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In the Big Discussion we bring together a panel of industry experts and focus on one key topic within the field service sector.
In the first of a new four part series, we turn our attention to Augmented Reality where our panel includes Stephen Jeffs-Watts, Senior Advisor Service Management, IFS, Francesco Benvenuto Product Marketing Manager, SPACE1 by OverIT and John Bishop, President, Librestream...

Why should field service companies deploy an augmented reality solution if they already have a peer-to-peer video tool (such as Facetime or Skype) already available and free to use?

JOHN BISHOP, PRESIDENT, LIBRESTREAM
Choosing a video chat product as a remote expert augmented reality (AR) solution can seem like an easy path to fulfilling an immediate need.

As AR platforms and capabilities like remote expert guidance have matured, enterprises have developed clear requirements for security, IT controls, usability and performance. Requirements that these kinds of tools are not able to meet. For example, how will the solution perform in low bandwidth environments? Can IT control how much bandwidth will be consumed?
How can I quickly engage supply chain experts and customers? How can I be sure my content is safe and meets privacy requirements?

We deployed the first AR remote expert solution in 2006 – long before remote expert guidance was part of AR. Over the past 12+ years, our enterprise customers like Rolls Royce, NOV, Colgate-Palmolive, SGS, and hundreds more have guided the development of our solution to solve these difficult challenges.

FRANCESCO BENVENUTO, PRODUCT MARKETING MANAGER, SPACE1 BY OVERIT
Augmented Reality does not imply the use of a mere Remote Support solution but of an advanced tool aiming at supporting field technicians in their daily tasks through advanced collaboration and content sharing features.

AR solutions, such as OverIT’s product SPACE1, offer both real-time remote assistance and access to pre-built AR work instructions simultaneously.

In this way, support means collaboration and remote problem solving, but with a groundbreaking concept in mind. When assistance was guided by standard videos, both field technician and remote operator had to rely solely on voice instructions. SPACE1 is one step ahead, allowing experts to make marks that stick where drawn and annotations to be displayed on the users’ point of view while supporting them. Moreover, it enables the sharing of digital twins to be set where the remote expertise is needed, thus broadening traditional field working modalities and creating a brand-new cooperative virtual environment. See it in action here.

By using AR products users can capture images, record live support sessions to retain and share the expert assistance (both verbal and supported by visual annotations) in the future or even generate reports and offer actionable insights into improvement opportunities while providing additional employee training.v
AR solutions, embedded in the service delivery process can greatly enhance and enrich the customer experience.

One of the most compelling use-cases is in service call avoidance; where AR, when implemented in a seamless manner, empowers contact agents with enhanced diagnostics capabilities and tooling – being able to see and remotely guide the customer in triage with directive instructions, document sharing and image mark-up. These capabilities can reduce down-time, avoid the need to send a field technician to site and thus directly improve customer satisfaction. Additionally, compliance obligations can also be met through integrated session recording; which isn’t possible in the peer-to-peer space.

That same capability can then be deployed in the field; giving the technicians and the remote experts guiding them much wider capability with a resulting increase in effectiveness and efficiency. In this way, the technology increases first-time-fix rates, improving cost-to-serve and providing another dimension in improving the customer experience.


The second part of the big discussion will be published next week, when the panel answer questions on the role that AR can play in the challenges that come with an ageing workforce.

Is your organisation digitally determined or are you amongst the 54% of companies who are currently digitally distraught? Sarah Nicastro, IFS, reflects on some of the common errors to avoid when approaching digitalisation...


In a recent blog titled You Need a New Digital Transformation Playbook, published by IDC, author Meredith Whalen reveals that based on a recent study of digital leaders, 46 percent are what IDC refers to as “digitally determined” while 54% are what IDC calls “digitally distraught.”

It doesn’t surprise me that such a large percentage of organisations fall into the “distraught” category – true digital transformation is a massive undertaking that can prove daunting and frustrating at times. In an effort to alleviate some of the headaches that can come along with such a major initiative, I’m going to share four common missteps I see organisations make related to digital transformation:

#1: Overlooking the Cultural Implications of Digital Transformation
If you think of digital transformation as strictly a technology initiative, you are starting off on the wrong foot. Digital transformation requires just as much cultural change as it does technology use, yet this piece of the puzzle is commonly overlooked for a variety of reasons – leaders assume employees will just “get it,” carving out time for cultural change management seems to slow down progress, or companies just aren’t sure how to tackle such a cultural shift.

