HOLT CAT, the largest US dealer of Caterpillar machines and engines, has adopted Augmentir’s Connected Worker platform to speed-up the process of training new technicians and to standardise job times.

The company operates across construction, mining, industrial, petroleum and agricultural sectors, selling, renting and servicing equipment. The firm will look to spread the Augmentir platform across other areas of its re-manufacturing and rebuild operations, including their business systems and workflows.

Artificial Intelligence's effect on Field Service Productivity

The firm’s new workforce approach will see them dovetail Augmentir’s AI-centric software with Salesforce’s Field Service Lightning, a platform they currently employ, and a move that Brandon Acosta, VP of Enterprise Operations at HOLT CAT, says should enhance productivity and output. “We truly believe that the seamless connectivity of Augmentir with that platform [Field Service Lightning] will empower our technical staff within one end-to-end digital platform; not just what to do, but how to do it,” he said.

Russ Fadel, Augmentir’s CEO and Co-Founder is confident HOLT CAT will see progress in staff training and overall productivity. Commenting, Fadel said: “We are excited to be selected as HOLT’s connected worker platform for its service, repair and maintenance applications. Our AI-based Connected Worker Platform helps industrial companies to intelligently close skill gaps so that the entire workplace can perform at its peak.

The Augmentir platform uses Artificial Intelligence in a suite of tools that assist firms in the digital transformation of their operations, for example moving from paper-based procedures to digital, augmented work instructions. It can speed-up the process of training new technicians by capturing legacy worker knowledge creating digital work instructions and workflows.

It recently upgraded its remote-connectivity capability, Augmentir Remote Assist, which now includes real-time chat, live video and audio collaboration and a recording capability to enhance knowledge sharing, a requirement gaining traction as social distancing rules from Covid-19 permeate service operations.

---

Further Reading:

• Read more about Artificial Intelligence in Field Service @ https://www.fieldservicenews.com/artificialintelligence
• Read more Augmentir @ www.fieldservicenews.com/augmentir
• Read more about HOLT CAT here. 
• Read more about the impact of Covid-19 on Field Service @ https://www.fieldservicenews.com/en-gb/covid-19

So far in this series of excerpts from a white paper recently published by Aquant, we've assessed the significant challenge field service companies face in finding balance in their workforce and the role Artificial Intelligence (AI) can play in helping companies do so. Now in the final excerpt in this series we look at how equally the implementation of AI requires a human touch to succeed. 

 

In Field Service we Must VALIDATE AI WITH HUMAN KNOWLEDGE

Much has been made of the idea that machines can replace humans for essential job functions. The truth is that AI is nothing without the real-life expertise of humans to guide and validate its findings.

Automating insights from historical data is not enough on its own. In order to ensure that findings about the solutions to service challenges are accurate, an organisation must bring in its experts to assess and improve the solutions offered. Before AI, organisations needed to take experts out of the field for months to help with training or knowledge sharing. With the right AI solution, experts can optimise insights in a matter of hours.

When solutions to challenges are automatically generated by a system, it enables members of the service team to spend more time doing what they do best—which is applying their expertise in the field.

 

Speed up the Training of your Field Service Engineers and Increase Their Expertise

With easy-to-access information that understands what you mean regardless of specific phrasing, and a dynamic pool of information to draw from, smart systems give all employees equal access to previously hidden information.

Skills that previously took years to learn (usually by waiting to personally encounter and solve each unique problem) can now be passed down to newer employees in a matter of days. In addition to solving the practical problem of on-boarding new hires, it also helps to engage millennials in a way they are more comfortable with. And when knowledge is easier to acquire, employees can work on acquiring soft skills like customer service and relationship building, which can’t be taught by even the most powerful machines.

 

Case Study: How 3D Systems were able to scale their field service wrokforce and decrease repeat field engineer visits with actionable insights

3D Systems empowers modern manufacturing with best-of-breed plastic and metal 3D printers.

They help manufacturing clients dramatically reduce build time and enable healthcare organisations to custom-fit solutions and improve patient outcomes. With a robust global client base, they needed to onboard new service techs quicker to get them out in the field and solving complex service problems.

As the workforce grew, one of the hardest issues was extracting the organizational knowledge out of the heads of the most experienced engineers and into the hands of everyone in the field. They turned to Aquant’s AI-powered service intelligence platform to mine and analyze all their information, including data stored in field service solutions, CRM, and parts systems. In addition, the tool was able to uncover info that lay dormant in free text notes.

"3D Systems has seen a 62% reduction in parts usage and a 39% decrease in repeat visits, driving significant cost savings..."

