If Netflix can predict exactly what you’ll binge this weekend, why are so many corporate learners still stuck with generic, one-size-fits-all training?
In a world where algorithms anticipate our entertainment preferences, suggest our next purchases, and even match us with potential partners, learning & development (L&D) has some serious catching up to do. Today’s workforce is diverse in experience, learning styles, and career goals. Yet many organizations continue to deliver uniform training programs that fail to engage, inspire, or meet individual learner needs.
Enter personalization at scale, the strategy that allows organizations to tailor learning experiences without adding overwhelming complexity or cost. Thanks to advances in AI, machine learning, and learning experience platforms (LXPs), scalable personalization is not only possible but increasingly expected.
In this blog, we’ll explore why the “one size fits none” approach is quickly becoming the future of learning and how organizations can embrace this shift to create meaningful, effective, and engaging learning journeys.
Why “One Size Fits All” Doesn’t Work Anymore
There was a time when giving everyone the same training made sense. It was easy to manage and didn’t take much time, but that was also when floppy disks ruled the tech world, and phones had cords.
Today’s workforce is a different story.
Every learner is different. Some like short, quick lessons. Others enjoy long, deep courses. Some prefer watching videos. Others want to read or practice hands-on. People have different jobs, skill levels, and career goals. Giving them all the same training is like handing out identical shoes to a whole company; someone’s sure to get blisters.
The way we work has changed, too. With more people working remotely or in flexible roles, learners need training that fits their schedules. A fixed, one-size-fits-all program just doesn’t work anymore.
And let’s be honest, people expect more now. Netflix suggests what to watch. Spotify creates personal playlists. Amazon knows what you’ll buy before you do. When workplace training feels generic and outdated, learners notice, and they tune out faster than a bad TV series.
In fact, the LinkedIn Learning 2024 Workplace Learning Report found that 78% of employees are more likely to engage with learning that supports their career and personal growth.
If training doesn’t meet people’s needs, it doesn’t just waste time; it wastes money. It can even lead employees to look for opportunities elsewhere.
The bottom line? Your workforce is diverse. Their learning should be, too.
What Is Personalization at Scale?
Personalizing learning for one person is simple. You ask what they need and suggest the right course or resource. But what if you have 500 people? Or 5,000? That’s where personalization at scale comes in. It’s about giving each learner the right learning experience without having to create a custom plan for everyone manually.
This is where technology becomes essential. Artificial intelligence (AI) (machines doing tasks that usually require human thinking) and machine learning (ML) (machines improve by learning from data) can help. They look at what learners are doing, which courses they take, what skills they need, and how they prefer to learn. Based on that, the system can suggest the best content automatically. It’s like how Netflix knows you better than your best friend, but instead of movies, it’s learning content.
Many companies use learning experience platforms (LXPs), which are smart online learning systems. LXPs organize learning materials and use AI to recommend what each person should focus on next. Some even create full learning paths based on a learner’s job, interests, or career goals.
Of course, none of this works without good data. Good data means information that is accurate, complete, and useful. It tells us things like which courses learners have completed, how much time they spend learning, what skills they already have, and how they like to learn, whether that’s watching videos, reading, or doing activities. It also shows how well they’re doing, such as whether they pass quizzes or need more help. Without this kind of data, even the smartest technology won’t know how to suggest the right content. It’s like trying to cook without knowing what ingredients you have.
Good data should also be updated regularly. People change jobs, build new skills, and shift their learning goals. If the system doesn’t keep up, personalization will soon stop being helpful. And, of course, it’s important to collect and use this data responsibly to protect learners’ privacy.
However, while technology can personalize what people learn and how they receive content, it can’t fully replace the human side of learning. Support from managers, coaches, and peers still plays an important role. Technology helps deliver the right content at the right time, but people help learners stay motivated, answer questions, and apply what they’ve learned in real life.
In short, personalization at scale means using smart technology and good data to give people the learning they need, while making life easier, not harder, for learning teams.
Real-World Examples — Who’s Getting It Right
Personalization at scale might sound like a big, complex idea, but many companies are already doing it and getting great results.
