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EPISODE 115: How AI Improves Skills Training Impact
Lefteris Ntouanoglou, Founder & CEO, Schoox
As AI reinvents business from the ground up, frontline workers are facing tremendous challenges. Organizations need fast, effective skills training now, more than ever. How are LMS vendors stepping up with next-generation solutions?
That’s what I’m discussing today with one of the industry’s leading innovators, Lefteris Ntouanoglou, President and CEO of Schoox. Since 2012, he and his team have been on a mission to fundamentally transform frontline training.
So, join us, as Lefteris and I discuss recent breakthrough advances in frontline learning systems, on the Talented Learning Show…
AI IN FRONTLINE SKILLS TRAINING — KEY TAKEAWAYS
- The frontline workforce is massive, representing nearly 80% of employees in the U.S. and abroad. Yet sky-high turnover and persistent talent shortages underscore a critical need for effective skills training.
- Because most frontline workers operate in “deskless” roles, reaching them through digital technology and keeping them engaged is especially challenging. The best skills training is designed with these issues in mind.
- AI is changing the learning landscape at warp speed, and skills training is no exception. Employers that leverage AI to rapidly develop, deliver, measure, and improve frontline capabilities are seeing significantly better business results.
AI IN FRONTLINE SKILLS TRAINING — Q&A HIGHLIGHTS
Welcome back, Lefteris. Several years have gone by since our last podcast discussion. So, why don’t you start with a brief update about your company?
Sure, John. Over the years, Schoox has evolved into a complete platform for learning, development, and business growth. Honestly, this unified approach was our vision from the beginning, over 10 years ago. We knew this is how it should be. But putting all the pieces together has been very hard.
Along the way, it sometimes seemed like a Frankenstein solution. But now, AI has reached a level of maturity that makes it possible to connect all the dots.
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What does this integrated approach bring? Why do you think it’s superior?
We’ve always thought the purpose of learning is to develop people. Organizations invest in developing people so they can contribute to business success.
But with so many different applications supporting different L&D activities, solutions have never been integrated in the way they should be. It is not enough to see what training someone completed in a performance review application. That’s just data sharing.
All these systems should be connected so that data produced in one application has an impact on what happens in other applications.
Here’s a small example. If you have a skill assessment with a low score, that should trigger the learning application to recommend the right training to improve your score. But that kind of sophisticated integration has not been possible within one application.
Interested in Schoox? Check reviews, demos, case studies and more in our independent Learning Systems Directory! SEE THE SCHOOX PROFILE →
Which elements need to be centralized, in your view?
The whole spectrum of learning activities should be included — not just self-paced learning, but also instructor-led training, and on-the-job training, which is partially social. All these activities need to be connected with each other, and with skills, goals, performance reviews, coaching, and business analytics. And these other pieces must be interconnected, as well.
All these connections are very complex and multi-layered. Because even with developing people, learning is only one aspect of development. Coaching and other activities also play a role.
But bringing all the pieces together makes a big difference.
Interesting. Let’s talk about how skills models fit in. It seems organizations have been struggling to make this work for decades. Have they rounded the corner?
Honestly, with all the market noise now, the level of maturity is much lower than you might think.
The skills-based learning trend really started after the pandemic. There was a need for upskilling and reskilling. So, organizations realized it was important to connect learning with skills.
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Hmm…
But then the conversation became consumed with ontologies and taxonomies, how to deal with diverse skill sets, and how to tie competencies to skills. It was a complete mess.
Now, organizations are paralyzed. Mostly, they focus on how to make sure they find the best potential skills ontology and connect skills with jobs. But I think that’s the wrong way to go.
Instead, focus on a business metric that a specific skill can move, within the context of the job, the brand, and the industry. When you do this, you’ll have a very different skills conversation. It becomes more practical and pragmatic.
No doubt.
For example, it is not enough to say we have to train someone on communication as a soft skill. What does that even mean? The business context is highly important.
A restaurant may want to train a server in communication, so they’re able to upsell more. Or they may want to increase order accuracy rate, which can quickly reduce customer complaints.
So, if they increase order accuracy by 3% and improve customer loyalty and satisfaction by 2%, what does that mean for the organization on an annualized basis? Now, that is a very different conversation. It is communication as a skill, regardless of its ontology.
