During a recent Field Service News Digital Symposium presentation on the use of Aquant's Artificial Intelligence tool within their service triage process, Mark Hessinger, Vice President of Global Customer Service, 3D Systems Corporation, touched on perhaps probably the most pervasive issues that our industry faces.

That issue is how do we stop the tribal knowledge contained in our ageing field service workforce walking out the door. It is a challenge we are seeing emerge across all regions and all industries.

It is a well-documented issue. Many field service companies are currently staring down the barrel of an ageing workforce crisis while struggling to engage with a future generation of workers. Some industries may have a slight advantage, companies at the cutting edge of technology such as 3D Systems for example, who will likely attract bright young minds eager to embrace a technology set to be a fundamental part of the future. Yet, even these companies generally still face higher rates of attrition than acquisition when it comes to talent.

This is perhaps why this presentation by Hessinger resonated so strongly with its audience. As Hessinger went through the multiple benefits of implementing Aquant's AI-powered triage tool, this was one aspect that really struck a chord.

3D Systems had, via Aquant's AI, found the keys to unlock much of the core knowledge locked away in the vast pools of data that all service organisations will hold. They found a way to keep the decades of tribal knowledge within their walls.

"Like other companies, we do have [staff] turnover," Hessinger explains.

"We were able to use all that information we had, to continue to support the product so that that was a nice real-life outcome of using the the Aquant tool..."

"And on certain product lines, we don't have a lot of printers installed, so we don't have a lot of people trained. For example, on one Multijet printer, our subject matter expert chose to retire a couple of years earlier than we expected. So everybody started to get a little nervous as we only had one other person who did not have the same depth of experience on that product."

"Yet, that person told me, 'you'll be fine, it's all captured in the Aquant tool. I validated that it works,'" Hessinger commented as he outlined a perfect example of a challenge many service leaders may recognise. As Hessinger explained, it was a situation that soon became even more challenging.

"Shortly after that, our second person that knew that technology also left," he continued, "so there I am without our two tech support people for this product line. However, we were still able to continue to run and support customers and actually, we haven't had any escalations on that product in the last nine months since those guys left.

"That is because we were able to use all that information we had, to continue to support the product which is a nice real-life outcome of using the the Aquant tool," he adds.

Essentially, what Hessinger and the team at 3D Systems implemented was an additional AI 'trainer'. They found a technological solution to a human problem. Ultimately, the AI allowed 3D Systems to make that transition from losing two central members of staff on a specific product line. They managed to stop that tribal knowledge leaving the organisation.

This also appeared to be something that could be almost universally applied to any field service scenario - indeed for any organisation that held sizeable layers of data that is currently a massively underutilised information resource. What came across in Hessinger's presentation was that the was already buried within their systems - Aquant surfaced it, neatly and effectively.

As Hessinger explained "Typically we require our field service or tech support personnel to document in the case what happened and that's written down. When you go back and look at it at those notes, [it is usually] because there was a similar case at some point and you start searching for cases to find the information, those are the times you go digging for it.

"Yet, now you're not digging for it. It's accessible and there, everything you've captured," Hessinger explains.

Further Reading:

• Read more about Digital Transformation @ www.fieldservicenews.com/blog/tag/digital-transformation
• Read more about Artificial Intelligence @ www.fieldservicenews.com/hs-search-results?term=Artificial+intelligence
• Read more exclusive FSN news and features from the Aquant team @ www.fieldservicenews.com/hs-search-results?term=Aquant
• Connect with Mark Hessinger on LinkedIN @ https://www.linkedin.com/in/markhessinger/
• Find out more about Aquant's AI-powered service triage @ www.aquant.io/
• Follow Aquant on Twitter @ twitter.com/Aquant_io

 In this last article in this series of excerpts from a recent white paper published by Aquant, Edwin Pahk, VP Product Marketing and Business Development, Aquant outlined the first two fo five critical KPI's field service organisations must monitor. Now in the third article in the series we look at three more crucial KPIs... 

Would You Like to Know More? www.fieldservicenews.com subscribers can access the full white paper on the button below. If you are yet to subscribe join 30K of your field service management peers and subscribe now by clicking the button below...

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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 white paper. 

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KPI#3: MEAN TIME BETWEEN FAILURES

 

What is it?

Mean time between failures (MTBF) measures the average time between customer issues. The goal for service organizations is to maximize this metric because a high time between failures represents high service quality and maximum uptime.