The Natural Language Processing (NLP) engine embedded in the technology is even able to map different phrases and words all back to the same problem, which structured the data more efficiently and made it easier to search. During the install process, which took less than a week, the tool scoured and categorized data, and then their best engineers sat down to validate the data and improve findings.

3D Systems is now able to leverage Aquant’s Intelligent Triage product to assess and troubleshoot customer tickets quickly, helping service pros resolve issues on the first visit. They’ve also decreased parts costs and usage by correctly identifying the source of the problem and sending the right tech, with the right skills into the field with the right parts.

All employees have more equal access to knowledge, making it easy for junior techs to get up to speed quickly. As a result of implementing Aquant across the organization, 3D Systems has seen a 62% reduction in parts usage and a 39% decrease in repeat visits, driving significant cost savings.

 

Would You Like to Know More? There is a Field Service News white paper on this topic available exclusively to fieldservicenews.com subscribers. Click the button below to access it now! 

---

This premium content is sponsored by: 

   

 

---

Data usage note: By accessing this content you consent to the contact details submitted when you registered as a subscriber to fieldservicenews.com to be shared with the listed sponsor of this premium content, Aquant, who may contact you for legitimate business reasons to discuss the content of this content.

---

NEW! If you would prefer to access our full premium content library without having to submit data to our sponsors you can opt for a paid subscription for as little as £15/month find out more @ https://www.fieldservicenews.com/subscription-tiers

In our previous article in this series of excerpts from a recent white paper published by Aquant we explored the significant challenges field service companies are facing as they try to navigate the huge demographic changes that are underway at the moment as the ageing 'boomer workforce is replaced by their millennial cohorts. In today's article we explore why the current knowledge transfer tools are letting field service companies down. 

The labour shortage forces organisations to choose between immediate needs, such as having their most senior staff in the field addressing urgent customer issues, and long-term goals of documenting their knowledge and training new employees.

 

Knowledge Transfer in FIeld Service Requires Tools Fit-For-Purpose:

As most managers know, when resources are tight, the biggest fires get put out first and smouldering issues continue to be put off until they can’t be ignored.

It’s not that companies haven’t tried to harness insider info and scale training. There are mobile apps and field service tools designed to capture notes from the field.

However, change management can be a bigger barrier than the C-suite anticipates, leaving managers tasked with motivating the workforce to use the technology that some in the field consider clunky or time-consuming. And even when these tools are successfully put into use, it’s difficult to make these notes and comments that are captured on customer tickets actionable.

They’re often riddled with typos and contain information about multiple tasks in one long, free text form. How can any organisation parse that information and use it effectively?

This challenge is at the root of why so many internal knowledge bases are missing the deep insights of employees in the field. Plus, most of these solutions are static databases, as opposed to connected learning tools that know what information is necessary, can prompt employees to ask the right questions, and then figure out logical solutions based on partial inputs.

Digitally savvy employees are used to using tools like Siri that understand their location and habits and can offer intelligent solutions without the user having to do all the legwork.

 

Uncover Existing Data to Fill in the Gaps in Your Field Service Knowledge Base

People make the best mentors and trainers, and those with deep on the-job knowledge often excel at diagnosing obscure problems that newer employees may have never experienced, but these deeply knowledgeable employees only have so much time and ability to impart their wisdom.

As organisations seek to meet high customer service expectations, human knowledge must be combined with an artificial intelligence discipline called machine learning in order to democratize that knowledge. 

 

Use Machine Learning Technology to Distribute Existing Knowledge

Customer-facing organisations have far more information and institutional knowledge squirrelled away than most managers and executives realise.

There are free text notes, product images that sit within and outside of CRM, ERP, WFM, and other databases. Technology partners that leverage Machine Learning (the process of computers improving responses with experience) can capture this unstructured information and add it to the knowledge base, alongside real-time data, producing a rich and interactive pool of information that all employees can draw from.

The right application can make actionable recommendations and predictions based on this data, helping teams solve customer and service challenges efficiently.

 

Apply Natural Language Processing on Top of the Information Mountain

With the amount of data in play, it’s not enough to simply convert current and historical information into structured data which can easily be indexed and searched.

The problem is that different customers or regions might have different terms for the same issue. Plus, case notes about this issue might contain typos and misspellings, making it difficult to manually identify and categorise records. A solution that offers Natural Language Processing, in combination with Machine Learning, digs deep into the historical information and acts as a translator.

It will understand the root issue regardless of how it’s described by analysing the past examples, whether it’s faulty equipment or new installs. It will map these different ways of describing issues back to the same solution—even if the descriptions contain mistakes. In addition to helping call centre agents and techs in the field, it’s an essential learning tool to help employees level-up by quickly accessing critical data to get the job done.

