Field Service Matters is the leading professional community focused on digital experience strategies, the evolution of the digital workplace and intelligent information management. Founded in 2016, Field Service Matters is a popular native digital publication catering to a global readership of business leaders and sophisticated practitioners that are crafting the digital strategies for the modern enterprise.
With companies like Uber, Amazon, and Airbnb providing customers with on-demand service, expectations are a lot higher. Customers not only demand visibility into the service process, but they want to be a part of it.
With companies like Uber, Amazon, and Airbnb delivering on-demand service, customer expectations are higher than ever. Customers not only demand visibility into the service process, but they want to be a part of it. Why? Because engaging in a dialogue with your customers helps you better understand their needs. And it allows you to provide more efficient service and better customer experiences.
For instance, your customers can give you more details about their issue, or even send a picture before the service visit. That way techs can arrive fully prepared for a first-time fix and customers can avoid rescheduling the appointment. You can also avoid customer no-shows by asking customers to verify their appointments before the day of service. Your customers will appreciate that you’re involving them in the process because it shows you care about solving their problems.
ClickSoftware recently hosted a Meet the Boss event in London, focusing on reinventing field service management for optimized customer experiences. Paul Whitelam, ClickSoftware’s Group Vice President of Product Marketing, discussed the importance of opening up communication with the customer during the service process. Watch the video below to learn more.
There is a clear dissonance between what service organizations, such as telecommunications, are delivering and what customers expect. The telco industry is a highly competitive market, with organizations likely to invest, and compete, with each other for customer experience and acquisition. Understandably, telco customers hold high expectations for the service that they are paying for, yet the telco industry simply isn’t offering the expected experience to its customer base.
In light of the gap between customer expectation and reality, ClickSoftware conducted its 2017 Field Service Report. The study—across seven countries—indicated that the telco industry, alongside other service organizations, needs a better way to engage with customers and, thus, deliver an improved customer experience. The study also recognized that suppliers are heavily focused on the delivery of new technologies, whereas optimized, real-time communication and a transparency for service delivery are high on the customer agenda.
This evidence, supporting the lack of customer satisfaction within the telecommunication industry, can be verified by a simple internet search for ‘bad customer service telco’ and observing the sheer volume of articles written on the subject, from publications across the US, Europe and Australia. Forrester analyst, Dan Bieler, discusses in two of his blog articles, ‘Poor customer experiences remain the Achilles heel of telcos’ digital transformation efforts’ and ‘Make Omnichannel a Cornerstone of your Digital Transformation – The Telco Angle’, how rampant customer dissatisfaction seems to plague the telco industry globally.
What does this mean for the future of telcos?
The results of the survey, combined with numerous articles on the lack of great customer service in the industry, should provide an eye opener for telcos; they need to be more aware of customer expectations and meeting these in terms of the services and overall experience they provide. The vast amount of complaints and dissatisfaction emphasise how it is not just an odd problem here and there. Customers want improved communication and efficient services, not cancelled appointments or unacceptable wait times. In today’s fast-paced world, these expectations are nothing out of the ordinary. Telco service providers should embrace heightened expectation, as a result of ‘instant’ technology services, as a basic step towards achieving customer satisfaction.
The repercussions of bad customer experience include a negative economic impact, a damaged reputation, and a loss of customer retention rates. In the age of social media, customers have more public avenues than ever before to complain about poor service to their peers. If an individual receives bad service, they can easily and immediately share their bad experience with family members, friends, and even online strangers. The risk of bad reviews on social media continues to grow, with online users now frequently reading or sharing viral posts that highlight service mistakes. The fool-proof way to avoid social media backlash is undoubtedly to improve the service that is given to customers.
Telecommunications firms must understand their options when it comes to addressing the correlation between outstanding customer experience and increased revenue, customer retention rates and satisfaction. Only then will they take the steps necessary to improve their services to fulfil their customers’ expectations.
In the past year, chatbots have exploded in popularity. E-commerce giants, customer service websites, and even the White House have all seemingly dipped their toe in the chatbot waters. Some have been successful, others quite the opposite.
With organizations like Facebook and Microsoft failing catastrophically with chatbot technology, where does that leave the rest of us? And more importantly, should field service organizations even bother with chatbots in the first place?
While this emerging technology shows great promise for our industry, specifically the virtual assistant capabilities of software, there are many lessons to be learned from early implementation failures.
But first, a definition:
A chatbot (short for chat robot) is a computer program that can autonomously communicate with people via text or audio stimulus. Whether voice-activated (e.g. Siri, Alexa), or text-based (e.g. web chatbot), these softwares leverage artificial intelligence to communicate by mimicking human behavior to the best of their programmed ability.
And now, onto the fail show.
Fail #1: Microsoft
On March 23rd of 2016, Microsoft released an artificially intelligent robot via Twitter named Tay (short for Thinking About You). The bot was designed to act like a modern 19 year-old American girl and autonomously interact with, and learn from other Twitter users. Within minutes, other Twitter users had taught the software inflammatory language, and offensive cultural cues.