How it measures workforce performance

MTBF is less about resolving the single issue that prompted a failure, and more about a service professional’s ability to holistically maintain the health of the machine. This is a skill that is typically difficult to measure. Seasoned service heroes know how to take advantage of time in front of an asset to ensure that everything is working properly. They’ll work to proactively maintain or replace parts before a failure occurs, and understand how to keep failures from happening in the future.

How it measures customer experience

The less you notice this measurement creeping up, the better. Tracking MTBF is a great way to measure customer uptime and service reliability — ultimately resulting in happier customers. While service is about providing a great experience in each customer interaction, a better outcome is preventing the failing in the first place.

Challenges to measuring mean-between-failures

• Measuring mean time between failures requires long intervals of data because it’s a lagging indicator: MTBF is a big picture measurement. It requires a sustained ability to measure the time difference between failures. Quite often, organizations may only look at a quarter’s worth of data, and that’s not enough time to accurately measure MTBF because a good indicator of health means that failure may only happen every few quarters. 
• Attribution of mean time between failure to service professionals is up for debate: What is the definition of failure? Is it when different, unrelated issues arise in the same asset? Or can it also be a problem that (unknowingly) is not fixed correctly the first time, and subsequent service calls were needed to address the actual problem? Because multiple service technicians are usually contributing to service across one asset or customer, it’s difficult to attribute a long or short MTBF to a single individual.

How to measure mean-time-between-failure:

It’s straightforward with the exception of these scenarios. When dealing with long MTBF intervals (6 months or longer) or an extremely short average asset lifecycle, using the standard approach to MTBF might not be suitable. Instead, using MTBE (mean time between events) might be a better measurement. When using MTBE as a metric it’s less about whether a particular interaction with a customer constitutes a failure and more about measuring how many times you had to interact with that customer. Fewer interactions signal fewer service issues.

 

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KPI#4: SERVICE COST PER WORK ORDER

 

What is it?

Service cost per work order (or per case) is an effective measurement of the total cost of each work order or case created. It’s also known as the average cost per truck roll.

How it measures workforce performance

The cost per work order provides a measurement of the duration and/or parts usage a technician uses, on average, to resolve an issue. Higher performing individuals innately know how to solve problems without shotgunning expensive parts.

How it Impacts Customer Experience

While customers aren’t concerned with how much it costs to resolve each problem, the bigger quality issues remain true here. A lower cost per work order generally highlights a higher quality of service -- and that’s what customers notice.

Challenges of measuring mean time to resolution

• Service cost per work order might be a misleading indicator of performance: Context is key, especially when a few experts are regularly assigned complex jobs. These are cases when top employees may have a higher average service cost per work order. If yours is an organization that saves the most difficult cases for workforce heroes, know that the more complex the cases, (typically) the more expensive the service costs. ○
• Service costs can have an inverse relationship to customer satisfaction: You likely get requests from service teams for additional help because more resources (and faster response times from those with lighter workloads) typically result in better service performance. So don’t look at this metric without regard to the customer experience component. ○
• Service cost per work order doesn’t differentiate poor experiences and repeat visits: After scouring data from hundreds of organizations, it’s clear that one of the most difficult challenges in measuring service costs hinges on the ability to identify when consecutive work orders are related to the same issue. Organizations that carefully track when cases that were previously closed, were closed in error -- because the root issue wasn’t resolved properly the first time -- are rare.

How to measure mean time to resolution:

One of the best ways to track cost per work order is to use the metric to measure service cost per success. By flipping to the positive outcome, your organization will have a better understanding of who within your workforce are the heroes of your organization (those who resolve issues with minimal parts and visits). The difficulty with measuring each success is understanding whether a case is isolated or related to another case. Depending on how you capture data, you can use different methods to measure successful events, including the method describing how to measure repeat visits previously.

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KPI#5: NET PROMOTER SCORE

 

What is it?

Net promoter score (NPS) is one of the most widely used methods to identify customer satisfaction and loyalty. Simply put, it measures the number of promoters and detractors for the service you provide

How it measures workforce performance

There is no other metric that reinforces the statement “customer is king” more than NPS. Happy customers overwhelmingly signal strong workforce performance. Typically, NPS measures a qualitative experience (technical workforce skills), such as how quickly a problem is resolved, but sometimes, NPS reflects a customer’s opinion about how they feel they’ve been treated (soft workforce skills).

How it measures Customer Experience

This is one of the most straightforward measurements possible to gauge customer satisfaction.