 

In the final feature within this series of excerpts we will look at two more ways field service companies can utilsie the data within their existing records to help solve the field service skills gap as well as an industry case study from a leading high tech organisation in the 3D printing space. 

 

Would You Like to Know More? There is a Field Service News white paper on this topic available exclusively to fieldservicenews.com subscribers. Click the button below to access it now! 

---

This premium content is sponsored by: 

   

 

---

Data usage note: By accessing this content you consent to the contact details submitted when you registered as a subscriber to fieldservicenews.com to be shared with the listed sponsor of this premium content, Aquant, who may contact you for legitimate business reasons to discuss the content of this content.

---

NEW! If you would prefer to access our full premium content library without having to submit data to our sponsors you can opt for a paid subscription for as little as £15/month find out more @ https://www.fieldservicenews.com/subscription-tiers

Field service teams are in flux. The existing drain to the workforce brought on by a deluge of retiring Baby Boomers combined with an unsteady economy is creating unprecedented service and performance challenges. In this series of excerpts from a new White Paper published by Aquant, we explore how Artificial Intelligence can pave the way to overcoming these challenges for field service organisations...

Even in an uncertain environment, there are cost-effective ways to ensure continuity of service. Adopting AI-driven field service technology will allow your service organization to pivot quickly and help erase the skills gap.

By capturing untapped tribal knowledge and making that insight accessible across your workforce, the technology will empower less tenured employees with the wisdom of your experts. The results are quicker, more comprehensive training for new hires, increased job satisfaction, and ultimately, a better customer experience.

 

Where to Find the Next-Generation of Field Service Professionals

Service teams are in a labor crunch.

According to 2018 global research by Manpower Group, skilled trade positions, particularly technicians and engineering roles, are the hardest to fill. This didn’t happen overnight. The Service Council detailed the coming storm in the labor market in 2015 research, noting that “70% of service organisations indicate they will become burdened by a retiring workforce over the next five to ten years.”

We are in the midst of that talent shortage and organisations are scrambling to fill openings, with more than 70,000 service technician jobs listed across the country. Baby Boomers, who make up a significant majority of the workforce in the service industry, are now retiring. In the next ten years about 10,000 Boomers a day (across all industries) hit retirement age.

That’s a lot of farewell parties.

Analysts and economists have been sounding the alarm bells for years about the coming crisis, but many companies have struggled to pivot quickly. While Millennials now make up the largest portion of the workforce overall, the service industry has struggled to attract and retain the digital generation, due in part to housing shifts from the suburbs to the city, and the large number of millennials who hold bachelor’s degrees compared to a generation ago.

While the majority of customer call centre and field service jobs don’t require a college degree, the jobs do offer many qualities that young talent are seeking, such as room for advancement and a sense of purpose. In order to recruit and retain young employees, an emphasis on professional development is crucial.

 

Don't Let You're Field Service Expertise Leave with Your Retiring Technicians:

 

In addition to contributing to the labor crunch, retiring boomers are exacerbating the knowledge gap in service. Unlike other industries where institutional knowledge is indexed, best practices documented, and lunch and learns held monthly with pizza, technicians often work solo or have limited interactions with other team members.

In lieu of imparting tips and tricks, technicians often keep knowledge of a myriad of parts, fickle machines, and client quirks tucked away in their head or scribbled down on paper work orders that fill desk drawers and glove compartments.

There’s also an employment tenure gap between generations, which is causing more turnover overall. 2016 research found the overall average employee tenure across all industries and age groups to be 4.2 years.

Millennials average roughly 3 years and Gen X average tenure is 6.5 years. Boomers have an average tenure of 10 years, but most are at or close to retirement age.

Even if you could hire more Millennials, the knowledge drain is forecasted to continue as the pace of churn quickens. 

Indeed, the challenges around finding balance within the field workforce is becoming increasingly difficult as we navigate this demographic shift.

However, it is not impossible and emerging tools such as Artificial Intelligence can really come to the fore in overcoming these challenges, which we shall begin to explore in the next feature within this series. 

 

Would You Like to Know More? There is a Field Service News white paper on this topic available exclusively to fieldservicenews.com subscribers. Click the button below to access it now! 

---

This premium content is sponsored by: 

   

 

---

Data usage note: By accessing this content you consent to the contact details submitted when you registered as a subscriber to fieldservicenews.com to be shared with the listed sponsor of this premium content who may contact you for legitimate business reasons to discuss the content of this content.