I assure you, making an effort to get the cultural part of digital transformation right will pay dividends. I’ve heard countless tales of efforts gone wrong because the employee wasn’t bought in on the concept or properly trained on the tool introduced.

Key areas to focus on are to communicate clearly and regularly with all employees on the need and objectives for your transformation – implement a feedback loop with your employees and listen to what they have to say. Be selective about the technology you adopt as part of your effort – if the tool doesn’t meet the needs of your workforce or
is difficult to use, adoption will suffer. Investing in tools that do what they say they will and deliver an experience your employees actually value will build their trust in your digital transformation efforts. Finally, continually monitor adoption and “take the temperature” of your employees to course correct your efforts as needed.

"Making an effort to get the cultural part of digital transformation right will pay dividends..."

 

#2: Failing to Set a Solid Digital Transformation Foundation
It’s all too easy to become enamored by some of the ultra-cool facets of digital transformation and gloss over some of the basics. But for true digital transformation to be successful, you have to walk before you run.

You have to ensure you’ve laid a solid foundation of basics from which to build your digital repertoire. While not as sexy as AR and AI, effective and efficient communication, bulletproof scheduling and routing, and solid work order management are examples of more basic technology that simply has to be mastered before being built upon.

As you evaluate your foundation, think about the past — what do you have in place already that is working well; the present — what you want to accomplish in the near term; and the future — what you want your digital portfolio to look like five years from now. This will help you visualise the evolution of how you build on what you have to get where you want to be, or will help you to identify changes you need to make to your current systems before building upon them.

#3: Defining YOUR Desired Digital Transformation State
To achieve digital transformation success, you MUST realise that your desired end state will be unique. I’ve seen organisations get off track because they see what ABC Company is doing and make every effort to replicate their success, rather than tailoring the approach to their own business. It’s fine to look around you for inspiration but staying in your own lane is critical to your success.

Start by defining your business goals, by visualising what YOUR desired digital transformation state looks like (and of course agreeing upon this vision organisation-wide). Each businesses’ end goal is going to be individualised, as well the approach for getting there – no two companies can follow the exact same path.

Once you have your goals set and vision articulated, focus then on only the technologies that will get you there – don’t allow yourself to be sidetracked by the new, shiny thing that will ultimately bring no value to your business but looks really cool. Stay focused and measure your progress to that desired state.

#4: Racing to Reach The “End Goal” of Digital Transformation
I’m here to break it to you: you’ll never reach the end of your digital transformation efforts. The “end goal” is a myth; it doesn’t exist. The reality of digital transformation in the technology age is that it will keep going, and going, and going.
This means you have to work to perfect the art of ongoing cultural adaptation, business goal setting, and technology adoption – because you’ll be adding on to and tweaking your digital transformation efforts from now until the end of time.

Don’t let this overwhelm you – the foundation you are setting will equip your entire organisation to make future adjustments and additions far more seamlessly.

While there is no true state of completion, the race is on to make progress and remain competitive.

Sarah Nicastro is Director of Service Management Business Development at IFS.

PTC's Servigistics platform will integrate with IFS' Field Service Management, Applications and Maintenix solutions.


IFS the global enterprise company have announced a partnership with computer software and services company PTC that they say will reduce asset downtime and improve service part availability.

The partnership will see IFS' three field service platforms - IFS Applications, IFS Field Service Management and IFS Maintenix - incorporate PTC's service-parts optimisation solution Servigistics.

Commenting on the agreement, Aly Pinder, IFS' Program Director of Service Innovation and Connected Products said: " The collaboration between PTC and IFS connects two critical aspects of service – field execution and service parts management. To remain competitive and deliver enhanced service experiences, it is crucial to have the right service part available for a service technician to fix an issue promptly and during the first visit."

Leslie Paulson, Servigistics Business Unit's General Manager was equally positive. “We are excited to partner with IFS to integrate our solutions and pursue new frontiers of innovation in connected service delivery,” she said. “Having the right part in the right place at the right time has never been more important. We’re pleased to be working with IFS to enable companies to differentiate their service and maintenance operations.”