Challenges of measuring mean time to resolution

• Net promoter score alone is not a true measure of workforce performance: While customer satisfaction is a critical component in delivering great customer service, NPS alone is an incomplete measure of the performance of your service workforce. In service organizations where NPS is the measurement used, service costs skyrocket. Customer service professionals provide endless perks and free services in order to create customer loyalty. Unless this is part of your organization’s objectives, be careful when using NPS alone. 
• Net promoter score is difficult to attribute to any one service factor: While NPS is a comprehensive measure of a customer’s experience, it’s difficult to use it to clearly identify any one specific factor or event that impacts score.

 

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In the final feature in this series we will look at the Aquant Workforce Performance Index and how field service organisations like yours are leveraging this to improve their customer satisfaction ratings. Look out for this article in a weeks time!

Alternatively, subscribers to www.fieldservicenews.com can access the white paper on the button above and the rest of our premium content library! Join 30K of your field service management peers and subscribe @   www.fieldservicenews.com/subscribe

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Further Reading:

• Read more about Leadership and Strategy @ www.fieldservicenews.com/blog/tag/leadership-and-strategy
• Read more about Managing the Mobile Workforce @ www.fieldservicenews.com/blog/tag/managing-the-mobile-workforce
• Read more news and articles featuring Aquant @ www.fieldservicenews.com/hs-search-results?term=aquant
• Connect with Edwin Pahk on LinkedIN @ https://www.linkedin.com/in/edwin-pahk-8a066515/
• Find out more about the solutions Aquant offer to help field service companies @ www.aquant.io/
• Follow Aquant on Twitter @ twitter.com/Aquant_io

In a recent presentation in the Field Service News Digital Symposium, Mark Hessinger, Vice President, Global Customer Services, 3D Systems Corporation outlined how his organisation had harnessed Artificial Intelligence within their service triage and delivery having implemented Aquant’s AI-powered tools.

It was an impressive presentation that outlined several different benefits that 3D Systems Corporation realised in just a matter of months since the implementation.

Perhaps the one critical takeaway from Hessinger’s presentation was just how many aspects of their service delivery had been touched and optimised by the Aquant AI solution.

During the presentation, Hessinger referred to benefits that included vital areas that are high on the agenda for improvement, by many if not all field service organisations. Hessinger explained how they had seen direct performance improvements in the optimisation of the service logistics chain, a significant reduction in truck rolls and an increase in perhaps the most crucial metric within service delivery – first time-fix rates.

"All those things come together, the better information you have, the better accuracy you have on resolving things..."

However, during the Q&A segment of the presentation, Hessinger was quizzed by Kris Oldland, Editor-in-Chief, Field Service News about what was the critical factor that drove 3D Systems Corporation to seek out an AI solution and engage with Aquant?

“We met with Aquant at a field service conference, and found somebody who was trying to solve the problem that we were trying to address” Hessinger had commented during the presentation – so what exactly was that problem?

Mostly, it was the result of the evolution of the 3D printing sector itself as the industry evolves from supporting prototype development to full production.

As Hessinger explains, “The key driver was after I joined 3D Systems, we had to make that shift from supporting a prototype house to a production environment. If the printers are not working in a prototyping environment, they [the client] may call today, with an expectation of us being with them in a few days. In production environment you have to be so much faster because a 3D printer not producing final parts directly impacts revenue."

“I was looking for a tool that could help us with just improving the speed and the rate of resolution. All those things come together, the better information you have, the better accuracy you have on resolving things. It just allows you to get to solve the problem faster,” Hessinger adds.

“Resolving problems quicker and more accurately was one of them was the key driver initially.”

Further Reading:

• Read more about Digital Transformation @ www.fieldservicenews.com/blog/tag/digital-transformation
• Read more about Artificial Intelligence @ www.fieldservicenews.com/hs-search-results?term=Artificial+intelligence
• Read more exclusive FSN news and features from the Aquant team @ www.fieldservicenews.com/hs-search-results?term=Aquant
• Connect with Mark Hessinger on LinkedIN @ https://www.linkedin.com/in/markhessinger/
• Find out more about Aquant's AI-powered service triage @ www.aquant.io/
• Follow Aquant on Twitter @ twitter.com/Aquant_io

 In this first article in a series of excerpts from a recent white paper published by Aquant, Edwin Pahk, VP Product Marketing and Business Development, Aquant explained why now more than ever what we measures matters. Now in the next feature in this series we look at the first two of five crucial KPIs that field service organisations must monitor

Would You Like to Know More? www.fieldservicenews.com subscribers can access the full white paper on the button below. If you are yet to subscribe join 30K of your field service management peers and subscribe now by clicking the button below...

