth Industrial Revolution.
However, the full benefits of 5G can only be reaped with the establishment of a solid ecosystem in which technology, regulatory, security, and industry partners all have a part to play.” Total mobile data traffic continued to soar globally in Q1 2019, up 82 percent year-on-year. It is predicted to reach 131 exabytes (EB) per month by the end of 2024, at which time 35 percent is projected to be over 5G networks.
There are 1 billion cellular IoT connections globally, a figure that is expected to rise to 4.1 billion by the end of 2024, of which 45 percent are represented by Massive IoT. Industries using Massive IoT include utilities with smart metering, healthcare in the form of medical wearables, and transport with tracking sensors. The June 2019 report also features three articles written jointly with service providers that offer a glimpse of the progress being made in markets that are on the verge of, or already deploying 5G.
With Telstra in Australia, Ericsson explores how to manage the ever-growing demand for data and video while maintaining consumer experience, particularly for live content streaming. MTS in Russia helps to describe how mobile networks should evolve to ensure the level of network performance that will meet customer experience expectations during preparations for 5G. The article co-written with Turkcell in Turkey looks at how network performance and service offerings are managed in a successful fixed wireless access (FWA) implementation.
How To Develop Databased Solutions
Today any machine can be digitized and connected; collecting the data is not an issue; what is becoming more important is how the field data can be exploited to identify the right action to be taken.
This creates a very complex problem, as the right data must be transformed so that only the right information, at the right time, in the right form can be delivered to the right decision-maker, independently of the problem domain - e.g. route cause analysis, demand forecasting, productivity optimisation, spare parts delivery. Helping people taking decisions can be seen as a smart service, that is designed on the base of a thoroughly understanding of the business complexity.
Ecosystems made of people and equipment, business objectives and strategies, as well as personal needs, attitudes and preferences (must-have’s, nice-to-have’s) of each operators. Once these needs are fully understood, information can be elaborated from data to create the right insights. The Data2Action framework provides guidance towards the development of data-driven services. The understanding of why and how customers interact with assets is achieved using Design Thinking approach.
Principles Of Service Design Thinking Underpin the Data2action Framework
A good design is not only a matter of aesthetics. When designing a product, many factors have to be considered. For example, how the product is going to be used, and by who. This determines the product functions, form, materials, colors, etc. This requires the ability to understand what the product user is trying to achieve (an outcome, an experience).
The same applies to service design, in which the object to be designed is a process which aims to reach a goal, through the use of products, software applications, information, etc. The challenge is that there are many more people involved in the consumption and delivery of the service, the service relies on collaboration, the service is mostly intangible. The Service Design approach is based on a hands-on, user-centric approach to problem definition and idea/solution generation can lead to innovation.
This is of utmost importance, as the application of these principles can lead to competitive advantages. Remember you only do things that are of value to you in one form or other. Service Design Thinking (SDT) is an approach that aims at designing services by applying different tools based on five principles.
Service design thinking should be:
• User centred;
Understanding The Problem: Why Understand First?
How can a problem or challenge be successfully solved without understanding it properly? Well, it can not. Without a deep understanding, disruptive solutions will not work, or you will be applying sticky plasters. The challenge lying ahead of you is to understand, describe and visualize the situation. The understanding of a complex problem requires to know who the involved people and equipment are, and how the processes in which they are operating runs. The understanding phase of the Data-2-Action framework consists of mapping the (OVERALL) job-to-be-done of the customer, mapping the actors and using avatars to build the ecosystem to discover and appraise who and what is involved.
Principles for Digital Service Development: How To Generate The Best Ideas
The problem statements and the ecosystem visualization developed provides a solid foundation for the development of new ideas and solutions for services. Some new ideas may have already appeared and can be improved in this phase.
These cases, also called scenarios or user stories, can be visualized using the customer journey blueprint. In the customer journey blueprint, the processes, actions, and involved personas/avatars are visualized to display the desired situation, in which the problems are solved.
Outcomes for each actor here should be clearly defined along with any payoffs. Working in pen and paper works really well. For Smart Services with many actors and many machines expect there to be many scenarios to focus on and even more ideas to provide improvements. In the ideation stage, many ideas will be generated.
The ideas need to be rated in order to evaluate which are worth to be prototyped. For selecting the best ideas, an idea scoring system is best.
Building Valuable Solutions: Creating Information From The Raw Data
With the overview of the ecosystem of people, processes, and machines it becomes clear from the scenarios and user stories of where the data is produced and who needs to consume information derived from it. Prototyping it is a way to validate our ideas and possible solutions and it should be fast and keep concepts as simple as possible. This avoids spending too many resources on building solutions only to then finding out that it does not work.
The best way is to create hand-drawn dashboards or widgets which represent the solution and test them as quickly as possible before starting with the actual implementation (often coding!). The process of drawing dashboards may also reveal new ideas which can be useful or new insights into whether the solution is technically visible or not. Many dashboards should be created, to keep it organized we use the Case Actor Matrix (CAM).