Pricing details have not been yet been revealed, but according to MRO-Network.com, IFS have said this will depend on specific customers' needs. 

Blockchain and its potential has been mooted in field service circles for years. Is it time we stop thinking big and instead build smaller use-cases before we lose sight of what’s actually important, the end-user? Mark Glover, Field Service News’ Deputy Editor finds out more.

In 2008, a person (or a group of people) known as Satoshi Nakamoto conceptualised the first blockchain. A year later, this digitised digital ledger was a critical accessory to the group’s (or his) headline act, the now ubiquitous cryptocurrency Bitcoin.

The impact of this decentralised digital currency on financial markets and a curious, confused society has been fascinating to follow. That the persona of the inventor or the inventors remains unknown adds to the plot.

Yet, without blockchain, the currency wouldn’t function. This smart ledger, driven by a peer-to-peer network has the potential to stamp itself on industry and in particular field service. But can the sector adopt the technology in a way that will ultimately benefit the end-user?

Firstly though, and apologies to all those who have a handle on the technology, what is blockchain? Scouring the internet for a simple definition is tricky, eventually, the excellent forward-thinking mission.com offered this: “Blockchain is the technology that underpins digital currency (Bitcoin, Litecoin, Ethereum and the like). The tech allows digital information to be distributed, but not copied. That means that each individual piece of data can only have one owner.”

 

"The tech allows digital information to be distributed, but not copied. That means that each individual piece of data can only have one owner..."

 

Straightforward enough. But let’s expand it to industry. How can it fit into the aerospace sector and specifically a plane engine? Parties involved include the airline, the engine manufacturer and the service company all of whom are squirting data into that asset’s blockchain.

The jet engine is a high-end valuable piece of equipment, the blockchain systems enable a single, irrefutable history of that asset. The linking of parties (blocks) removes the requirement for inter-party consultation before extracting required information meaning critical decisions can be made quicker and more effectively. It’s also secure and visible to everyone and accurate and trust, therefore, is enhanced around the chain. The benefits are tangible. So why aren’t all companies rushing to implement it?

“Like all emerging technologies there are only going to be one or two applications that are going to come up for this kind of thing in the very early days,” says Stephen Jeffs-Watts, Senior Advisor – Service Management at IFS. Stephen is an expert in blockchain, a keen enthusiast of its benefits but warns that fields service shouldn’t get too carried away just yet, particularly as sectors are only starting to dip their toes in the murky blockchain water.

 

"We have to try and bear in mind that it [blockchain] is also directly proportionate to the type of kit that’s been installed...“

 

A lot of the use cases that are coming up at the moment,” he tells me, “are in very high-value assets and very highly regulated supply chains; in aerospace, defence, nuclear and very-high-end medical applications,” he pauses. “There aren’t too many Phillips Medicals out there.”

In field service, blockchain technology can potentially trace parts, verify assets and look-up maintenance and operations history, but according to Stephen, it needs to bed-in with modern hardware before its benefits can be felt. “We have to try and bear in mind that it [blockchain] is also directly proportionate to the type of kit that’s been installed,” he warns, “Are you really going to use blockchain to authenticate the asset history or the maintenance and servicing history for a ten-year-old piece of equipment?” Another pause, “You’re not.”

Let’s go back to the jet engine blockchain analogy; the engine itself is a high-end piece of equipment.

The airlines and engine manufacturer, themselves are high-end companies:  BA, KLM, Lufthansa, Rolls Royce, GE, Northrup Grumann, for example. All are big companies keen to monetise blockchain, the only real way to do this is through data-ownership but in a high-asset blockchain, this isn’t always straightforward.

Who owns the data from a jet-engine? Is it the airlines?

The thrust from their plane goes through that engine and what about linking that to the pilot who’s flying that aircraft and jet engine through the air? That’s the airline’s data too. They also have a hand in the plane’s load: the number of passengers and baggage, fuel etc. That’s also data from the airline.

The engine itself? Rolls Royce might run it on a power-by-the-hour contract, so it’s their engine, so do they own the blockchain data? Like that other revolution IoT, blockchain becomes an issue of data ownership. What can be done to grease the chains to make the process run smoother?

