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Manuel Grenacher, General Manager SAP Service Cloud at SAP discusses the latest revolution: the Industrial Internet of Things...

Is Machine Learning the future of service? SAP's Manuel Grenacher thinks it could be...

Bill McDermot has left SAP to take-up CEO role at ServiceNow vacated by John Donahoe who joins Nike.

The world of field service delivery is going through significant transformation currently and at the heart of that transformation lies Artificial Intelligence, Manuel Grenacher, GM of SAP Service Cloud writes...


Many industries and domains are already using artificial intelligence (AI). When it comes to field service management, however, AI is still a new aspect in the field of service excellence. Imagine customers calling their service provider because an installation is malfunctioning; a machine has to be maintained, or an urgently needed spare part is needed. It is always essential that a service technician is on-site quickly – not any technician, but the one with the required know-how and tools.

To support this process, field service management solutions based on AI help to coordinate and organize customer requests. Additionally, the waiting time for customers until their problem is fixed can be reduced immensely.

Since traditional resource planning can no longer cope with the enormous volume of service orders that arise, AI is an ideal solution. Artificial intelligence uses customer information and data to empower service companies so that they are able to make strategic and informed decisions.

Thorough analyses powered by AI help to streamline project planning, staffing requirements, new products, inventory management, and customer service.

Automation reduces workloads
Due to an ever-growing number of work orders, the time pressure on service staff is increasing. Automated bot systems based on artificial intelligence, such as chatbots, represent a forward-looking solution in field service management.

Chatbots assist service technicians and customers alike by giving them 24/7 feedback based on the company’s FAQs or data sheets as well as manuals to solve minor machinery defects autonomously. Thus, first level enquiries can be answered immediately, and on-site visits can be reduced.

In addition to chatbots, artificial intelligence is key to the automation of workflows in service sectors. Field service management solutions based on AI can take over the role of dispatchers, for example: They analyze customer inquiries and assign jobs to the most suitable service technician based on their qualifications, location, and availability. Companies benefit from more efficient and faster operational planning of their service staff. Consequently, advantages for customers are improvements in the fields of time and expert service.

Multichannel support, a recipe for happy customers
Customers increasingly expect service companies to be available on all possible channels in order to receive the best support for their issue.
AI applications can be used to collect, analyze, evaluate, and forward requests received via e-mail, social media, webchat, telephone, or in personal conversations with employees, that can then choose between different answer options. If necessary, these answers can be personalized and individualized to the customer’s request.
An approach like this accelerates the exchange with customers and enables real-time as well as multichannel support.

AI algorithms enable personalized service
Field service management solutions can gather data and, as a result, companies can access vast quantities of information with every single customer contact. Furthermore, AI algorithms help to analyze the collected data and draw conclusions for future deployments of service technicians by extracting relevant pieces of information.

Additionally, they offer information about when a service order is due or which tools are required. Machine learning also helps to calculate how long the next service deployment will take. All results and findings are stored in the field service management software and other linked systems so service technicians can access customer information at any time and location to customize their service according to the client’s needs.

Artificial intelligence is one of the most important future technologies in the area of field service management to be used to increase service excellence and to please customers.

It enables and improves a smarter and more efficient workforce by delivering reliable customer support in real-time. 

Manuel Grenacher is GM of SAP Service Cloud

In today’s society whereas consumer’s we are becoming increasingly used to and expectant of instant results is an obvious challenge for field service organisations but can remote services help bridge the gap? Manuel Grenacher, CEO, Coresystems discusses...

With the pervasiveness of the Internet of Things (IoT), everything from device performance to customer interactions has become faster and more connected. Devices that require maintenance and repair now operate on an accelerated timeline of immediately notifying the user when service is needed. Because of this, customers expect real-time responses, leaving little to no time for a field service technician to travel to the site, troubleshoot the issue and fix the device. Therefore, to maintain and improve customer satisfaction, technicians are exploring ways to provide the same level of onsite, but while remote.

The idea behind remote technicians stems from the technician’s ability to diagnose a problem, determine possible solutions, and lay out a plan for issue resolution - all before they take one step onto the worksite. In a perfect world, remote technicians essentially only have to leave their workstations once to perform tasks that require a high level of skill, or perhaps not at all for routine maintenance and repair. Naturally, this drastically cuts down the amount of travel cost and time and total project duration needed to solve an issue with a customer’s device, streamlining the entire service request from issue detection to resolution.