This tool allows matching Actors with a Cases (we use a scenario before) and the dashboard enabling the understanding of their purposes - how would you use it to help make a decision. A logical cascade should be build and dashboard widgets should be reused as much as makes sense. These conceptual solutions need to be challenged from a technical perspective.
We use a Source Target Link Matrix (STL Matrix) to show the information needed from the conceptual point of view. We define the requirements and quality of the data needed to develop the dashboards. The matrix distinguishes between existing data and data that needs to be collected, as well as adjustments and improvements that have to be made to the databases
Test Ideas And Improve
The testing is essential within the data2action frameworks and Service Design. It should happen as quickly to avoid the development of solutions, which do not fulfill the identified case and or are not technical visible. The best method for testing the usability is to hand over the dashboard to the target actor and ask them to try to use it and listen to their feedback based on the feedback the usefulness can be improved. New ideas also come from the feedback discussions. The technical aspect needs to be evaluated as well. Meaning, that the information derived from the data is actually significant. This is determined by the data experts and the user.
According to a new research report from IoT analyst firm Berg Insight, global shipments of NB-IoT devices reached 53 million units in 2018.
Annual shipments are expected to almost triple in 2019 reaching 142 million units. Commercial deployments are essentially confined to China, where the semiconductor companies HiSilicon and MediaTek account for a large part of the NB-IoT modem volume.
“NB-IoT device shipments will ramp up quickly on the European and North American market in the next 18 months”, says Fredrik Stalbrand, Senior Analyst, Berg Insight. “While early deployments have so far been focused on traditional verticals such as smart metering, we expect to see NB-IoT being integrated into a broader set of products in 2019–2020, including home appliances, door locks and smoke detectors”. Combining low power consumption and the inherent security of cellular connectivity, the NB-IoT standard provides multiple benefits to the connected home and building segment.
The transition from 2G to 4G is a global trend, accelerated by NB-IoT. The major North American carriers were late adopters of the technology but are now adding or trialling NB-IoT in their networks as a complement to LTE-M. T-Mobile was the first to launch an NB-IoT service in 2018 and was followed by Verizon and AT&T in the first half of 2019.
In Europe, the leading mobile operators are making good progress towards ubiquitous NB-IoT coverage. Vodafone has been among the leaders in the development of NB-IoT and will roll out commercial services across all its networks until 2020. At the end of 2018, the operator had live NB-IoT services in eleven countries, including Germany, Italy, UK, Spain and the Netherlands. Deutsche Telekom launched in Germany and the Netherlands in mid-2017 and offered coverage in five additional countries at the end of 2018. Telefónica has launched its first NB-IoT networks in Spain and Germany.
Other mobile operators offering NB-IoT in the region include Orange in Belgium, TIM in Italy, MTS in Russia, Telia and Telenor in the Nordics, along with a number of national mobile operators. Australia, Singapore, South Africa, South Korea, Japan, Indonesia, Brazil, Turkey and the UAE are other examples of countries where network services are available.
Problem-solving is an essential skill set for all Trusted Advisors, yet many of us take it for granted. We assume our Technicians and Engineers must be great problem solvers because that is what they do. Most have developed ways to solve problems through on the job training and mentoring from experienced colleagues, but very few have been educated in this key professional competence – logical problem solving!
This lack of competence can cost companies considerable money and customer loyalty. You will have all experienced problems that don’t seem to go away, where teams of people seem to solve, resolve and resolve again the same issue. These are the type of problems that are complex, multifaceted and can costs companies thousands and sometimes millions of pounds.
They require a disciplined process and in truth most companies do not sufficiently support their staff in developing this critical skill set. As data analytics becomes increasingly influential in field service processes, so logical problem solving skills will become more important!
Increasingly the solutioning of known problem sets will be done through self-service, lower skilled technicians or even automated through remote services. Companies will want their skilled technicians to focus on the more complex technical issues as well as fixing the customer relationship.
How can you up the game of your technical teams, save your organisation costs and increase customer loyalty?
Best in class companies with a Trusted Advisor mindset where the goal is to continually create more value for their customers, embed in their culture a logical problem-solving wheel, which starts and finishes with the customer. This gives companies a common language and process to solve problems, which is critical to improving the skill levels of all their employees. When problems are complex, it develops a good discipline, especially around problem definition and data collection.
As the ability of service organisations to leverage advanced analytics to analyse unstructured data found in service reports becomes more widespread, so a common language becomes even more important in identifying and predicting fault patterns. There are also many tools for both analysis and solutioning that help break open the problemsolving process. Some examples from the problem analysis phase are the 5 W’s (Who, What, Why, Where, When) for situational fact finding, the 5 Why Method for root cause analysis and Fishbone diagrams, sometimes known as Ishikawa or FaultFinding Trees.