16 hours later, Microsoft was forced to shut the software down completely due to the negative image they had generated, and public sentiment. Following Tay’s shutdown, Microsoft released another bot in the United States named Zo, but this bot was likewise ultimately a failure.
To be fair, Microsoft has successfully launched chatbot softwares in China and Japan, both of which have not gone off the rails.
In examining this situation, there are two major mistakes Microsoft made that service organizations should avoid when developing chatbots:
1. Avoid Clinging to Cultural Cues
Microsoft’s attempt at mimicking millennial teen behavior lacked taste, and backfired in a big way. Instead of looking cool to their target audience, they demonstrated to the entire world that they knew little about their millennial audience’s needs, behaviors, and desires.
Field service organizations that want to leverage chatbot technology to communicate with customers should avoid trying to mimic culturally charged language, or mirror customer personas too closely. The key is being there to answer customer questions in their moment of need. Don’t waste precious time trying to fool your customers into thinking your chatbot is their friend. Your customers don’t need robot friends.
2. Serve a Purpose, or Serve Your Customers
In theory, Tay was a cool new teen robot software that internet users could chat with.
In reality, it was a cultural information mining experiment meant to gather intelligence about a target audience. Tay served no purpose beyond giving Microsoft actionable intelligence that they could use in future product development.
Harmful to society? Not really. But consumers rarely want to interact with a brand’s software unless they are getting something of value in return. Microsoft made themselves a target by putting out a software that ultimately served no purpose.
Field service professionals must hone in on specific purposes for chatbots. Pick one or two big customer pain points, and use chat technology to make it a little better. Are your customers frustrated due to long wait times when calling in for service? Offer them the opportunity to use chat technology to schedule their next appointment.
Are there frequently asked questions, or common issues your customers face? Program your chatbot to answer these questions fast, instead of forcing your customer to move around your website in order to find an answer.
Fail #2: Facebook & The White House
In April of 2016, Facebook launched artificial intelligence chatbots for the messenger app. Early partners included 1-800-FLOWERS, CNN, and a weather app called Poncho.
Long story short, it didn’t go so well. And as you can see below, Poncho wasn’t so great about delivering accurate weather predictions.
On August 10th of 2016, the White House announced they would receive correspondence from citizens via a Facebook messenger bot. In the first week, most journalists had agreed that the chatbot was labor-intensive to use, and even posed some basic security concerns.
There were several problems, and lessons we can learn from this chatbot. Although the main takeaway centers around usability.
Don’t Make the Customer Experience More Cumbersome
From an experience perspective, The White House chatbot was no different than other forms of digitally contacting POTUS. Instead of responding to users, the chatbot simply led them through a step-by-step process of filling out a message that may or may not have been sent through the system for approval, or disapproval. The actual process of using this chatbot was labor-intensive, and was no more convenient or valuable than sending an email. Arguably, it was even more cumbersome than previous methods.
Using technology for technology’s sake rarely goes well. Service organizations can learn from the White House that if they are going to jump into new technology, they must embrace it wholeheartedly. It’s simply not enough to offer a new service channel that is as cumbersome as previous touchpoints, or fails to meet the promise of easier use.
With companies like Forrester predicting artificial intelligence (AI) investments will jump 300% in a single year, it’s clear that AI is not just a passing fad. Adventures in Artificial Intelligence is a series for savvy field service professionals looking to stay on top of AI trends, and their impact on service.
In our previous post, we explored machine learning and its potential applications for field service organizations.
This week, we’ll be getting more specific about which human tasks artificial intelligence will replace in both the short, and long-term. But first, some news. The AI landscape is shifting rapidly, and key players continue to shake things up on a daily basis.
Our first story features Google, who revealed at their recent annual developer I/O conference that their neural network and artificial intelligence software is designing new AI systems more effectively than Google engineers. That’s right, the AI they built is now autonomously building better AI.
This project, dubbed AutoML, involves deep learning techniques and neural networks that effectively mimic processes found in the human brain. Google is using this software to, “design networks for image and speech recognition tasks. In the former, the system matched Google’s experts. In the latter, it exceeded them, designing better architectures than the humans were able to create.”
How will this impact service? As AI gets better at recognizing images, speech patterns, and facial expressions, it will likewise be closer to evaluating whether equipment requires service based on simple images.
Here’s the full scoop on the future of AI at Google, if you prefer to watch:
Halfway across the world, a Swedish startup named Gavagai AB announced this month they’ll be using artificial intelligence language analysis software to monitor and decipher the language of bottlenose dolphins.
Does that mean future middle-school children will choose between French, German, Spanish, or Dolphin? Unlikely.
While a dolphin language analysis appears rogue at first blush, Gavagai AB has assured many that this challenge will directly improve their software’s ability to interpret words, and noises alike. They report this investigation will improve their analysis of human language and emotional triggers, as well as help them interpret sea creatures’ behavior, or even someday in a galaxy far far away – interpret space alien languages.
In a solar system a bit closer to field service, OpenAI recently announced they have created an artificially intelligent robot capable of “one-shot imitation learning.” The robot effectively watches a single simulation of a task, learns it, and performs it without flaw.