Field service technicians no longer need to blindly infer what is happening on the broken device based on descriptions from less experienced users, nor do they need to fumble through repair instructions over the phoneField service technicians no longer need to blindly infer what is happening on the broken device based on descriptions from less experienced users, nor do they need to fumble through repair instructions over the phone. Indeed, the remote technician takes full advantage of tools such as augmented reality, artificial intelligence, and even the IoT itself to deliver the same experience as a technician standing in front of the customer would.

So how does it work? It starts with putting the proper infrastructure in place to allow technicians to troubleshoot issues on devices and machines from afar. Taking issue detection as an example, remote technicians can use augmented reality to share a mobile phone screen with a customer for a visual walkthrough of the issue. From there, the remote technician can schedule an onsite appointment if needed and manage the parts orders needed for specific projects, ensuring all the necessary assets are in place well in advance.

To be fair, managing a workforce of remote technicians is no easy task. In order to optimize your field service operations, it is extremely beneficial to be able to automatically assign the most qualified and available technician for respective service requests, taking into account expertise, location, and availability. As a fail-safe, the onsite technicians should have easy access to online product specifications and other assets needed to complete service requests. Additionally, similar to how remote technicians use augmented reality to connect to the customer for issue detection, on-site technicians can connect to more experienced journeyman technicians back at headquarters to troubleshoot unforeseen issues. This creates a network of knowledge that will keep project duration to a minimum, improving efficiency for the technician while onsite.

The way in which field service technicians work has evolved and is continuing to do so. The next generation of technicians are prioritizing independence, autonomy, and flexibility, on top of foundational knowledge and customer service experience. As the IoT continues to grow, so will the need for remote technicians, and the field service industry assuredly has the infrastructure to maintain the high level of customer satisfaction that we strive for today.

What are your experiences experimenting with a more remote field service workforce? Feel free to share your thoughts in the comments section below!

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Field Service Management is becoming an increasingly complex beast, particularly in the face of increasing customer demands - the solution lies in real-time writes Manuel Grenacher, GM of SAP Field Service Management...

The longer a plant is malfunctioning or down, the more costs companies have to bear. To avoid that, IoT-based solutions such as condition monitoring and predictive maintenance enable organizations to oversee machines in real-time. At the same time, however, these concepts result in increased complexity: In the event of emergency, companies expect that problems with their plants will be remedied immediately.

For service technicians, that means to act fast upon requests: their customers do not only expect high-quality service, but also the speed of service delivery should be up to their expectations. But how to keep up with the increasing demand? Intelligent planning in an ever-growing digitalized world is crucial to companies: it builds the foundation for excellent field service. Thus, on-demand service is no longer sufficient – organizations have to go beyond their conventional methods to handle customer requests.

More than ever, field service software helps to keep up with the pace: technicians are able to receive information that is accurate to the minute and can respond directly. Thanks to modern transformation technologies, upcoming problems can be detected right from the start and inquiries can be processed in real-time. Companies need to be the master of your offered services. Real-time service delivery can be easily implemented, and the result is remarkable: more satisfied customers and an increased turnover.

Requirements For Digital Twins In Service
Sufficient sensors and a systematic evaluation of the data are the essential basis to predict imminent component failures – an approach that is already feasible today. However, technical possibilities are still far from being exhausted right now. Due to ongoing depreciations or for other economic reasons, companies are only gradually investing in plants equipped with modern IoT technology. IoT, however, will become more affordable in the near future. Sensors will therefore spread continuously while at the same time becoming easier to use, more resistant and cheaper.

New concepts for real-time monitoring
Predictive maintenance and condition monitoring are two examples for future-oriented solutions that support service technicians in delivering the right service at the right time. The concepts are able to identify when maintenance work is required by collecting data from the machine itself, previous service calls and connected tools. Under certain circumstances, maintenance can even be conducted by the machine itself without human interaction.

Furthermore, technologies providing predictive maintenance and condition monitoring do not only help to maintain plants, they also steer the technician toward the root cause of the problem: the service specialist knows when a problem will occur and is able to initiate preventive actions – In addition to malfunctions and interruptions of plants being reduced, production capacity increases.

The potential of digital field service and crowd service
If you want to offer high-quality field service to your clients, you cannot avoid digitizing your work processes. With the rise of IoT, a wide range of new solutions have emerged, for example digital field service management solutions. By using such software, service providers can record, sort, and prioritize customer data easily. This helps to quickly assign technicians to customer requests and process them. Digital field service management solutions store information on the current order, the customer history and machines, which leads to a high first-time fix rate. But what to do if a plant unexpectedly shuts down and no technician is available?

