Learning Metrics or Learning Analytics?

BY Celisa Steele


Yesterday I attended the eLearning Guild’s Webinar “Collecting *Useful* Learning Data.” They had me at the title—that asterisk-sandwiched word useful is oh so important.

During the session, Neil Lasher, the learning consultant presenting, pointed us attendees to a short blog post from Talent Analytics on the difference between talent metrics and talent analytics.

Talent metrics (also known as workforce analytics) measures tangible data such as headcount, attrition, and compensation. This is appropriate to recommend when you are selling to HR. Talent analytics provides strategic talent insight and measure intangibles such as how employees work and what they are driven by, providing context that’s otherwise missing from the data. This is appropriate to recommend when you sell to the business. Here are some common talent challenges that illustrate the differences (and who derives the most value):

Talent Metrics (HR): How many top sales reps left last quarter?
Talent Analytics (Business): Why do my top performing employees keep leaving?

Talent Metrics (HR): What is the average compensation for engineers across the organization?
Talent Analytics (Business): Why are our top software engineers dissatisfied even after we’ve given everyone a department-wide raise?

The blog post speaks most directly to big corporations, but with minor editing, we can shift the focus to learning, and it applies equally well to membership-based organizations.

Learning metrics measure tangible data. Learning analytics provide strategic insight and context that’s otherwise missing from the data.

What is your learning data telling you? Are you too focused on learning metrics (enrollments, completions, scores, etc.). While often easier to track, metrics aren’t as valuable as learning analytics.

Why aren’t members enrolling in this course they said they wanted? Why aren’t they completing the courses they begin? What are they really applying to their work?

I found the Webinar a good reminder that it’s always important to know why you’re tracking data—and to make sure what you’re tracking is telling you what matters.

Celisa

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