“You’re going to have to get industries and supply chains to actually come together and solve the underlying data ownership issue,” Steve offers. “There is going to have to be some kind of consensus; an informal consensus through co-operation; the introduction of some kind of industry standard or ultimately an enforced consensus through legislative means,

Be it an Industry standard or a regulatory framework, large-scale blockchain implementation ultimately needs sectors to work together, to come together in agreement and as Steve explains, it also becomes an issue of trust. “Let’s say there are ten people involved in the supply chain: the operator, the Original Equipment Manufacturer (OEM), there may be a service operator; they’re all contributing data to that chain.

“But does the end operator actually have enough trust in the OEM to question if they are going to use their data and benchmark it against its competitors”, he ponders.

Issues around data-ownership, trust and unfit equipment unable to handle what is essentially a large-scale, shared google document are indicators that large-scale field-service blockchain implementation isn’t as close as we might think. Perhaps we are setting our sights too high? Maybe the use-cases should be carried out on a much smaller scale?

After all, cryptocurrency, the original thread of blockchain was designed for electronic financial transactions, not necessarily jet engines. Stephen agrees, referencing a well-known tracking device, he suggests we should keep things simple. “We could use blockchain like a glorified RFID tag that authenticates, verifies and gives you a reference point,” he says. “I can look at the blockchain and I can see who made it, when it was made, how it was transported.

“Where they may be just a couple of parameters about its last usage, you can look at that by a component-by-component type level, specifically in those cases where that kind of information is critical, or the authenticity is critical.

 

"There’s got to be a realistic level of ambition and some specific use-cases that prove the technology and prove the value of the technology before there comes any mainstream adoption..“

 

There’s got to be a realistic level of ambition and some specific use-cases that prove the technology and prove the value of the technology before there comes any mainstream adoption,” Stephen urges.

My conversation with Steve has been fascinating and his contribution to this article I’m sincerely grateful for. The insight he offered - most of which I’m unable to fit into this wordcount – was invaluable, yet despite all its potential of blockchain Stephen left me with a thought that goes beyond the blockchain hype: “So what?”

So what if an asset is pumping with blockchain data? All the customer wants is the device to start working again so they can get on with their business.

“What value does that bring to me as a customer,” argues Steve. “unless I’m in a highly regulated environment. When do you start loading up past-maintenance history? Is it good? Is it worthwhile? Probably not. So what’s the use-case that going to give killer value?

Steve continues from the end user's perspective: “Great, you’ve got blockchain. What do I get from you having blockchain? What do I get from being able to prove every last working second of this particular piece of kit? Why should I care?”

It’s an excellent point that perhaps gets lost in this fourth industrial revolution we find ourselves in. Among AI, and IoT and machine learning and blockchain should we not just focus on the customer needs and their requirements? Or will we continue to pursue the hype?

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This year's Aftermarket Business Platform was once again a hive of information as senior leaders from across the European continent and beyond came together to share their insight, learn from their peers and see first hand the technology that is shaping the sector. The conference was packed with the leading thinkers within the industry from both the practitioner and solution provider side including regular fieldservicenews.com columnist Mark Brewer who spoke with Coppperberg's Mark McCord...

 

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The schedule for Aftermarket 2019 is already being put together and it promises to be a key date in the calendar once again. This is an event that almost always sells out so head over to aftermarketeurope.com now and secure your place at this important industry event...

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In an outcome-based economy, the customer’s experience becomes the focus of the production process. But if a new product can achieve the same experience as an older model, where does that leave innovation?

According to IFS global industry director for service management Mark Brewer, innovation becomes even more essential, even if it’s driven in different ways.

“Rather than restricting innovation, the manufacturer is induced to continually reflect on how the product is behaving in the field,” Brewer explains on the sideline of Aftermarket 2018. “A combination of both consumers and industry are driving innovation. Organisations are being flexible to adapt to the expectations of millennials, generation X and so forth.”

Brewer has spent his 20-plus year career in presales, product management, business development marketing and he crisscrosses the world representing IFS at trade shows and winning business for the Sweden-based software developer.

 

"Rather than restricting innovation, the manufacturer is induced to continually reflect on how the product is behaving in the field..."

 

While the service industry is undergoing a transformation that’s putting the focus on experiences and outcomes rather than product manufacturing, Brewer says innovation will come in the form of better, more cost-effective, ways to provide those experiences.