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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 white paper. 

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KPI#1 FIRST TIME FIX RATE

 

What is it?

First time fix rate (FTF) is one of the most popular metrics for workforce measurement. It’s simply how often someone is able to fix the issue in question on the first try. This is typically referenced in both a contact center and field service scenario.

How it measures workforce performance

Generally, it’s assumed that the higher the first time fix rate, the more competent or skilled the technician is.

How it impacts customer experience

FTF makes a big impact on great customer experience. Customers want resolution quickly, and they don’t want to have to place a service ticket two days later because the issue was never properly resolved. Solving issues correctly the first time boosts a brand’s value and acts as a competitive differentiator, making it just as important as the quality of the initial product or service.

Challenges to measuring first time fix rates

• Service costs can increase: Service organizations often throw a lot of money at the problem to increase first time fix rates. The problem? First time fix rates alone do not represent the skill level of your workers. For example, a technician tends to swap costly parts for a new one every call instead of digging deeper into how to fix the root issue. Stats will show a high FTF, but doesn’t take into account that a cheaper option could likely have fixed the problem
• First time fix doesn’t reflect technician skill: Not all issues resolved on the second attempt reflect technician error. Often, failure to achieve FTF happens in tandem with an accurate diagnosis. If the dispatcher didn’t provide insight into the situation, a tech may arrive onsite, quickly diagnose, but need to come back later that day or days later with the right part. Understanding the context of what the metric represents is just as important as measuring first time fix rates.
• Properly defining and tracking first time fix is a challenge: This is especially problematic depending on how an organization tracks the KPI. If each new ticket is measured in a vacuum, a first time fix rate may be high. But what if tech thinks they fix the issue on the first visit, only to be called back a week later because of a different problem with the same machine? If the tech makes another quick fix, you record that as another FTF. Go team!
  But wait a minute. What if a third ticket is issued a week later and a different tech arrives on-site to realize the first tech was simply putting a band-aid on a more complex root issue? A deeper analysis of these common miss measurements finds that service organizations really have more chronic repeat visit problem than they realize.

How to measure first time fix:

It’s not an exact science, but a much more accurate approach is to measure whether there was a visit for that same asset or issue that occurred within X number of days of the previous visit. While this isn’t a complete solution, it addresses the major fallacy of the first time fix rate.

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KPI#2 MEAN TIME TO RESOLUTION:

 

What is it?

Mean time to resolution (MTTR) refers to the time it takes to resolve a customer issue. This is typically defined as the time between the case creation date and its closure date. Similar to the pain of staying on hold when trying to resolve a personal issue, minimizing MTTR is a key factor in increasing positive customer experiences and reducing costs. Organizations with high MTTR often have techs who find themselves in escalation black holes.

How it measures workforce performance

MTTR has an inverse relationship to first time fix rate. As your FTF rate goes up, MTTR should go down. How so? That’s usually related to service heroes resolving issues (really resolving the root cause) on the first visit, with the right parts and tools to make quick work of the problem.

How it Impacts Customer Experience

Consumers and B2B clients want immediate service. Amazon Prime, overnight shipping, Netflix, and more all represent the demand for immediacy. MTTR is a critical part of that customer service experience, and if your customers don’t receive the attention and quick resolution they want, they’ll seek out a competitor.

Challenges of measuring mean time to resolution

• Poor data collection or lack of uniform data: This is the biggest issue related to measuring MTTR. While case creation/creation date is a fairly consistent data point across organizations, case resolution time or date is much less reliable due to poor data collection. The biggest issue here is a lack of compliance among users -- technicians often forget to close out cases until days after the problem is resolved.
• Dependence on first time fix measurement: MTTR is highly dependent on how FTF is measured. Failed visits have a profound impact on MTTR, and the stats are grim. Issues not resolved the first time require, on average, another 14 days to resolution. The reason is often attributed to the need to order additional parts, scheduling issues with customers. MTTR suffers from the same challenge as FTF if the root causes of failure aren’t addressed.
• Mean time to resolution is a measure of process and people: It’s tough to separate the two. MTTR can be used to measure workforce productivity, but it’s also a measure of capacity and process. Sometimes when MTTR slumps, that’s the result of lack of enough headcount versus workforce performance.

 

How to measure mean time to resolution:

There are several approaches to mitigate some of the challenges faced when measuring MTTR.