A nightmare not only for operators, but also for manufacturers and service-providers. To master this challenge, the implementation of a crowd service approach can help to strategically avoid service shortage. Companies can reach out to their partner ecosystem, which may consist of the enterprise group, subsidiaries, partners or freelancers. In that way, technicians can be sent to the client by using on-demand distribution.

As a result, resources can be bundled, services improved, and customer satisfaction increased. Increased service reach through real-time support Real-time service is not only about being quickly on-site – it is also about giving support via email, video, chat and social media as well as via client portals and mobile applications.

At the same time, many customers want to be actively involved: with the help of self-service portals they can check operational data, view tutorials, request remote support from an external support team, or even make an appointment with a service technician.

Offering clients a range of real-time contact opportunities, and, thus, being available 24/7, ensures a sustainable and positive customer experience.

Manuel Grenacher is General Manager of SAP Field Service Management

Digital Twins have been discussed in tech circles for a while now, but their potential value in field service is still only just beginning to filter through, Manuel Grenacher, SAP Field Service Management, explains the role they could play in improving service delivery. 

Have you ever considered the possibilities and potential of digital twins for your customer service?  Don’t worry, we are not talking about virtual figures in cyberspace that are modelled after the user just like avatars.

A digital twin represents a real object in the digital world. Digital twins are composed of data and algorithms and can be coupled with the real world via sensors.  They form the basis for a digital customer service and other industry 4.0 related processes. In short, “digital twins” recreate a system in the computer. Ideally, data from the engineering phase – from 3D models to detailed information on installed components – is transferred to the operating phase.

Sensors provide live information on operating conditions, and in addition, all technical innovations on the system, such as the installation of a spare part, are tracked in the “digital twin”. Users benefit from more accurate real-time information and they get a detailed “reference book” with all service information they need.

But how can companies use the advantages of digital twins for their customer service? Digital twins enable the implementation of predictive maintenance since they allow data to be assigned to specific plant conditions. Thus, changing measuring conditions often show in advance that a certain component will fail in the foreseeable future. This allows planned system downtimes to be better coordinated and repair cycles to be adapted to expected failure probabilities.

Requirements For Digital Twins In Service
Sufficient sensors and a systematic evaluation of the data are the essential basis to predict imminent component failures – an approach that is already feasible today. However, technical possibilities are still far from being exhausted right now.

Due to ongoing depreciations or for other economic reasons, companies are only gradually investing in plants equipped with modern IoT technology. IoT, however, will become more affordable in the near future. Sensors will therefore spread continuously while at the same time becoming easier to use, more resistant and cheaper.

"A digital twin represents a real object in the digital world..."

Enabling New Business Models, A Recipe For Digital Success
Industry 4.0 cannot work without a well-planned and technologically underpinned digital service concept, because service is an essential part of digitization. Many companies today already try to stand out with the quality of their service rather than just great products since they are often too similar, even exchangeable.

Customers therefore primarily choose the partner that offers more and faster service. The goal of every company should therefore be to better understand its customers, create better touchpoints and improve service.

This is where new concepts such as “machine-asa-service” become more and more important: companies only purchase the performance of a machine instead of the machine itself – including the service to ensure constant performance. Service Lifecycle Management plays a central role in this concept. In the future, entire ecosystems will emerge from new service providers using concepts like this.

Digital Twins Will Revolutionize Customer Service
Digital twins with their immense data material in both service and business intelligence offer the potential to create entirely new areas of business. Sensors allow to map and control machine statuses and product quality in real time – as well as predicting problems at an early stage. This way, service can intervene before expensive machine failures occur.

Furthermore, companies can dynamically adapt maintenance intervals to actual requirements on the basis of live information. In the future, all of a company’s systems as well as all of its spare parts, tools, containers and products, will be represented by their “digital mirror images”, a complete factory in the computer. The large amount of data that can be collected using digital twins in combination with artificial intelligence evaluation will provide stunning new insights into the interaction of operating processes.

This will lead to fully automated smart factories, which, thanks to artificial intelligence and digital twins, can control themselves practically without human intervention

Manuel Grenacher, is GM at SAP Field Service Management.