Earlier, he explained the concept to dozens of delegates at the Berlin event using the example of Philips. The Dutch electrical giant used to sell tens of thousands of light bulbs to Amsterdam’s Schiphol Airport. Now, he explained, it no longer sells bulbs – instead, it provides a contract that will ensure the facility’s lights never go out.

“When you take ownership of the outcome, sure it turns the model on its head but in that example, they want to minimise the amount of product they shift because it’s all coming off the profit margin of their contract,” he explains.

“Likewise they are going to great lengths to optimise the number of visits they make — so they intelligently combine visits. If they’re going to do an overhaul of certain sections of the airport, they pull all the near-term jobs into the same routine and send one team in one hit. It’s a win-win because the customer doesn’t want engineers swapping things out every day.”

In his presentation, Brewer said research showed companies could earn $12 in product servicing contracts for every $1 earned in product sales. BMW, he pointed out, earned 12% margins on the sale of each car but 65% on provision of services for each of those cars.

“Service traditionally has been underinvested,” he told delegates. “That golden goose hasn’t been mined very well – but that’s changing.”

Driving that change is technology, he explains later. “Digital twinning”, in which manufacturers track the performance and condition of their products in the field via inbuilt monitors, has the potential to revolutionise the service industry.

 

"For the first time, the customer is no longer the sensor - the machine is the sensor now..."

 

“For the first time, the customer is no longer the sensor to say, for instance, that an elevator is broken; the machine is the sensor now,” Brewer says. “When a company sends a product out they never lose sight of it.

“With IoT and the leveraging of all their product information in the form of CAD, they can see how their products are performing. More interestingly, they can see the features that customers are using and not using. In that way they can see where they’ve over-engineered the product and can defeature to reduce costs by taking things away.”

The end result is innovation targeted at creating better customer experiences. More and more, that will come in the form of software upgrades.

“It doesn’t mean we have to reflect hardware changes to reflect innovation and change,” he explains. “The Tesla gets its upgrade at the click of a button and GE today employs more software engineers than hardware engineers.”

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Artificial Intelligence has increasingly become a key discussion in all industries and its impact in field service management is predicted to be hugely significant, but how should field service organisations leverage this powerful twenty-first-century technology? In the part one of this two-part feature Marne Martin, President of Service Management, IFS outlined why AI in field service is about far more than chatbots, now in the concluding part, she outlines how AI can bring a touch of genius to your field service operations...

 

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Solving Problems When One Isn't Albert Einstein

Human agents are capable of optimally dealing with a customer, and AI can free them up for the most interesting and demanding tasks. In the case of scheduling technicians in the field, humans are just not up to the numerical challenge of adjusting a schedule in an optimal fashion as humans typically focus in on an aspect of a problem to solve rather than finding the best solution overall.

A dynamic scheduling engine (DSE) driven by AI algorithms is designed to solve complex scheduling problems in real time—problems much too complex for any human dispatcher or customer service agent to handle, especially when at times individuals will act myopically based on their area rather than for the greater good of the company and its customers.

 

"Even a static service schedule can be handled in myriad different ways and decisions regarding which technician to send to which of several jobs in what order are often made based on suboptimal heuristics..."

 

Even a static service schedule can be handled in myriad different ways and decisions regarding which technician to send to which of several jobs in what order are often made based on suboptimal heuristics.

“Steve’s son is in daycare in this part of town, so I will schedule this appointment last, so he will be close by.” Sometimes jobs are scheduled based on first-in, first scheduled, regardless of the actual urgency of requests that come later.

Manual or traditional software-based scheduling may be a workable solution for service organizations with a very small number of technicians each engaged in a small number of jobs during a day. But it does not take many technicians or jobs for the number of possible solutions to outstrip human computation capabilities either individually or as a group.

Even at the low end of the spectrum, a human dispatcher cannot quickly identify all the possible solutions and pick the best one. With two technicians and four service calls there are already 120 possible solutions— different combinations of technician, job and order. Two technicians, and five service calls yields 720 possible solutions. Four technicians and 10 service calls present a dispatcher with 1,037,836,800 possible solutions.

But the time you get to five technicians that must complete six calls each—a total of 30 calls, you have 12,301,367,000,000,000,000,000, 000,000,000,000,000 possible solutions.