• Measure the difference in mean time to resolution rather than overall rate. Instead of looking at MTTR as a single unit, focus on the aspects of MTTR that reflect workforce performance. For example:
  • This can be identified in the difference in MTTR between individuals when a failed visit occurs. Service professionals who often require multiple customer visits will generally have greater MTTR rates versus your best experts who seldom make repeat visits.
• Use only open dates to measure mean time to resolution. Given the lack of quality in measuring accurate resolution dates, using open dates and visit dates to define the MTTR threshold is a way to identify MTTR. This eliminates the inconsistency in resolution or close dates, and will only work on customer issues with failed visits.

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In the next feature in this series we will look at three more crucial KPIs, Mean Time between Failure, Cost Per Service Per Technician and Net Promoter scores. Alternatively, subscribed now for access to the white paper above and the rest of our premium content library @  www.fieldservicenews.com/subscribe

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Further Reading:

• Read more about Leadership and Strategy @ www.fieldservicenews.com/blog/tag/leadership-and-strategy
• Read more about Managing the Mobile Workforce @ www.fieldservicenews.com/blog/tag/managing-the-mobile-workforce
• Read more news and articles featuring Aquant @ www.fieldservicenews.com/hs-search-results?term=aquant
• Connect with Edwin Pahk on LinkedIN @ https://www.linkedin.com/in/edwin-pahk-8a066515/
• Find out more about the solutions Aquant offer to help field service companies @ www.aquant.io/
• Follow Aquant on Twitter @ twitter.com/Aquant_io

You can’t manage what you don’t measure. It is an oft repeated phrases amongst management professionals of all sectors. As we establish the way out of the toughest crisis our industry has ever seen, good management is crucial and that means the metrics we measure are more vital than ever. In this first article in a series of excerpts from a recent white paper published by Aquant, Edwin Pahk, VP Product Marketing and Business Development, Aquant explains more... 

Would You Like to Know More? www.fieldservicenews.com subscribers can access the full white paper on the button below. If you are yet to subscribe join 30K of your field service management peers and subscribe now by clicking the button below...

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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 white paper. 

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The service landscape is facing a dramatic transformation that ranges from the need to skill up a new workforce, to the move away from a reactive break-fix work towards a predictive service model. This, coupled with the desire to limit expensive on-site visits and customer demands for enhanced SLAs, means every service moment matters.

To make this transformation a reality requires a workforce of high performers, but there are plenty of hurdles on the path to achieving this goal.

Assembling and nurturing a powerhouse service team is challenging

• Baby Boomers are in the midst of a powerful retirement wave
• There is a sizable skills gap between new recruits and those who are retiring
• High paying service jobs became less desirable over the last decade as enrolment in vocational schools declined in favor of university programs
• Millennials and Gen Z seek to work, collaborate, and develop professional skills using speedy tech tools versus long-term learning plans

And the service landscape looks different, too

• Machines are more complex and require a workforce with advanced technical skills
• Consumer demand for standardized service costs are driving more predictive service offerings

• A move towards remote diagnostics and self-service triage offerings empower the customer to handle simple issues that don’t require a technician to be dispatched

• Changing economic factors are driving renewed pressure to stabilize or cut service costs

When we peel away the layers, all of this reinforces that a high-performing workforce is a key competitive differentiator. But how do service leaders move forward in this new service

landscape? Tools that map out your workforce, providing a snapshot of your experts versus challengers, and provide guidance on how to upskill the whole team is the first step.

 

Why Measure Individual Workforce Performance?

Service companies need to zoom in and out when it comes to KPIs Organizations have dashboards and charts to measure the service KPIs of the entire team, but few are zooming in to look at individual performance. Big picture knowledge is essential, but without visibility into great performers (service heroes) versus those who would benefit from training or upskilling (challengers) it’s hard to create service plans that address the root cause of workforce issues.

You likely know the shortlist of service heroes.

They are saved to your favorite contacts. And you may have a training plan for a few of the team members you know are struggling. What about the other 98% of the team? How are they really performing, and what do they need to do to level up and develop the skills and confidence of your superstars?

There are some obvious signs that members of your service workforce could use additional training. For example, those who regularly require repeat visits to remedy less complex issues is an obvious sign. What about more subtle indicators?

Some on the team may appear to check all the right boxes but may be struggling in other ways, such as racking up high parts costs by swapping out parts until the job is fixed.

This is where workforce measurement helps make sense of employee data by analyzing KPIs in a way that really matters. It can spot inconsistencies in service quality among the team and help you pinpoint who needs training and who is in the best position to provide mentoring.

But, there’s a caveat! Before you can get here, you need to measure the right things the right way.

 

Do the KPIs You Measure Provide the Right Insights?