In the screenshot above, a human simulates the stacking of blocks using virtual reality goggles (right) and a real-world robot precisely mimics it in one-shot, without flaw (left). We can not overstate what a huge leap forward in robotic ability this represents.
This type of technology will be a real game-changer for service in the coming years. Just imagine a few of the potential scenarios in which we could use simulations to teach robots to:
Perform service tasks in dangerous scenarios
Troubleshoot equipment in inclement weather
Fix space equipment while in-flight
Fix pipes, networks, and dams submerged underwater
Manually troubleshoot equipment that previously required having humans present
Without further ado, here are some human tasks in field service that AI (and robots) will replace in the near, and long-term.
Human Tasks AI will Replace
While autonomous vehicles, or even field service drone taxis, are not quite ready for market adoption in most countries, there’s no denying that at some point in the future our cars will drive themselves. Artificial intelligence software that enables autonomous driving is rapidly reaching its market potential. In fact, Nvidia and Audi recently reported they’ll have a driverless car ready for market by 2020.
Many service engineers spend half their time behind the wheel each week. If freed up from driving, they would have more time to perform strategic tasks while in transit, including:
Getting familiar with their next customer challenge
Communicating with previous, or future customers via text, or voice
Fielding photos or videos of broken equipment from their next service site
Connecting with dispatch to discuss scheduling, conflicts or customer queries
These are obviously just a few of the potential values of freeing technicians up from the wheel.
2. Dispatch & Scheduling
While many scheduling softwares already leverage some automated features, the majority of future dispatch and scheduling tasks will be completely supplanted by software.
These AI dispatchers will be capable of interpreting, and mimicking human scheduling behavior, and will be far superior to humans at dealing with crisis scenarios like storms, major power outages, or even earthquakes.
Naturally, there will still be a need for humans to manage the dispatch software itself. Likewise, service engineers will still need to interface with their human counterparts in troubleshooting schedules, optimizing routes, and more. This isn’t doom and gloom. We expect a hybrid human-software approach will be necessary.
In all, we expect this process to happen slowly, but you should start seeing AI dispatch and scheduling automation broadly adopted within the next three to five years.
Here are a few changes you can expect:
Voice-activated technology will be introduced that allows dispatch managers to distribute tasks without any typing. Likewise, field engineers will be able to accept or decline schedule changes using this same voice-activated technology.
Machine learning algorithms will be built based on the most efficient dispatch professionals. Dispatch software will continue to be optimized based on this information.
Comprehensive programs which can autonomously manage dispatch and scheduling, and evolve while doing so, will enter the market. This may take years, but will completely change dispatch management as we know it.
3. Self-service & Customer Communication
The first question any IT service professional will likely ask when you call is, “Have you tried restarting it?”
Likewise in field service, millions of customer calls result in millions of field engineers getting in millions of vehicles driving to millions of service locations only to find out the path to resolution is so dirt simple, the customer could have gained resolution all on their own.
THAT is a big fat waste of time, talent, and money.
In the coming years, artificial intelligence software will alleviate the need for needless service visits by interfacing with customers to resolve many of their requests through self-service, on-demand equipment assessment, and more. PwC recently reported that this type of AI could eliminate as many as 80% of current service requests. Joe Atkinson of PwC remarks,
“Instead of sending every service ticket to a dispatcher, we can route it first through an algorithm and determine the best avenue to solve the problem. Is there an online FAQ that provides the customer a quick path to resolution? Would a simple customer-performed troubleshooting step, like restarting equipment or replacing a simple component, solve the issue?”
As the field service industry faces a rapidly aging workforce, who struggle to keep up with customer requests, AI will be a key component in bridging the talent gap.
Here are a few ways AI will help customers resolve simple service challenges:
Chatbot technology will be available to customers who can ask specific questions about equipment, parts, common service scenarios and more. These chatbots will instruct customers on the simple steps they can take without service, and when a scenario warrants involving their service provider, or technician.
By embedding artificial intelligence software and sensors in complex field equipment, devices that breakdown will be designed to automatically send information to dispatch, or the service team about exactly what isn’t working. Service would effectively find out something is broken before the customer does.
Years in the future, many customers will have voice-activated devices connected to IoT sensors embedded on all the mechanical equipment they own (or in enterprise settings, the office manager deals with). Customers will simply ask their voice-activated “hub” questions about malfunctions, mechanical device status, and more.
While AI will certainly replace many human tasks, we feel the most strategic roles in service can never be supplanted by machines. Whether robots can learn service tasks, software that will re-organize a dispatch schedule in seconds, or drones that can survey hard-to-reach equipment, we will need even smarter service technicians and managers who can humanize the technology for customers.
In the end, good service is about good relationships with customers. We believe artificial intelligence can help us all achieve that end.
These days we don’t give it a second thought when Netflix or Amazon recommends a video or product that would probably interest us. Or when Google seems to read our minds as we’re typing in a search phrase. These are examples of machine learning—a subset of artificial intelligence (AI)—in action in our everyday lives.
In our last post in this series, we explored virtual assistant technology powered by AI and machine learning. While AI can be tough to get your arms around, machine learning is complex territory in its own right. In this post, we’re going to break down machine learning into everyday terms and explore how it might play a bigger role in your life out in the field.