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Makes sense…
Many of our large customers have great HCM products. And many are introducing skills in one form or another.
But you would be surprised by our conversations. Because none of our Learning Impact Suite customers are coming to us with skills mapped to jobs.
They do it through our system. It takes about 30 seconds. And they’re happy with that skills profile. But for us, it is just the first step towards building the entire business impact profile.
It sounds like an organization’s first big headache is the taxonomy. Second is the job. And third is the mountain of untagged content they’ve been accumulating for 20 years. How do you deal with that?
The biggest problem with skills is exactly what you said. Taxonomies. Skills can come into a learning solution from many different sources. But the system must be able to leverage information from a highly diverse skillset.
Let’s say you bring in skills from an HRIS integration. And you also subscribe to a third-party content library with 100,000 courses. Those courses may have skills mapped, or not. If so, they may have completely different skills. In addition, you may create content internally. And your admin makes decisions on-the-fly about what skills to use for those courses.
So, your system may have skills that are different, but nearly duplicate. Imagine 10 skills that are almost the same. Plus, you’ll need a skills assessment and a skill gap analysis for it all.
Interested in Schoox? Check reviews, demos, case studies and more in our independent Learning Systems Directory! SEE THE SCHOOX PROFILE →
Right.
That’s why we put so much effort into doing this dirty job that is very hard to explain. But without it, there is no skill-based learning.
Mmhmm…
Our functionality creates a layer of equivalent skills on top of whatever a subscription model may add. So, it automatically builds equivalencies between a skill and the skill your organization is really using.
There’s also a dashboard that helps you identify skills that are nearly duplicates, including the kind of similarity, and how many jobs and courses they impact.
It also includes tools that help you merge skills, which is a fairly complex process. Because you may have one skill mapped to 100 courses, and 10 jobs with a nearly duplicate skill mapped to 200 courses. Plus assessments. We automate and streamline the whole process.
That’s exactly why organizations got stuck on skills in the past. It’s impossible to do manually.
Yes. With this, the world will be different.
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But what about all the proprietary training content? Stuff about products, services, and processes. Do you tag all of that?
Yes. But I want to be clear. Skills is only part of the information needed to understand how to best serve a certain job with content. It is not just skills.
We allow mapping of courses with skills and processes. But to make intelligent recommendations, we also look at the rest of the metadata and the content itself.
It may include thousands of files — training materials, policies, playbooks. Everything an employee has access to is ingested and analyzed. This ensures that the system returns the best possible response for how to execute a task.
Cool. Now, let’s talk about impact, because that’s where the rubber meets the road. How do you approach this?
We’re trying to make learning meaningful, so it can serve its ultimate purpose. As we discussed, for frontline skills training in a casual dining restaurant, what matters is knowing things like how to improve order accuracy, or increase average check size, or reduce food waste. You’re interested in specific business metrics.
So, within our suite you can:
- Define the specific business impact of a job. This helps the system identify potential uplift opportunities. For instance, if your average check size is $9, how can you increase this by 5-10%? On each check, targeted skills training may make a small difference. But if you train 10,000 servers, it could mean a huge increase in overall revenue.
- Next, you’ll want to build relevant skills training for that job. The system accounts for the job context, the industry, and the behaviors needed to improve target business metrics. It also creates the ideal training plan and all course content.
- Then, no matter what training you offer, the intelligence layer continuously captures what content was offered and consumed, along with questions from people who need assistance, and outcomes. And it uses this information to provide additional training.
- Finally, a sophisticated dashboard lets you correlate skills training and improvement with business metrics. Are outcomes close to our forecast? Do we have enough data to predict future outcomes? If the system is fully built, it will suggest realistic impact adjustments. For instance, it may say you should decrease expected future revenue increases from this training by 7%.
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All training organizations face the same problem: limited resources and unlimited requests. But you help them prioritize, with predictive tools that use industry benchmarks they refine and customize over time?
Yes. And it can all be done super-fast now, so you can run pilots. Because it no longer takes months to get useful feedback from the field. That means you can roll-out and scale frontline skills training faster, with more confidence.
Are you focused only on companies with frontline workers? Or does this skills training method have broader business appeal? …
… For complete answers to this and other questions about how AI improves the impact of skills training, listen to the full episode on Apple Podcasts, on Spotify, on Amazon, or right here on our site.
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About the Author: John Leh
