When it comes to your training program effectiveness, data could tell the difference between a win and a total failure. You already know that learning metrics are important. But collecting these metrics is just as important as the ability to read the story they tell.
And that story might not always be a good one.
Your training strategy is focused on results and you need a way to see whether you’re achieving them. Training data is key to finding out what’s really going on. Digging deeper into the numbers can help you see red flags and address them to ensure training success.
Why you need to dive into learning metrics
To make sure training is more than just a box to check, you need to have a data-driven learning strategy. And if you want to know whether your training is reaching your goals, scratching the surface of your training data is usually not enough. You’ve got to dive deeper.
For example, you might be happy to see high attendance rates on a webinar or a 100% completion rate on a compliance course. But did your employees truly learn what they were supposed to learn? How do you determine whether the skills and knowledge are being applied back on the job?
Also, your boss, the budget manager, or the senior management team have made decisions to invest in your training strategy. You need to provide definite proof that it’s working and that time and money aren’t going to waste. And when you present training analytics, you need to make sure there are no gray areas.
Know what the numbers mean and what they show. Especially if they show your training is failing.
Gather both qualitative and quantitative data
The first step toward diving into data is to collect the right kind. Quantitative data is a good starting point. It shows you the numbers—things like how people engage with the training and how well they’re testing. These numbers can highlight the weak points in your training but don’t necessarily address the “why” behind them.
Include qualitative data in your reports, too. Run surveys around the learning experience. Or, send out assessments exploring what supervisors and employees are experiencing back on the job. These in-depth analyses can give you a sense of whether people are retaining the information they learn.
So exactly what data should you look at to get a real sense of whether your training is in trouble?
5 learning metrics that can tell you if your training is failing
To see how your training is doing, start by reviewing your training KPIs. What do you want to achieve with training? You can only tell your training is struggling when you can see where it’s not reaching its goals.
Training strategies and goals differ from company to company. But there are key metrics that can reveal training gaps and areas for improvement regardless of the strategy. You need to look at data that goes beyond the obvious numbers around engagement and completion rates.
Here are five deeper measurements that can help tell the more complete story.
1. Course completion time
Don’t just focus on whether employees finished a course or how good their test scores are. Take a look at how long it takes learners to finish their training. High test scores mean employees are learning the content. But what if it took them five or six months to complete that course?
The faster employees learn, the more quickly they’ll implement the skills, and the sooner you’ll see results.
Check average times to complete the course as well as individual times. Patterns of slow time to completion could mean your instructional design needs to be more effective. For example, you might need to simplify some sections, break a course down into smaller chunks, or prepare a suggested training schedule for your employees.
2. On-the-job learning transfer
High test scores aren’t always an indication that people actually learned the skills. Perhaps the questions are too simple or employees get the correct answers while information is still fresh in their minds.
For training to be truly successful, employees should apply what they’ve learned. You can gauge how much they’ve learned and whether and how they’re using them on the job by sending post-training surveys. Gather performance data (i.e., numbers associated with your company goals). Or, poll managers and peers about the results they’re seeing.
If you have KPIs around behavior change or business results, a lack of change in performance is a big sign that training isn’t working. You should revisit your training and find a way to help people transfer the skills back on the job.
3. Employee satisfaction
Engagement scores and completion rates are good surface indicators of success. But those numbers may say more about your employees’ diligence than training effectiveness. Find out more about your training’s impact by looking at employee satisfaction.
Include post-training survey questions like “How likely would you be to recommend this course to a colleague?” or “On a scale of 1 to 5, how helpful did you find this course?” These learning metrics will help you know whether employees see the value of training. If they don’t think it’s worth sharing with others, you may need to adjust your training to make the connections to company and employee goals more clear.
4. Highest and lowest performers
You want all your employees to benefit from training, but each person learns differently. Catering to different learning styles is key to helping everyone have a good training experience. If you want to find major gaps in your training, look for trends among learners.
Pay attention to patterns around who isn’t scoring as high on assessments or who’s moving more slowly through a course. Consistent issues with the same groups can be a red flag that your training isn’t speaking to certain types of learners. This can be an indication that you need to diversify your delivery methods.
5. Interaction with the training material
Note how learners interact with different parts of their training. Do they return to certain content over and over? Do they drive more online discussions or leave more comments around a certain video or exercise?
These reactions indicate that people find these elements more engaging or useful. On the other hand, sections that don’t see return traffic or where people spend very little time could mean that they don’t find the content valuable or that they don’t understand it.
How to use data to improve your training
Looking at these learning metrics, among others, can help you see the warning signs that your training isn’t succeeding. Here are some ways you can use what you learn from data to make improvements.
- Add more learning modalities. To address poor engagement or slow learning times, consider including more diverse content types. Create videos or infographics. Offer more hands-on exercises or interactive quizzes. You may also consider giving learners access to additional resources. For example, provide links to articles, lectures, or videos around a topic and let them choose their own learning path.
- Make sure all your content is high value. If people don’t report finding value in certain content, revisit it. If it’s crucial content that’s just not reaching learners, revise the material. Clarify how this course aligns with business goals and employee development. If you find the content in question isn’t necessary or helpful, consider removing it. Focus on your training KPIs and make sure all your content serves your goals.
- Replicate your success. If certain parts of your training are having a bigger impact, look at how you can mimic them in the parts that aren’t doing so well. What’s working in the lessons people are more engaged with? What’s the standout feature in the content around skills that are being more widely adopted? Consider things like delivery (engaging videos, helpful graphics, quizzes) and clarity (Does the training outline how it’s important to learners’ success?).
- Provide practice opportunities. If you want to boost skill transfer, give learners chances to practice. Help employees bridge that gap by building muscle memory for using the skills. Include practice sessions and tests where they apply skills to real-life situations. Or run follow-up sessions for role-playing or reinforcement exercises to give them an even more consistent experience.
- Gather data before and after changes. Changes don’t necessarily lead to success. After you implement a solution, gather more data. Compare results from before and a reasonable time after the update. If you don’t see the progress you need, go bigger with the changes. Or, revisit your previous data and look for other sources of the problem.
Strengthen your training with a data-driven strategy
By analyzing learning metrics, you learn what’s working and what’s not. Going deeper gives you a clearer picture and a better chance of saving training that may be failing. That’s why a data-driven learning strategy is important to your success.
Let your tech do the heavy lifting of collecting complex data. Leverage your LMS reports to show the numbers so you can focus on the more creative aspect: reading the story behind the numbers and improving the actual learning process.