The A-B-Cs of Machine Learning
Before machine learning and the internet, computers performed tasks based on programs written in binary code contained in closed systems. Computers knew how to perform specific, repeatable tasks, based on direct input from humans.
As the internet advanced in the 1990s, the code landscape likewise evolved at a rapid pace. Fast-forward to today and the fact is we simply have too much data, and too many unique behavioral processes for any binary system to accommodate. Smartphones, social media, and real-time technologies now feed more data into computers than we could ever process through fixed systems.
Machine learning helps us deal with both changing behavior and data proliferation through algorithms that evolve without human input. To boil it down, we’re teaching computers to make assessments without human input.
Machine learning is teaching computers to learn as we humans do: by interpreting information from the world around us and bucketing it into manageable categories. Machine learning algorithms then apply this information to situations they run up against in real-time. Many machine learning algorithms continually learn as they apply information in real-time to create predictive scenarios for reacting to internet stimulus.
What are Machine Learning Libraries & Applications?
Think of your brain as having two major components or capacities: storing information (i.e., your memory) and thinking (through intelligence). As described above, we can now train computers to think based on the information they gather and store. In the world of machine learning, a computer’s memory is its library of information.
Instead of building up that library slowly by adding new “books” (i.e., information) over time, we can give the computer access to existing machine learning libraries and applications that call upon pre-existing algorithms, or sets of information.
The result is each machine learning algorithm doesn’t have to learn everything from scratch. It can use the problems solved by previous algorithms, which are accessed through machine learning libraries.
It’s just like this scene from the Matrix. Well, kind of:
Machine learning libraries help computers “think” through the situation at hand, leveraging data collected by algorithms that have solved similar problems in the past. Some common machine learning libraries and applications include:
The ability to better process, interpret, and learn from data empowers field service teams to predict instead of just react. Plus, it allows them to automate tasks that don’t need human input. Here are some examples:
Monitor and repair assets: Machine learning could process data gathered by sensors on equipment in the field to identify issues or even predict potential ones. Better yet, in some cases, machine learning could apply the necessary fix and eliminate the need for a visit by a field service technician. A similar but slightly different scenario is that machine learning could detect maintenance trends, order necessary parts, and schedule visits by field service engineers before a customer places a call.
Optimize operations: To outright eliminate or minimize repairs and visits by technicians, machine learning could monitor assets and fine-tune settings to ensure optimal operations. As a result, field service engineers would only need to get involved for major issues or emergencies.
Perform first-level diagnoses: Machine learning algorithms could process service tickets to determine the best course of action. That could include sending the customer a link to a PDF manual or triggering an email with step-by-step instructions on restarting the equipment.
Help equip technicians: By evaluating like service calls and recognizing the best course of action across the aggregate, machine learning could recommend the most fitting parts and tools for technicians to take to a job.
These are just a few examples of how machine learning could impact—and is already changing—field service. More real-world applications are sure to come, and when they do, your organization can gain a competitive edge by preparing to harness these opportunities.
To stay ahead of the latest field service trends, subscribe to the Field Service Matters blog. And be sure to check out part one and part two of Adventures in Artificial Intelligence if you haven’t already.
There’s always more to learn in the field service industry. Luckily, the second half of the year is full of events dedicated to field service management, customer experience, technology, and employee engagement. Here are a few you might want to attend:
When: June 5 & 6
Where: Sun City Resort, South Africa
Saphila is a biennial conference for SAP users to connect, create, and collaborate. Network and share knowledge about innovations, implementations, and service delivery with your peers. You’ll have access to a world of first-class contacts and customers including CEOs, CIOs, and hundreds of potential customers and future business partners. Discover new products and see demos from a variety of exhibitors. While you’re there, attend presentations meant to inspire you to reimagine your own business, visit a wide range of tracks with relevant and valuable content, and network closely with others at breakout sessions. Topics include:
When: July 6
Where: Centre d’affaires Paris Arpège Trocadéro, Paris
If you can’t make it to the CIO Executive Roundtable, or just want to learn more about improving customer experience in the digital era, try this IDC event in Paris. Join this conference to discuss and learn how to solve common customer experience challenges, including delivering quick solutions, offering personalized experiences, and reaching customers on their preferred channel. You will learn:
How to set up an omnichannel strategy
How to take a customer-centric approach and generate customer trust
How to leverage machine learning and predictive approaches
Field Service News and ClickSoftware are hosting an invite-only executive think tank. You’ll also have the chance to explore and share best practices with an exclusive group of C-level peers. Apply for a chance to discuss:
The growing importance of field operations
The challenge of increasing customer demands and expectations
Delivering outcome based solutions, and the benefits and challenges of adopting such approaches
When: September 14
Where: NIO RUM, Stockholm, Sweden
Nothing’s more devastating to a brand than poor customer service. Customers today, no matter the industry, expect simple, seamless service experiences and real-time communication. Today, customer service and value have become competitive differentiators. Join this exclusive roundtable discussion hosted by ClickSoftware and IDG to discuss the future’s customer-driven service organizations. Learn how to create a successful field service organization that focuses on satisfied customers, and become best-in-class in service delivery. You’ll also learn how to:
Create motivated teams and productive service technicians
When: November 13-15
Where: Hyatt Regency Lost Pines Resort and Spa, Texas
If you’re a senior service executive, you might be interested in Field Service Connect. This interactive forum provides opportunities to benchmark, share ideas, find solutions for your business, and build lasting relationships.
