A New Approach to an Age Old Problem?

Aug 13, 2020 • Features • Ageing Workforce Crisis • Artificial intelligence • Video • Digital Transformation • Aquant • north america • Field Service News Digital Symposium

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.