Take McDonald’s, for example. With employees all over the world, in many different roles, it’s impossible to train everyone the same way. Instead, McDonald’s uses smart learning apps that adjust the content based on each employee’s job, how fast they learn, and what they already know. So, whether someone is new to the kitchen or training for a manager role, they get just the right learning at the right time.
Deloitte, one of the world’s largest consulting firms, also uses personalized learning. They use an LXP to help employees choose learning paths that match their jobs and career goals. The system also uses AI to suggest helpful courses and resources, making it easier for people to learn what they need without getting lost in a long list of options.
Then there’s Amazon. As the company grows and changes, so do the skills their employees need. Amazon uses data to see what skills people already have and what they need to learn for future roles. This way, whether someone works in a warehouse or as a software engineer, they get learning opportunities that help them grow in their careers.
These companies show that personalization at scale isn’t just possible, it’s already happening. It doesn’t just help learners, it helps businesses too, by making sure people have the right skills to succeed.
Common Pitfalls (and How to Avoid Them)
Personalization at scale sounds like the perfect solution, and it can be, but there are a few common mistakes that can make things harder instead of easier.
One mistake is giving learners too many choices. While people like having options, too many can feel overwhelming. It’s like walking into a giant supermarket when all you wanted was a loaf of bread and somehow ending up in the electronics aisle.
Another risk is bias in the technology. If the data going into the system is incomplete or unfair, the recommendations it makes might also be unfair. For example, if past training mostly focused on certain job roles or skill sets, the system might keep promoting those same things and ignore others. This is why it’s important to check and update both the data and the recommendations often.
Some organizations also make the mistake of thinking that once the technology is in place, their job is done, but technology can’t replace human support. Learners still need help from managers, mentors, or peers. They need feedback, encouragement, and sometimes just someone to answer their questions.
Finally, it’s easy to focus only on technology and forget about privacy and trust. Learners need to know that their data is being collected and used responsibly. Without trust, even the best learning system will fail.
The good news? These problems can all be avoided with careful planning, regular reviews, and keeping people, not just technology, at the heart of the learning experience.
How to Get Started with Personalization at Scale
Bringing personalized learning to hundreds or thousands of people can seem like a big task, but it doesn’t have to happen all at once. Here are some simple steps to help you get started.
First, look at the data you already have. What do you know about your learners? What courses have they taken? What skills do they need? How do they prefer to learn—short videos, longer courses, or hands-on activities? You might be surprised at how much useful information is already available.
Next, choose technology that can grow with you. This might be a learning experience platform (LXP) or another tool that can suggest learning paths and track progress. Look for technology that can start small but expand as your needs grow. You don’t have to invest in the biggest, most complex system right away.
Then, start with a pilot program. Choose a group of learners or a department where personalized learning could make a big difference. Test your approach, gather feedback, and make improvements before expanding to the whole organization.
It’s also important to keep human support in the mix. Technology can suggest content and track progress, but managers, mentors, and peers can provide encouragement, answer questions, and help learners apply what they’ve learned in real situations.
Finally, communicate clearly with your learners. Let them know how personalization works, what data is being used, and how it can help them grow. When learners understand the benefits and feel that their privacy is respected, they are more likely to engage fully.
Start small and scale up. Even Rome didn’t personalize in a day!
Conclusion
Your learners aren’t widgets, and their development paths shouldn’t be either. As organizations strive to attract, retain, and grow top talent, scalable personalization is emerging as both a competitive advantage and an employee expectation.
By leveraging data, embracing technology, and maintaining the human touch, L&D teams can finally break free from outdated, uniform training models. If entertainment platforms can tailor our weekend watchlists, then surely, it’s time for corporate learning to tailor our career growth.
It’s time to rethink, retool, and reengage. Start small. Think big. Personalize boldly.
At ELB Learning, we can help you make it happen. Our team works with organizations to design customized learning solutions, from personalized learning paths to adaptive technologies and engaging content tailored to your workforce. Whether you’re starting small or scaling across your whole organization, we can help turn your personalization goals into reality.
Let’s talk about how we can support your journey toward scalable, personalized learning.
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