When: November 29-December 1 Where: NH Collection, Amsterdam Grand Hotel Krasnapolsky
Field Service Europe is Europe’s leading service and support conference. You’ll be exposed to service leaders from some of the largest European manufacturers to small and medium sized business. Experience several sessions, networking, and interactive learning. It also features guest speakers and keynotes from top manufacturers and service organizations.
Driving service revenue and customer satisfaction
Leveraging Industry 4.0 and disruptive technologies to enhance service
Preparing your organization for the next generation of service and support
In today’s technologically advanced world, an organization relying on outdated tools is at a disadvantage against better-equipped rivals. But making the case to the decision-makers can try the patience of even the most stoic field service managers.
As a manager, you know that field service management (FSM) software is now essential to delivering streamlined, effective services. That, in turn, keeps company costs low, customer satisfaction high, and new business coming your way – all critical to maintaining a competitive advantage. You also know that to keep that edge, you need to call upon the newest features.
But this may require that your organization make a change – rarely a welcome situation in business. Your job is to connect the dots for your higher ups, helping them see that the value of this change will make it worthwhile. Here’s a step-by-step guide for doing just that.
Step 1: Align with Strategic Goals
You need to identify, evaluate, and select the right software for your business, and support that with a strong business case. To make the optimal choice, you need to find the solution that can best help your company achieve its field service goals. But it’s critical that you align these with bigger organizational objectives.
For instance, if a company priority is to reduce costs by a certain percentage, how much of that is field service expected to contribute and what are your options for cutting costs? Will a new solution help you better track and process work requests? Will it enable you to increase your first-time fix rate? If a top company goal is to increase customer renewal rates, can a solution help you put more power in the hands of your customers or streamline the entire process, from reporting a problem to paying the invoice? Changes like these that help deliver better, faster service can dramatically impact customer satisfaction ratings.
Be sure to understand the order of priority for your company’s top goals. By doing this and aligning strategic organizational objectives with field service goals, you can use a set of key objectives and associated metrics as a guide during your solution evaluation.
Step 2: Do Your Homework
Your next step is evaluating your options. Engage your IT group early as a key participant. This will help ensure you address their requirements and avoid IT resistance later in the process. Plus, IT can become a convincing ally as you make your case to the executive team.
User adoption will be a key concern for both you and your management team, make sure you clearly understand your team’s needs and preferences for FSM tools. It’s a given that you will need support for mobility and cloud-based access to effectively support your team in the field. In addition, it’s important to choose a deployment model that is most fitting for you. Beyond that, focus on the features needed to enable your team and best serve your customers. Few businesses make use of every feature available in a software solution. What’s important is making sure you get key features needed most, with the option to customize if necessary.
Rank how well each solution will support your team and can help you reach your strategic goals. Then ask the top vendors to help you calculate the potential impact of their solution on your key metrics.
If possible, solicit the participation of a field service team member to help vet solutions once you narrow the list. Better yet, run a small trial with a subset of users before making your final decision.
As you narrow your options, be sure to assess the vendor along with the software. Find out how long the software has been available, how much of the vendor’s attention and R&D is dedicated to it, and the experiences of other customers. Understand support options and meet staff you would interact with as a customer to ensure a cultural fit. Assess how well the vendor has kept pace with the market and even introduced innovations, and ask about its vision going forward.
Step 3: Make Sure Your Numbers Pass Muster
Ultimately, your executive team cares about numbers. It’s why you needed to be clear on key goals and metrics before starting your evaluation. As part of your business case, you’ll need to present how the solution will help your company reach those KPIs. But it’s even more important to share a cost-benefit analysis. In other words, you need to demonstrate that the benefits justify the cost of the solution.
Once you have established a solid case, ask your CFO to review the numbers and, hopefully, give you at least a cautionary go-ahead. The good news is that field service is increasingly playing a critical role in the customer experience, which is directly tied to revenue. That means you shouldn’t need to work hard to get the CFO to consider and weigh in on your plan.
Step 4: Craft a Compelling Case
Now it’s time to document the key findings of your evaluation. Remember: you’re not selling software to the executive team. All they care about are the results the solution can deliver and the ultimate value of the investment. With that in mind, write in a language that matters to the leadership team. Explain your preferred choice and justify your selection. Focus on presenting the facts of your assessment, and be prepared to articulate the risk versus ROI of going with your recommendation.
Highlight the ways that you and the vendor will minimize the impact of change, and be sure to underscore how the deployment will positively contribute to the company’s strategic goals.
By approaching your project in a methodical manner, focused on convincing the decision makers of the value of this change – in their language – you will be well on your way to deploying powerful new FSM software.
Make sure you keep pace with the latest field service trends by subscribing to the Field Service Matters blog.