Manuel Grenacher, CEO, Coresystems, reflects back on some of the big predictions he made earlier this year and reflects on the progress made in interweaving the Internet of Things, Artificial Intelligence and Augmented Reality into the fabric of field service delivery across the last 12 months...

 

The days are getting shorter and colder, which means the holidays are approaching and 2019 is just around the corner (believe it or not!). So now is the perfect time to take a look back at 2018 and take stock of the advancements the field service industry made this year.

Back in March, we highlighted three trends we predicted would have major impacts on the field service sector in 2018. We noted that while 2017 introduced innovative new technology-based trends with the likes of artificial intelligence (AI) and augmented reality (AR), 2018 would bring real-world applications that put those buzzwords into practice.

So let’s review the progress of each of those three trends this year – after all, predictions don’t mean much if you don’t evaluate how accurate they were, right…?

 

The IoT Drives Proactive Device Maintenance, Service and Repair

Since the Internet of Things (IoT) became an integral part of almost every business’ technology mix midway through this decade, field service innovators have been finding ways to use the increased connectivity of the IoT to gain a competitive advantage. We predicted that in 2018, further innovation would allow field service technicians to utilize the IoT and automation in today’s devices – with the goal of providing service in real-time to meet (and exceed) customer expectations.

As is often the case in the field service industry, supply chain and manufacturing organizations were at the front of the line when it came to utilizing IoT-enabled and supported field service. Toward the end of this interview between SupplyChainBrain and various supply chain executives, the benefits of the predictive maintenance that the IoT enables become clear. Regarding sensor-equipped motors in warehouses, automation solutions provider Knapp noted:

“A motor might transmit information about vibration or heat, for example. It could indicate it needs potential maintenance services, and that's important because that would be predictive maintenance as opposed to breakdown maintenance, which is much more costly and can severely impact service levels.”

We’re seeing this focus on IoT-enabled predictive maintenance across the board with our manufacturing customers, so we can confirm that it definitely became a major focus in 2018 – and will continue to do so in 2019.

 

Artificial Intelligence Simplifies and Automates Service Appointments

Although artificial intelligence (AI) is in danger of becoming a somewhat empty buzzword in many industries, it’s here to stay – indeed, Gartner forecasts that 85 percent of customer interactions will be managed by AI by the year 2020.

The field service industry is applying AI in very meaningful ways as we speak, and it’s the concept of predictive maintenance that is driving the adoption of AI. For example, a recent study of original equipment manufacturers (OEMs) in the supply chain sector found that most OEMs are gathering data from sensor-equipped products in the field—a key requirement for predictive maintenance. In addition, more than half of OEMs plan to make AI and machine learning a major investment, while 90 percent intend to invest in predictive analytics within the next 12 months.

Beyond predictive maintenance (but related to it), AI can streamline the field service technician dispatching process – which crucially means customers can get their equipment serviced faster. Influential software authority Capterra highlighted how design consultancy Philosophie, using AI, developed a field service program that handed 90-95 percent of the technician dispatching duties to an AI system – which enabled the field service team to dedicate its human talent to the more difficult field service jobs.

AI most definitely made its stamp on the field service industry in 2018, and the innovation is expected to continue next year and beyond.

 

Augmented Reality Provides Unprecedented Visibility into Worksites

Back in March, we noted that the increased connectivity that the IoT brings will continue to propel the application of augmented reality (AR) in the field service sector. In 2018, we saw AR applied by companies aiming to improve their first-time fix rate on service calls, as well as other vital field service functions.

ZDNet detailed several highly-recognizable brands using AR for service calls, including BP's U.S. Lower 48 onshore oil and natural gas business, which has been equipping field service technicians with AR platforms to assist with repairs, and Caterpillar, which recently tested an AR solution for the technicians who service a line of its onsite portable generators. Caterpillar provides field personnel with an internally-developed iPad app that interfaces with IoT sensors on the generator to provide real-time diagnostics and repair protocols.

While AR is in its infancy relative to the IoT and AI, we’ve seen our own customers' leverage AR to make better use of their field service resources – including servicing their customers’ equipment remotely through AR glasses. We’re very likely to see the usage of AR expand in the field service industry in 2019.

It certainly appears that the trends we highlighted earlier this year continued to gain significant traction in the field service industry in 2018, and we fully expect IoT, AI and AR technologies to continue to drive a wide range of innovative projects and initiatives in 2019. And once the calendar turns to 2019, look out for our predictions on the developments to look forward to next year!

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