The importance of statistical skills in the future should not be underestimated, as data becomes an essential resource in the service resolution processes. Many of you will know these tools from your professional experiences and probably take them for granted as part of your work life. However, you will be surprised at how few of your colleagues really understand how to solve problems. Many will often jump to the first solution that fits the symptom’s they are seeing.
They will switch components in & out to see if the symptom goes away without really understanding the root cause. This leads to significantly higher costs in managing spare parts and many more “No fault Found” from returns reports from component suppliers.
Research by Cranfield University ‘A framework to estimate the cost of No-Fault-Found events’ published in 2016 showed examples from the Aerospace industry where NFF cost companies between one to 300 million dollars and in some cases account for up to 80% of failures. Indeed, not solving the root cause of problems has led to industries developing their own problem solving methods.
If you have worked in the automotive industry, no doubt you will have experienced the 8D problem solving process and will probably be familiar with 6 sigma methods. Those of you with the experience of large field organisations will know that service leaders such as Xerox or Vaillant make logical problem solving a core skill in which they train their whole organisations, not just their service technicians. For these organisations, just solving the technical problems is not enough.
They recognise that the art of creating customer loyalty comes from an ability for the organisation to fix the customer. Hence a critical element of any work in logical problem solving is to recognise the role of the problem solver in the process. For example, if a service technician perceives their role as ‘fixing equipment’, this is what they will focus on.
They will miss the fact that the root cause might be a lack of customer training or an external factor such as raw material quality or the operating environment. This wider view of the problem, and an understanding of the problem solvers role in the effectiveness of the process, can save companies huge amounts of cost, and deliver more value to customers.
We often refer to this mindset as being the Trusted Advisor, and it is the reason why excellence in Problem Solving is such a vital and often overlooked capability that needs to be developed. We are all aware that the ability of any organisation to effectively solve problems is critical to its success in terms of costs and customer loyalty. Leading global organisations recognise this and train their teams in logical problem solving, yet for many organisations it is a capability that is taken for granted. And in the context of forming deeper lasting relationships with customers, we also should recognise that problem solving is an essential skill set of being perceived as a Trusted Advisor.
If you would like to know more about developing Trusted Advisor programmes in your business, then you can contact Nick at email@example.com.
The equipment segment accounts for the largest share of the total, representing connected units deployed on machines and vehicles used in mining operations, according to new research from Berg Insight. This includes solutions ranging from OEM telematics systems on mining equipment to advanced connected solutions supplied by mining technology specialists.
The people segment includes various solutions deployed to support the safety and productivity of mining personnel, while the environment segment consists of sensor technology implemented for environmental monitoring of the mine itself. Growing at a compound annual growth rate of 15.5 percent, the total installed base of connected mining solutions in all these segments is forecasted to reach close to 1.2 million units in 2023.
The top players active in the connected mining space include strikingly different types of companies, ranging from specialised independent technology suppliers of varying sizes up to the leading mining equipment manufacturers.
“Many of the key players today serve both surface and underground mining customers”, said Rickard Andersson, Principal Analyst, Berg Insight. The surface segment is dominated by Modular Mining Systems (owned by Komatsu), Hexagon Mining, Wenco International Mining Systems (owned by Hitachi Construction Machinery) and Caterpillar through its Cat MineStar suite. “Modular, Hexagon and Caterpillar all serve underground customers in addition to a primary presence in the surface segment, while Wenco is fully focused on surface mining”, continued Mr. Andersson. He adds that VIST Group is also active in the surface segment and serves some underground operations as well.
Examples of key technology providers focused specifically on underground applications are Newtrax Technologies (recently acquired by Sandvik) and Mobilaris (partially owned by Epiroc). The underground segment is in general less mature and more fragmented. “Mine Site Technologies, MICROMINE and rapidBizApps are additional players in the underground segment that all also serve surface customers to varying extents”, concluded Mr. Andersson.
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.
Under the agreement, Ericsson will provide SoftBank with radio access network equipment, including products from the Ericsson Radio System portfolio. This will enable SoftBank to launch 5G services on their newly granted 3.9-4.0 GHz and 29.1-29.5 GHz bands for 5G New Radio (NR).
Ericsson will reinforce SoftBank’s existing LTE network while optimizing its 5G network. Ericsson Radio System products for this purpose will be deployed in several regions. With Ericsson Radio System, SoftBank can boost its spectrum assets.
Chris Houghton, Senior Vice President, Head of Market Area North East Asia, Ericsson, says: “SoftBank and Ericsson have been partners since the 2G era and we are thrilled to support them on this latest part of their technology journey. With the help of our advanced product portfolio, SoftBank can unlock the potential of 5G for Japanese society and we look forward to building on our long-standing partnership.”
Ericsson and SoftBank initiated joint proof-of-concept activities in 2015 and have successfully expanded their collaboration to include 5G testing of multi-bands, including 28 GHz and 4.5GHz. Both companies will continue to jointly explore 5G use cases, reinforce SoftBank’s existing LTE network while optimizing its 5G network and commit to realize 5G commercial services within this fiscal year