It has become clear that ideas and innovations once relegated to the worlds of science fiction have entered our daily lives. Every time you see that yellow first-down marker during an NFL game or the MPH displayed on your car windshield, you’re seeing augmented reality (AR) in action.
At its essence, AR offers a different way to interact with the world around us by, you guessed it, augmenting our reality. Unlike virtual reality—which recreates or replaces our world with a 3D model—AR superimposes information (think sound, imagery, and GPS data) onto a real-life view. Examples of devices and apps that put AR to use include Google Glasses, Snapchat’s face swap feature, and Pokémon Go.
“AR is most useful as a tool in industries where workers are either in the field, do not have immediate access to information, or jobs that require one or both hands and the operator’s attention” according to Tuong Huy Nguyen, principal research analyst at Gartner.
The beauty of AR is that it makes it possible for people—even inexperienced personnel—to be put in real-life situations with clear guidance. For instance, mechanics could be guided to repair an engine on the tarmac, even if they had never before worked on that particular model. It’s easy to see how those in the utilities and telecommunications industries could put AR to use. In fact, The Electric Power Research Institute (EPRI) is working with some of the world’s biggest utilities to determine ways to apply AR within the industry.
Training Field Personnel
One possibility is for training purposes. In fact, training was one of the first AR applications that researchers considered. Militaries around the world already use AR to train their troops. The technology makes it easier to understand and follow instructions, as compared to trying to follow written manuals or instructional videos, especially when it comes to tasks on 3D machines or devices.
Unlike virtual reality, AR doesn’t present trainees with a simulated environment. Instead, they are in an actual environment, where they would be expected to perform everyday tasks. And because augmentations can be changed on the fly, even personnel being trained remotely can be given in-the-moment feedback and updated guidance.
Assembling and Maintaining Capital Equipment
One area with huge potential for AR is the assembly and maintenance of complex equipment. In one test at Iowa State University, two groups of participants were asked to assemble a mock airplane wing. One group worked from instructions on a desktop computer, while the other worked from instructions on a mobile tablet converted to an overlay on the wing assembly. The group using the AR instructions committed 90% fewer errors during the assembly and built their wing 35% faster than the other group.
Caterpillar, the heavy equipment manufacturer, has an AR app for mobile devices, that guides services technicians through complex procedures. It also launched Cat® LIVESHARE, a tele-presence tool that makes it possible for a technician and expert in different locations to collaborate in a live, real-time setting using augmented reality. The users can collaborate using voice, 3D animation, annotation, screen sharing and white-boarding on any device. The idea is to make it feel as though an expert is by your side, helping you step by step, as you repair, troubleshoot a problem, or conduct maintenance on equipment.
Caterpillar is also exploring the use of AR animations to guide service technicians as they perform maintenance on Caterpillar’s XQ35 on-site portable generators, which are rented out to construction sites and live events.
AR could also come in handy for the telecommunications industry. Imagine a telecommunications company being able to see underground—much like Superman using x-ray vision—to locate its infrastructure. By using AR overlays on mobile devices, complemented by geographic information system (GIS) data, technicians could literally visualize underground assets, such as buried cables and cut wires, in their immediate vicinity.
Seeing Into AR’s Future
Many analysts feel AR is ready to explode within the business world. Digi-Capital projects that worldwide revenues from AR deployments will reach $90 billion by 2020. Global Market Insights Inc. pegs the market valuation at more than $165 billion by 2024. Index AR Solutions anticipates a $105 billion market for the U.S. Enterprise within 15 years, and believes early adopters will gain a competitive advantage in their industries. One reason for the optimism may be that companies realize the value of their investments with the very first use of an AR app
Hurdles on the Road to Full-Fledged Adoption
Though AR is proving its potential and seems to have a promising future, taking advantage of the technology isn’t always as simple as opening an app or putting on a pair of goggles. The processing that happens behind the scenes can require investments or integrations with a host of other systems and tools. Plus, to truly access and work with devices and machinery in the field using AR may hinge upon installing sensors in that equipment. Neither of these are small undertakings – or ones that can be accomplished overnight.
As is usually the case, it can be expensive and challenging to adopt emerging technology. In addition to the financial outlay, organizations will need to train their service personnel—often older workers who are less technically savvy—to work in new ways. They’ll need to take new devices into the field and follow guidance rather than calling on their intuition and experiences to date for problem solving. It might be difficult to get those in the field to work more collaboratively when they’re used to working in a lone fashion. Then there’s the issue of convincing them to put on a pair of goggles or wave their hands at a screen like Tom Cruise in the Minority Report.
We have yet to see if tomorrow will truly end up as portrayed in all those fantastical science fiction stories. But it’s clear that AR has a place in the here and now, and is more than likely going to change the future of field service.
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Market trends echo these sentiments. In 2016, smartwatch sales hit a plateau with just under 16% of U.S. adults regularly using wearable devices. In addition, leading players like Pebble completely shuttered their businesses. It begs the question:
Are wearables dead?
Those of a certain generation might think back to the secret agent comedy Get Smart, and the myriad of ridiculous places that concealed agent Maxwell Smart’s telephone. Among the 50 or so were his necktie, comb, shoe, belt, wallet, a handkerchief, a garden hose, and even a cheese sandwich. Some of the modern world’s “smart” devices probably seem just as far-fetched.