Finding the optimal solution becomes even more complex as additional and rapidly-changing factors are added into the mix:

• Emergent jobs come in that must take precedence over those already scheduled
• SLAs and other contractual requirements demand that some jobs be completed within a given timeframe
• Technician skill sets that influence which tech is sent to which job
• Tools and materials currently in stock on each service vehicle
• The current location of a technician in proximity to each job and to drop locations for inventory that may be required for a job
• The duration of each service call, both in terms of estimated time required to complete the call and whether a current job is running over the estimated time, resulting in knock-on effect on subsequent jobs

Former world chess champion Garry Kasparov, in his book Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins, makes clear that even his mind is not capable of computing possible solutions and outcomes as rapidly or effectively as an AI algorithm.

 

"Automating the schedule through AI not only enables a much higher level of service but frees up dispatchers to handle those “beautiful or paradoxical moves” that may delight a customer or solve a tough problem...“

 

The human mind isn’t a computer; it cannot progress in an orderly fashion down a list of candidate moves and rank them by a score down to the hundredth of a pawn the way a chess machine does,” Kasparov writes. “Even the most disciplined human mind wanders in the heat of competition. This is both a weakness and a strength of human cognition. Sometimes these undisciplined wanderings only weaken your analysis. Other times they lead to inspiration, to beautiful or paradoxical moves that were not on your initial list of candidates.”

Automating the schedule through AI not only enables a much higher level of service but frees up dispatchers to handle those “beautiful or paradoxical moves” that may delight a customer or solve a tough problem.

In the end, collaborating with intelligent machines will get us further faster than going it alone. According to Kasparov, the best chess is now played as grandmasters use computers to analyze positions, opponents’ games and their own games—elevating the level of play. In an interview with the Financial Times, Kasparov, who famously had matches against an early chess supercomputer, described how the best chess is now played by combining “human intuition and understanding of the game of chess with a computer’s brute force of calculation and memory.”

“I introduced what is called advanced chess; human plus machine against another human plus machine,” Kasparov said. “A human plus machine will always beat a super machine. The computer will compensate for our human weaknesses and guarantee we are not making mistakes under pressure … the most important thing is not the strengths of the human player. It is not the power of the computer. But it is the interface. It is the corporation.”

 

Legacy Approach to Inventory Logistics

Service management for many businesses relies on inventory … if completion of a service call requires inventory and you are out of stock, you cannot meet your commitment to the customer. When a service request cannot be closed on the first visit, it is often because the right part is not on the truck or immediately available.

So, service management software should encompass inventory management functionality, and that functionality should include automated reorder points for each part. The ability to take parts availability into consideration is a critical data set for AI to work on as parts are a critical determinant in first-time fix and job completion where parts are a factor. It also is a key aspect to successful SLA and outcomes-based commercial relationships.

Once inventory data is available and integrated, a powerful DSE may also be configured to influence inventory logistics so parts and materials are housed in warehouses, satellite offices or inventory drop locations closer to anticipated demand, with inventory matched to jobs in a forward or current day schedule. In one very large implementation of IFS Planning and Scheduling™ Optimization—in the London underground transit system—inventory and tools are dropped ahead of each service visit so technicians who ride the subway to the service site can pick them up.

This is only possible with a high degree of coordination between the service schedule, inventory logistics and an AI-driven scheduling tool.

 

Conclusion

Service organisations should recognise the tremendous potential AI holds—they can harness it to transform their operations, outflank their competitors and disrupt their markets. We are only starting to tap into the different ways AI can be used to better solve the problem of delivering optimal service in a rapidly changing environment as adoption is still lagging despite the real benefits AI brings. The good news is there are several straightforward and easily accessible ways service executives can harness AI technology right now, today.

 

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Artificial Intelligence has increasingly become a key discussion in all industries and its impact in field service management is predicted to be hugely significant, but how should field service organisations leverage this powerful twenty-first-century technology? In the first of a two-part feature, Marne Martin, President Service Management IFS, offers her expert insight... 

 

 

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Is AI a key topic for you?! There is a full white paper on this topic available to fieldservicenews.com subscribers. Click the button below to get fully up to speed!