---

NEW! If you would prefer to access our full premium content library without having to submit data to our sponsors you can opt for a paid subscription for as little as £15/month find out more @ https://www.fieldservicenews.com/subscription-tiers

The eternal hunt for field service excellence has recently been bolstered by the rapid rise of Artificial Intelligence as a major tool in the arsenal of the field service organisation writes Aly Pinder...

The emergence of the Internet of Things (IoT) has led to the next big challenge for service organizations and manufacturers. How can wemake sense of the data we now have access to? From executives to the front-line field service technician, the ability to turn data into actionable insights will become the measuring stick for sustained success.

 

Leverage

To take this leap from data points to insights, organizations are ramping up quickly to leverage artificial intelligence (AI) to ensure volumes data (flow, sensor, vibration, temperature, or other data) can be mined quickly, accurately, and autonomously. When asked in a recent IDC survey, manufacturers listed Big Data and AI as a 4.06-level of importance (on a 1-5 scale, 1-not at all important,5-very important) regarding technologies integral to their service innovation journey.

The increase in importance should come as little shock to most as technology become ubiquitous in our daily lives, however what is interesting is the impact AI is having on service broadly and field service specifically.

As organizations evolve service business models to be less reactive and more proactive or predictive, the ability to leverage real-time data across a complex network of inputs is becoming critical for this transition.

Being reactive or break / fix merely requires a customer or an operator to call the service desk and report an issue. But in order to truly be predictive or prescriptive with service prior to a failure, organizations must leverage performance data to allocate resources, trigger a service event, and schedule the service to be delivered.

Organizations are looking to AI to explore field service excellence in some of the following ways:

• Better service planning and execution – How often have we talked about the “rights” of field service; right part, right tech, right skills, right time, right resolution. As much as we’ve commented on this and attempted to reach this utopia, many organizations still miss. AI connects the dots between each of the inputs across field service execution to provide the intelligence necessary to make the correct decisions, each time.
  
  
• Customer experience optimization – Even at a global scale, manufacturers and service organizations are finding they need to personalize service experiences for their customers. AI is enabling organizations to segment customers and deliver the level of support desired. Not every customer wants the closest technician, some just want to see the tech they’ve built a relationship with over the years. AI can and should be used to identify customer needs along with how best to resolve an issue. Should you resolve an issue remotely, or send a field service technician, or notify the customer directly with a customer support agent to walk them through the fix?
  
  
• Self-healing and suggestive preventative maintenance – As service organizations embrace servitization or product as a service models, they will need to deliver uptime and outcomes. Analyzing asset performance data and anomalies at scale provides the bridge to these new autonomous field service business models. But AI also provides the reporting capability to support the dashboards and details which will validate these premium services. Without capturing data points and rationalizing the service being delivered, customers may not understand why they are paying for service when they don’t actually see a failure occur.
  
  

More and more products and equipment are being connected every day which in turn is leading to volumes of data that needs to be managed. Passively managing data will be a waste of these IoT investments. Furthermore, AI can accelerate service business model transformation which has been talked about for years if not decades.

I look forward to seeing how field service organizations take advantage of AI to take this leap and meet customer expectations for an enhanced service experience.

AI-powered smart video solution can intelligently capture and classify video according to the severity of driving events.

Verizon Connect Integrated Video uses artificial intelligence (AI) to intelligently capture and automatically classify video according to how severe an event is, showing only what is relevant and important to business owners and operations managers, as well as machine learning to help businesses improve driver behaviour and protect the bottom line. Verizon Connect Integrated Video also provides real data insights to help commercial drivers stay safe on the road and protect them against false claims.

Additional features include a speed Overlay, which enables operations managers to easily view the speed of the vehicle directly within the video clip to determine if speed is the factor that caused the event; and Video on Demand, which allows operations managers to request 40-second increments of available footage.

"Delivering our commitment to customers means creating innovative solutions, powered by the latest technology that helps our customers move their business forward,” said Derek Bryan, vice president EMEA, Verizon Connect. “We’re delivering next-level solutions, powered by advanced AI and machine learning to help our customers be safe, productive and efficient all over the world.

 

Augmentir have announced free use of its Remote Assistance Tool for front line workers to help companies address travel and social distancing issues around pandemic.

Augmentir have announced the free use of its Remote Assist support and collaboration tool for the remainder of 2020 to help industrial companies address the growing workforce and supply chain disruption created by the Covid-19 pandemic.

Employee Health a Priority

As Covid-19 continues to spread across North America, the CDC has suggested that businesses implement remote work policies and travel restrictions to help slow the spread of the virus. The situation has become more troublesome over the past few weeks, and many companies are looking for ways to help limit business disruptions while keeping the health of employees a top priority, influencing Augmentir's decision.