In field service, wearables could potentially monitor and improve technician health and communication while driving. They could help pinpoint the location of technicians on their way to or from a service appointment. And wearable virtual reality (VR) goggles can even lead technicians through a troubleshooting routine or guide them to fix a broken system.
But is that enough? Will wearables survive another year? Will they be viable in the world of field service?
Are Wearables Truly Dying a Slow Death?
At first glance, it may seem the consumer market is dying. One of its earliest smartwatch innovators—Pebble—shut its doors last December after being acquired by Fitbit. And Fitbit posted lower than expected earnings in 2016, prompting a layoff.
But it’s not all doom and gloom. According to IDC, nearly 98 million wearable devices shipped in 2016, and over half were fitness trackers. Plus, IDC projects over 124 million wearables to sell in 2017, with 57 million of them in the form of fitness trackers.
Some analysts say consumers see the Fitbit and other health trackers as redundant because smartphones provide many of the same basic functions (tracking steps and distance covered). Ramon Llamas, research manager of wearables and mobile phones at IDC, says these are all signs the market is maturing. He’s convinced consumers are interested in wearables and want to see more options.
So, what does that mean for field service?
Wearables as a Lifeline for Field Service
It may be a mistake to tie the fate of wearables in the business world to what we are seeing in the consumer market. Wearables actually saw strong uptake last year in other markets, including the medical and sports industries. This is a natural fit, since these sectors can largely apply wearables as initially designed for the consumer market (to track health and fitness). This may help explain why research firm Tractica predicts more than 66 million wearable devices will be shipped yearly for use in enterprise and industrial environments by 2021.
Wearables that enable hands-free communication and better task completion could make a mark on field service. Here are three categories with significant promise:
Field personnel often have their hands full…literally. Whether they are driving a vehicle, holding tools, or climbing a ladder, they can’t be distracted. That’s one reason wearables such as smart watches are so appealing.
Imagine the possibilities. A field technician on a pole or on the side of a building can call a remote expert for help diagnosing the situation—without holding onto a cell phone. Or they could use a voice command to access a knowledge base of information. The tech could even log the service details by voice in the moment, making sure all records are updated immediately and accurately.
The benefits of wearable watches are clear—techs stay focused on the task at hand while taking care of their calls more efficiently. The result? Higher first-time completion rates, faster and better service resolutions, and higher customer satisfaction.
At the same time, ready access to in-the-moment information can help company leaders better identify trending issues and prioritize responses. For example, if multiple technicians report back on the same issue with a newly launched piece of equipment, management can take immediate measures to proactively address the problem.
With smart clothing that resembles everyday wear, smartwear is a realistic possibility in field service.
Consider a smart jacket created by Google in partnership with Levi’s. Conductive fibers allow the wearer to connect to and control their smartphone by using their cuff like a touchscreen. Interacting with their smartphones while on call can expose field techs to potential hazards by distracting them from the task at hand. These dangers may reduce if instead they could swipe their jacket cuff to use their phone.
There’s also smart clothing that can read temperature and other environmental factors. A smart vest or jacket with this capability could help technicians gauge the environmental factors that might be contributing to a system problem or failure. In addition to quickly and accurately pinpointing the cause, such clothing would eliminate the need to carry additional equipment.
Smart headwear might be the most natural choice of wearable for those in field service. After all, many technicians already wear helmets or other head coverings as part of their uniforms.
Smart hats in a range of styles are already in use in industries like trucking and mining. Some can monitor for signs of fatigue and send alerts to those in risky situations or operating sensitive machinery.
Similarly, a headset that incorporates virtual reality along with a camera and communications capabilities can provide technicians with access to data and remote expertise. Imagine a technician is dispatched in the middle of winter to isolate a problem with a buried telecommunications line. Using the headset—which overlays information about the line’s location and relevant physical landmarks—the tech could literally look beyond the snow to identify the right section of cable and even locate the nearest entryway to access the cable.
Once underground, whatever the tech is seeing would be displayed back at headquarters so the remote expert could provide in-the-moment insights and suggestions. Moreover, the headset could overlay diagrams directly onto the cable, providing the on-site tech with clear guidance on how to handle the issue.
Though many of these wearables are still in their infancy, it’s easy to see their potential. It’s just a matter of time until they either get laughed off as the equivalent of Get Smart gimmicks or prove their merits and viability in the real world.
“Quality is remembered long after the price is forgotten.”
-Sir Henry Royce, Founder of Rolls-Royce
According to a Microsoft study, 97% of consumers said customer service is important to their choice, or loyalty to a brand. Depending on the study you read, gaining new customers costs between 5 and 15 times more than what it costs to retain existing customers.
Because at many organizations, loyalty is like chasing a unicorn. Loyalty is magical, mythical, and seemingly out of reach. Teams trying to understand customer churn don’t know why customers go away, what motivates them to stay, or how to go about keeping customers satisfied long-term. After all, it’s hard to get data from customers that don’t want to do business with you anymore.