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Artificial Intelligence (AI) will impact every industry and every business discipline—including field service management. But how quickly will practical solutions be available that enable the typical medium to large field service organization to take advantage of AI? And by practical solutions, I mean AI that delivers knowledge efficiently, processes solutions to complex data sets, and automates repetitive activities to allow human workers to focus on personalized service, solving complex problems and escalations, i.e. what people do best.

In some cases, these easily applied solutions are still on their way to market. In three specific areas, however, practical AI applications for field service are already commercially available as proven, commercial off-the-shelf software delivering real business value.

 

AI For Customer Interaction

First impressions matter. And unfortunately, the first interaction a customer has with your service organization often involves several missteps. Chief among these are long wait times on hold due to high call volumes. And then, as a customer attempts to reach out through multiple channels including email, chat and phone, the resulting data stream goes into separate siloes that are disconnected from each other, resulting in disjointed communication.

 

"Today, AI solutions can solve both these problems, but it requires more than “just” chatbots..."

 

Today, AI solutions can solve both these problems, but it requires more than “just” chatbots. Commercially available AI software that ties into chatbots is capable of learning which answers posed in a chat are appropriate for each question and automating a significant majority of chat interactions. A chatbot can be taught to answer commonly encountered questions, like inquiries about when a technician is scheduled to arrive. Of course, at some point, the AI chatbot may get stuck when personalized service is required, and a human agent takes over the discussion thread without missing a beat. This should be seamless not only to the customer but for the internal customer service, ticketing and support systems as well. The chatbot—regardless of whether driven at a given moment by AI or a human agent—should update the same customer record as other channels including social media, phone and email.

And from interactions, the AI functionality learns from answers provided by human agents and gets better and better at answering questions through learning processes. A truly advanced AI chatbot will also seamlessly hand off the chat to a human agent when the extent of its learning is overtaken. Only then can the entire customer experience be unified and consistent, even with a static number of agents handling a rapidly growing fluctuating volume of customer interactions.

AI-based chatbots, for instance, can enable a good agent to handle up to five or more chats at a time. It can capture Facebook messages and tweets and direct them to an agent or to AI for intervention. AI alone can handle, typically, between 50 and 60 percent of requests, freeing up human capacity or lowering staffing levels required to handle a given volume of activity.

 

Enables Management By Exception

In the case of AI applications for the service organization, a primary driver for ROI is that it enables humans to manage by exception. A high volume of activity can be automated, and humans intervene primarily when a situation falls outside the business rules or logic built into service management software. AI doesn’t eliminate the need for human interaction—it makes the human interaction more focused on what humans do best—handle escalations and complex decision making for unique cases.

At one IFS customer, an AI chatbot handles about 50 percent of interactions— primarily those reaching out to cancel their service after a free three-month trial period. Interactions cancelling a free subscription are handled entirely through automation. But if a longer-standing customer is cancelling their service, the interaction gets routed to an agent dedicated to saving the account.

Some interactions are by default easily handled by AI. If 30 percent of inbound contacts are requesting information on the arrival time of a field service technician, it may be possible to automate 90 percent of that 30 percent of contacts. But it is also important to consider the demographics of the customer base. Millennials are more likely to communicate via chat or social media, so if a significant percentage of customers are under 40, heavier reliance on chatbots and AI may help you increase engagement by streamlining your customers’ preferred method of interaction.

 

"Management by exception is also more successful when an AI application has access to extensive information about each customer..."

 

Management by exception is also more successful when an AI application has access to extensive information about each customer. So full integration with enterprise resource planning, field service management and other enterprise tools is essential. AI tools can be more effective if they have more rather than less information on the status of the customer’s account, including their maintenance or service history and warranty or service level agreement entitlements.

Integration between an AI chatbot, email, voice, social and enterprise applications is important for another reason. It enables one version of the customer record. Lacking this, a customer can send an email, and get no response. They send a direct message through Twitter. Then call and sit on hold. Then initiate a chat. All these interactions may not appear in a central customer record, but there have been three attempts to contact the company. Right from the first contact by email, the clock started ticking on a service level agreement.

Full integration can also enable a customer service team, once a customer request is resolved, to close off all queuing activations at the same time for the various contact methods associated with a customer case. Failing this, a service organization may spend a significant amount of time chasing customer requests that have already been resolved.

 

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