Learning Data: The real definition and how you can prove business impact

What is learning data? Let’s define it as “data used to measure and improve the impact of training.” Based on that definition, what learning data are you currently using? If you’re like most learning organizations, you’re currently tracking metrics such as:

• Online course completions
• Class attendance
• Test scores
• Seat times
• Survey feedback

Is this data sufficient to meet our definition? Well…let’s have a look.

Does this data show that people learned from your training?
No. It shows they did it and passed a test. It shows if they liked it. But none of this means they actually learned anything.

Does this data show that employees changed their behavior on the job based on your training?
No. Behavior change takes time, and most training programs have set start and completion dates.

Does this data show that your training positively impacted business results?
No. It actually has nothing to do with business impact, which also takes more time to measure than is typically allowed.

So, no, this data isn’t enough. It’s not completely worthless, but it’s pretty close. It can’t meaningfully inform your training strategy. It doesn’t offer insight into how well your training team is doing. And, worst of all, it can’t justify the value of your work to your stakeholders.

To really understand how your learning strategy is impacting your employees and your business, you have to expand your data scope to include modern learning metrics. This multidimensional perspective will not only help you validate and improve the impact of training, but it will also enable you to take the next leap forward in your learning strategy. This is the type of data that makes the future of workplace learning, including personalized and adaptive learning, machine learning and artificial intelligence (AI), possible today.

Modern learning metrics

Here’s a list of modern learning metrics you should begin to integrate into your measurement strategy if you want to improve the impact of your learning strategy.

Engagement: Think of this as the new version of participation. It’s not enough to know if someone went to class or completed a module. Engagement measures how frequently employees participate in training. This will help you directly correlate learning activity with changes in other metrics.

Knowledge: If you give someone a test at one point in time, you know what they knew at that one time. Remember—people forget! To really understand what people know, you have to continuously assess their knowledge. This will allow you to measure changes in knowledge—both increases and decreases—over time.

Confidence: It’s not enough to know something. You must have the confidence to turn that knowledge into action at the moment of need. Asking employees to continuously self-assess their confidence in various topics can help you identify potential indecision— before it happens.

Behavior: This is learning transfer. How have employees’ behaviors on-the-job changed since training took place? Collecting behavior observation data not only helps you connect knowledge growth to real-world action, but it also provides you with opportunities to correct behavior gaps before they cause problems.

Results: This is the ultimate goal. What happened to the key performance indicator (KPI) that you were trying to impact in the first place? By connecting the rest of your metrics to business result data, you can finally prove the value of your training.

How to get meaningful learning data

Now the big question is…How? How do you go from measuring with just tests and surveys to building a continuous, multidimensional data model of your learning organization? The answer: microlearning. A microlearning approach will help you become more targeted in the way you build training. It will also facilitate a more consistent learning experience for employees with more touchpoints and therefore opportunities to collect data. By shifting from one-and-done training to a continuous, microlearning approach, you can expand your measurement strategy and gather the insights necessary to prove your impact on the business.

Yes, you should still track course completions, seat times and survey results—but only when necessary. Rather than tracking just for the sake of tracking, you can design an experience built to provide relevant data that will improve your impact and increase the value of learning in your organization.

This might seem like a daunting task, but we can help. If you want to learn how you can leverage data to prove the impact of your learning programs on the business, make sure to visit our Measurement page.

JD Dillon, Chief Learning Architect

JD Dillon became an expert on frontline training and enablement over two decades working in operations and talent development with dynamic organizations, including Disney, Kaplan and AMC. A respected author and speaker in the workplace learning community, JD also continues to apply his passion for helping frontline employees around the world do their best work every day in his role as Axonify's Chief Learning Architect.

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