We see you shaking your head. Service organizations already spend quite a bit of time and effort tracking workforce KPIs, and most service leaders keep a constant eye on those numbers.

But right now those KPIs tend to be narrowly focused on single measurements such as productivity or first time fix, and they don’t provide a holistic snapshot.

Without zooming out for a 360-degree view, measuring in isolation often leads to systemic and costly service issues. Instead of focusing solely on “what” to measure, it’s more important to ask “how” you are measuring. Do you have access  to the right mix of information to measure what really matters? That should include understanding metrics at a macro level across the organization and on an individual level. Take a deep dive into your data.

Does one KPI improve, only to have another fall below target? Not analyzing the right data, or not doing so in the right way, can be just as harmful as not measuring at all.

In the next feature in this series, we will look at the five key KPIs that, when understood in relation to each other, can provide an accurate snapshot of what’s really going on with your service teams.

 

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Further Reading:

• Read more about Leadership and Strategy @ www.fieldservicenews.com/blog/tag/leadership-and-strategy
• Read more about Managing the Mobile Workforce @ www.fieldservicenews.com/blog/tag/managing-the-mobile-workforce
• Read more news and articles featuring Aquant @ www.fieldservicenews.com/hs-search-results?term=aquant
• Connect with Edwin Pahk on LinkedIN @ https://www.linkedin.com/in/edwin-pahk-8a066515/
• Find out more about the solutions Aquant offer to help field service companies @ www.aquant.io/
• Follow Aquant on Twitter @ twitter.com/Aquant_io

It’s well documented that happier and more engaged employees significantly boost customer experience. While plenty of workforce experts are armed with advice on management style, culture, and incentivization as a way to boost engagement, our customers and partners in the service industry also look at another factor — workforce experience. 

In the service industry, much of what drives customer satisfaction is directly related to the experience of the field service engineer on the job.

And right now, the average tenure of the workforce in the service industry is declining due to all the reasons that service leaders lament daily, including retiring Baby Boomers, higher turnover for younger workers, and a changing job market. 

It’s important to improve the collective knowledge of the entire workforce. Once you’ve bridged the knowledge gap, then it’s easier to improve service delivery. Here’s why: 

Experience and Training Builds Confident Employees 

If your employee isn’t sure how to make the correct fix or spends the bulk of their time on the job swapping out parts until the issue is resolved, they won’t be able to move forward and develop customer relationships. It’s also been shown that those with lower confidence levels project lower confidence to others around them. 

Ensuring field technicians are trained, mentored, and given tools to help them do their job right the first time, builds a positive reinforcement loop. Providing up-to-date technology also further engages Millennials and Gen Z who are motivated to master technology, seeing it as a career advancement step. And once they’ve mastered it themselves, they’re more likely to share tips and hacks with colleagues, creating an informal learning environment that increases confidence and workforce proficiency.

Studies have also shown that confident employees boost the bottom line. Employees that show greater confidence levels, on average, have 22% higher sales.

At a time when service models are moving away from break/fix work and towards proactive plans that rely on consistent service, and require some upselling on the part of service technicians, confidence and experience is key.

The Power of Tribal Knowledge - Equal Access to Knowledge is Key

Your most experienced employees have the most institutional knowledge, but they are also retiring in droves. There are ways to quickly upskill less tenured employees by using the deep expertise that has historically been locked in the minds of your best veterans. This is how to share tribal knowledge.

AI technology captures siloed tribal knowledge, makes that knowledge accessible across your workforce, and empowers junior employees with the wisdom of your experts. It’s also a way to effectively listen to the advice from your most tenured employees and work with them to put their wisdom into practice — showing them how their skills directly result in better customer experience. 

How can you transfer workforce knowledge quickly? AI combined with natural language processing does the work of years of in-the-field training. It takes historical data (including technician notes and other free text) and tribal knowledge, and turns that into prescriptive and actionable insights, accessible to everyone including customer service agents and field technicians on the job.

Customer Success: How Becton Dickinson Accelerated Knowledge Transfer - They leveraged AI to boost employee morale and NPS scores.

While service teams across the nation need to consistently hone their technical skills, technicians at BD (Becton Dickinson) need to be even more in step with machinery. The group services two main types of medical instruments: research instruments that are often specially designed for each client, meaning many are unique and clinical instruments that fall under strict FDA regulation.

The problem: 

A few years ago morale was low, employee attrition hovered around 26% and the service teams were consistently failing to meet SLAs. This also caused rising expenses, falling revenues, and record low customer satisfaction, with a net promoter score around 40%

Nearly half of the BD service workforce had less than 3 years of tenure. More experienced service engineers had an overloaded schedule and didn’t have time to train or coach newer employees.