Russ Fadel, Co-Founder and CEO of Augmentir, said, "COVID-19 is impacting the lives of people all around the world, and is forcing a change to the way we work. At Augmentir, the health and safety of our employees, as well as the employees of our customers and partners is the Company's top priority. Therefore, in a response to COVID-19, Augmentir will be offering its Remote Assist tool at no cost through the end of 2020 in an effort to help the many businesses affected by the sudden increase in work-from-home policies and travel restrictions resulting from the global outbreak of the virus. We hope to curb the predicted impact this virus will have on industrial companies and will remain steadfast in our commitment to serving the industry we call home." 

During this challenging time, video-conferencing, chat, and remote support and collaboration will be more important than ever in maintaining the wellbeing of employees while also enabling people to continue to work and businesses to operate. Augmentir's Remote Assist tool helps to minimize the negative impact that COVID-19 is having on businesses by providing a remote collaboration and support solution that can be adopted in less than 60 minutes, so that workers, technicians, and customers can get the support they need to do their jobs without compromising health, safety, or productivity.

Companies that sign up will have free use of the tool for the remainder of 2020, will be able to: stream live video and audio to remote experts to improve issue resolution and remote knowledge sharing; guide field technicians and customers with live annotations for enhanced collaboration and support remote users on their existing devices as well as AR-enabled smart glasses.

Commenting on the company's decision, Russ Fadel, Co-Founder and CEO of Augmentir, said, "COVID-19 is impacting the lives of people all around the world, and is forcing a change to the way we work. At Augmentir, the health and safety of our employees, as well as the employees of our customers and partners is the Company's top priority. Therefore, in a response to COVID-19, Augmentir will be offering its Remote Assist tool at no cost through the end of 2020 in an effort to help the many businesses affected by the sudden increase in work-from-home policies and travel restrictions resulting from the global outbreak of the virus. We hope to curb the predicted impact this virus will have on industrial companies and will remain steadfast in our commitment to serving the industry we call home."

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 final part of this series on AI our panellists, FieldAware's Mark Tatarsky and ServiceMax's Amit Jain, discuss if the technology compliments a wider strategy or can it operate in a silo.

Ericsson Network Services portfolio boosted to improve customer experience through greater focus on AI, automation and digital transformation.

 

Ericsson has launched two new artificial intelligence (AI)-powered offerings in its Network Services portfolio, enabling communications service providers to secure always-on networks and deliver optimal user experiences.

The two new portfolio additions — Network Intelligence and Omni Network Channel – are part of  Ericsson’s Network Services offering. They employ AI, automation and predictive analytics to address the complex reality faced by communications service providers: exponential data growth and the continuous introduction of new technologies such as 5G, digital transformation, and scattered information sources and insights.

Network Intelligence is an AI-driven preemptive support service that allows issues to be identified and resolved before they impact network performance. The service prevents critical outages and delivers the network stability needed for service continuity and optimal end-to-end performance.  Ericsson research shows that Network Intelligence reduces critical incidents by up to 35 percent by carrying out selective data collection, and automatically resolves issues within an average of five minutes from data collection.

Omni Network Channel is a unified digital workspace for interaction between the communications service provider and Ericsson, providing easy navigation, self-help and smooth collaboration. The workspace enhances network performance and consumer satisfaction through faster resolution of both the communications service provider and Ericsson operations’ issues. It also facilitates the adoption of new technologies such as 5G and supports communications service providers with the competence development of their personnel.

Roger O’ Hargan, Head of Service Area Networks, Ericsson, says: “Our core value is ‘Technology enhanced by people’ where people, framework and technology are our main assets. These new offerings are all about putting the service provider in the center by enabling self-help as well as smooth collaboration, co-creation, and easy access to data – all of which will help secure an always-on network experience.”

Justin van der Lande, Principal Analyst at Analysys Mason, says: “There is a demand among service providers for a more transparent interaction with their vendors when dealing with network issues. Ericsson’s intelligent workplace technology, boosted by the expertise of their people, addresses this well. This approach leverages the scale of Ericsson’s operations, its well-established frameworks and its wealth of industry knowledge to bring significant benefits to the service provider. Ericsson’s AI-powered Network Services are now readily accessible with shared data insights that put the customer experience front and center.”

Network Intelligence is built for product-near use as a natural extension of the Network Services portfolio. It is complementary to the Ericsson Operations Engine, Ericsson’s offering for managed operations, design and optimization launched in January 2019.