Loyalty is even more confusing for organizations providing top-notch service. After all, why would customers walk away if the service experience is spot on?
The answer is simple. The service experience is just one small part of the customer journey. Far too many organizations are focused on optimizing a single customer touchpoint, or fixing one-off problems. Year after year they chase new silver bullets, hoping each will finally solve their customer churn.
One year it’s, “we need an app!” The next, “get that self-service portal up pronto!” Soon you’ll be hearing, “service techs need augmented reality goggles!”
It’s time to stop thinking silver bullet, and start thinking long-term customer journeys. The loyalty unicorn is out there. The road to catching it is simply longer than we realized.
Whether improving the customer experience at an education phase, or retention phase, the key to catching the customer loyalty unicorn is connecting the dots between channels and experiences.
We recently reported that maximizing satisfaction through the use of customer journeys has the potential to lift revenue by up to 15% percent while lowering the cost of serving customers by as much as 20%.
According to recent Aberdeen research on the relationship between quality service and customer retention, companies that achieve service excellence enjoy 3.9 times greater year-over-year increase in customer retention rates, when compared to companies that fail to meet buyer needs.
But how can service teams get there?
1. Move from Touchpoints to Journeys
When a customer requires service, they’ll likely be talking to multiple parties, and interacting with many of your technologies or products along their journey. They might email, check your website, call a help desk, deal with your scheduling software, and eventually see a technician face-to-face.
Even if you optimize every one of these touchpoints to be incredible experiences in their own right, the overall journey can still be poor.
Let’s look at Uber as an example of a gold standard customer journey.
When ordering an Uber, users simply enter their credit card information (once), and their destination. That’s all that’s required of the customer.
They then are presented with convenient options, and useful information including:
The type of vehicle they prefer to ride in
A preview and picture of the driver
The option of canceling if this driver’s rating is not to their satisfaction
The amount of time they’ll wait for their driver
The length of the journey
The estimated cost of the journey
Here’s what happens when the driver arrives:
The rider enters the car
The driver takes them to their destination
Dirt simple, right?
Now, let’s compare that to a fairly common service journey.
The customer contacts a call center, or sends an email about a broken part or problem
The customer fills out multiple forms, or has to answer questions about the product, their problem, and history of service
The customer might get passed to another professional in scheduling
The customer schedules a service window, typically 4-8 hours long
The customer waits days, even weeks for their appointment with a field engineer
The customer must take paid time off or work from home while waiting for the engineer to arrive
The customer has no indication of when the technician will arrive (what if they are using the bathroom when a tech comes knocking?)
The field engineer shows up to assess the problem, sometimes leaving without fixing the problem due to not having the right part, or deciding the equipment needs replacing
The customer schedules another appointment
Weeks later, the equipment is serviced
It’s painful even reading through the whole list.
To get closer to an Uberized experience, organizations should focus on streamlining and connecting customer touchpoints. With modern technology, information gathering and scheduling processes could be completely automated. By breaking down silos and connecting systems, service resolution could happen significantly faster.
Even implementing simple functionality into your website, like allowing customers to upload photos of equipment requiring service, could allow techs to assess or fix problems at much higher rates.
2. Get Everyone Laser-focused on the Customer
Every service organization has customer-centric goals. In fact, I’m betting if you looked around your office you’d find a picture with fancy lettering framed up real nice that says something like, “The customer is always right.”
While these sayings are inspiring, they don't offer specific direction for how professionals that aren’t customer-facing can incorporate customer-centricity in their daily work lives.
In fact, many processes adopted at service organizations actually end up further insulating and distancing professionals from the very customers their organizations serve.
For example, let’s say an IT manager is selecting a new billing software for his field service organization. Will she select the software that’s easiest for her team to implement? The most cost effective? The safest? Or, the software that makes it easy for customers to pay online? Without formally including the customer considerations in this process, the customer will likely be last on the list.
Likewise, a dispatch manager might schedule service at the earliest possible window for a customer (say, 7 AM sharp) thinking it’s more convenient. Now, what if the customer isn’t a morning person? Do they want to answer the door at first light? Probably not.
Again, without a formal mechanism for including specific customer needs in the dispatch process, the customer needs will take a backseat to enterprise assumptions.
The key then is getting everyone focused on the customer. At every turn, we must be asking:
How will this impact the customer?
Will this improve the customer experience?
If the customer had to choose, what would they select?
So, when was the last time you checked in with your customers? Do you have any means of gaining regular feedback? Do you know how the changing landscape is impacting your customers?
All too often service providers rely on industry reports to decide how to approach customers. Or executives simply ask their peers what the latest and greatest means for satisfying customers might be. While gut-checking against industry trends and within your network can be helpful, nothing beats out straight dirt from your customers.
Getting customer feedback can happen in a variety of ways. Sending out formal surveys might work, but frankly, who has time to fill out surveys? Embedding feedback boxes right on your website might work, but you need the technology to support it.
In today’s digital landscape, reaching out directly to customers can be the most impactful means for gaining their feedback.
Consider setting up a reminder system after each customer interaction. Whether it's a call, email, or custom web form, ensure your customers have the opportunity to weigh in on every service experience.