Steve Chamberland, Director, US Service Operations at Becton Dickinson explained in a webinar that the team took drastic measures to improve performance by focusing on employee experience and training. He notes that the company adopted the following outlook to guide a transformation, “Employee experience leads to improved customer experience and that led to improvements in financial performance, which drove profitability.”

The Solution: 

BD invested in a range of technology solutions, including Aquant, and implemented an internal technology panel that consisted of gathering feedback from seasoned field service engineers. The goal was to boost morale while simultaneously enacting a service transformation based on their internal expert advice combined with the aid of tech tools. 

When it came to specifically using Aquant to aid in service, even with specialized machines and terminology, the Aquant NLP engine learned the service language unique to BD. And then turned to the input of experts to help further train the system to ensure the suggested solutions are the most accurate.

The Results:

Employee service and morale improved significantly after they had access to tools that helped them do their job more accurately. They also felt more empowered to make good service decisions. 

• Employee attrition dropped from 26% to 1%
• SLA commitments shot up to 99%
• Net promoter score now averages 80%

To learn more about how customers are using Aquant to build experience and improve the service experience, listen to the full webinar with Becton Dickinson. 

Join the webinar to hear how a leader in healthcare diagnostics is implementing AI tools.

As the medical device space shifts to more specialized equipment, organizations are increasingly turning to AI-powered tools to ensure maximum uptime for mission-critical equipment. For those who manufacture and service these machines, debate hinges on whether to build or buy AI platforms. Join the webinar Sysmex America, Inc. and Aquant to hear about the journey choosing AI tools.

In the live webinar, learn how Adan Deroche and Peter Tregarthen of Sysmex America, Inc., a leader in healthcare diagnostic solutions, took steps to:

• Assess the benefits and drawbacks of internal development versus using an AI vendor
• Uncover and analyze free text service information to drive meaningful outcomes in service delivery
• Work with Aquant to determine a roadmap for success by combing the knowledge of employee experts with the output of the tool’s AI-powered solutions.

Sign up here for the live webinar. We’ll be walking through Symex’s AI journey and are available to answer your questions.

What: Live Webinar with Sysmex America, Inc. and Aquant

When: June 9, 2020 @ 12 PM EDT

How: Register now

About Aquant

Aquant’s service intelligence platform transforms how organizations deliver service through artificial intelligence. The platform unlocks prescriptive and actionable insights from scattered data and free text and combines them with the collective experience and tribal knowledge of your most trusted experts. It empowers teams to use that intelligence to predict outcomes, optimize service team performance, and solve problems to deliver exceptional customer experiences. Learn more at Aquant.io.

As the service sector looks to reduce site visits in line with current social distancing measures Aquant suggests a solution to maintaining continuity during the pandemic lies in (Artificial Intelligence) AI, remote technology and better data collection.

The service industry does what it does best when in the field, repairing or maintaining equipment. But the medical community is urging us to #StayHome while we fight the pandemic. Service pros can’t unilaterally stay home, but there are ways to reduce the number of site visits needed, while still solving customer issues. And even as the pandemic declines, we are likely to see some social distancing remain, and a rollout of more rigorous health and safety policies that slow a full return to business as usual.

THE BEST WAY TO MANAGE fIELD SERVICE CONTINUITY

Service leaders are accelerating longer-term transformation plans that include self-service solutions, AI tools, more remote diagnostics, better data collection for predictive maintenance, and other changes that limit the number of visits technicians must make to work sites. While some solutions can be deployed more quickly than others, there are ways for service organizations of all sizes to immediately resolve issues faster.

Problem Solving & Planning With AI

1. Increase First Contact Resolution

Resolve less complex issues on the first call. Al tools can enable customer support agents to triage problems during initial contact. To do so, empower agents with the assistance of a robust triage tool that understands every customer and their equipment, and is able to make intelligent service recommendations.

That smart system gives your customer support team the ability to walk through dynamically generated, intelligent checklists with customers. Unlike decision trees, these checklists are created by using smart algorithms that are validated and improved by expert employees and continue to learn and evolve over time.

The more information the agent can prompt the customer to provide, the more accurate the suggested solutions, and the shorter the job duration. For example, the more time spent on remote triage upfront, the better prepared a technician will be on arrival — bringing the appropriate parts or tools. In addition, it provides opportunities for customers to undertake simple solutions themselves when possible.

2. Offer Self-Service Solutions

In addition to providing customer-facing agents access to a diagnostic solution, consider adding a self-service tool to your website for customers to access directly. Direct customers to use the resource to diagnose, and in some cases resolve, simple issues remotely without the need to dispatch a field technician. The most important aspect is that self-service tools are intuitive and:

• Includes an easy-to-use UI
• Asks questions in plainly worded language
• Can understand customer intent regardless of word choice they use to describe a problem
• Recommends the most likely fix that’s possible to achieve remotely.

The addition of self-service tools will immediately mitigate some of the travel problems associated with COVID-19, while also laying the foundation for a longer-term strategy that reduces the burden on an over-scheduled workforce.

3. Use the Right Parts the First Time

Most service organizations face two big parts problems:

The first is a lack of parts or rather a lack of the right parts. If a technician goes into a job without enough context about the issue or is a more junior member of the workforce, there’s a good chance the first visit will simply be a diagnostic one, and then they’ll need to return at a later date with the correct part or parts to complete the job. No technician wants to make multiple visits right now.

The second problem is often harder to detect. That’s the challenge that goes by many names including shotgunning, swap ‘til you drop, or troubleshooting with parts. It’s far more costly when field technicians cycle through more parts than required for a job. It’s also a drain on resources when inexperienced technicians, without the right guidance, struggle by swapping out parts until the issue is resolved. Instead of trial and error, choose AI tools that tap into organizational data, analyze that data, and provide techs on-site with the most efficient path to resolution — decreasing the time it takes to complete a job while also lowering service costs.

4. Analyze Hidden Data to Transition to a More Predictive Service Model

We’ve talked to service leaders across the country, and a common thread is that they are preparing for the post-pandemic, new normal. Future-looking service organizations are driving towards more planned and predictive models which will allow for more strategic workforce planning, fewer site visits, and more steady streams of revenue. And they know that to get there, they need better ways to wrangle historical data along with the ability to monitor and react to IoT and machine outputs effectively.

Start Planning for the Future What’s next for your service organization? Learn how AI-powered Intelligent Triage reduces repeat visits, increases first contact resolution, and creates a better customer experience.

Further Reading: 

• Read more about remote technology in service @ www.fieldservicenews.com/remote
• Read the latest news about Covid-19 and service @ https://www.fieldservicenews.com/covid
• To find out more about Aquant click here.

Service leaders community includes roundtables, webinars and executive slack workplace.

Service professional have dramatically altered their plans due to Covid-19. Simultaneously, they are preparing long-term strategies for recovery and growth. Without a blueprint, they are making quick pivots and seeking the support of colleagues to discuss what's working, what to avoid, how to keep their workforce safe and how best to maintain continuity.

In response, Aquant has created a content hub, Resources for Resilience, which includes webinars, virtual roundtables, and other ways for the service industry to connect. 

We've listened to our customers and the industry as they ask, 'What's next?' and work to figure our the complex challenges that lay ahead for them," said Mairead Ridge, Aquant's VP of Marketing, "Our goal is to help service leaders learn from the experiences fo their peers by amplifying the collective wisdom of service pros across the industry."

Join the Slack Workspace for service leaders, a place to have the important discussions they'd otherwise be having at industry events and forums, now postponed.

Upcoming events include:

May 5 - Virtual Roundtable: An Interactive Discussion about Covid-19 Response

Attend a forum of field service leaders for an interactive discussion about facing the challenges of the Covid-19 pandemic. Share ideas and get inspiration from other service professionals about response and recovery. Sign up now.

May 12 Webinar - Creating the Service Organization of the Future

Rodger Smelcer, Co-Founder and VP of United Service Technologies is mounting a Covid-19 comeback strategy; making investments in technology and and workforce training that is moving the organisations away from reactive break-fix work and towards planed an predictive maintenance. Register to attend.

Webinar Replay - Adapting Service Innovation Strategies for the New Normal

Join Gyner Ozgul, Senior VP of Operations at Smart Care Equipment Solutions as he discusses how his organization is changing the way they do business by empowering its workforce to make better, data-driven decisions. Listen now.

Webinar Repay: How Comfort Systems Combats Shifting Workforce Challenges witg AI

Joe Lang, VP, Service Technology and Innovation of Comfort Systems, shares how the team is using AI to build a single source of service knowledge based on the collective experience of the workforce. He also touches on the strategic initiative for up-skilling a new generation of technicians. Listen now.

To learn more and connect with service peers, visit Resources for Resilience, a Series for Service Leaders