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  • Writer's pictureRob Wright

Is Your Learning Data Predictive?

There are a lot of training and learning activities out there today getting labeled as 'skills.' Here's the problem...

A majority of those learning activities are based on knowledge, not demonstrated skills and proficiency. How can you tell the difference? If the heart of the activity is to participate in a class, review content, or pass a quiz, that's knowledge data. If the heart of the activity is to practice and attempt to do the thing you've been trained on, that's skills data.

Why should operations and business leaders care?

First, because Bright's research has found that over 80% of learners who can pass quizzes don't have the underlying skills they actually to perform the task. They can pass a quiz on your software, but can't apply it in your actual systems. They can select the 3 components of your cancellation policy from a multiple choice quiz, but can't explain it in an understandable way to a customer. They can describe best practices in overcoming objections, but they can't sell.

You get the idea. Mislabeling knowledge data as skills data is a huge disservice to your company.

Second, because if you can actually generate skills data, you'll quickly find that it has a high predictive value of an associate's future performance, and therefore of your company's future performance. If an associate's handle time in practice is 7 minutes... guess what their handle time will be in production? If they can't overcome objections and de-escalate tense situations in practice, guess what will happen when they're on with a real customer or patient?

If you widen the aperture on this concept, this means that you can predict error rates and data accuracy *before* that big software roll-out. You can forecast whether training will increase CSAT *before* you take 10,000 calls. You can provide insights on whether that new hire cohort will hit their sales goals this month *before* they burn through those leads. Here are a few takeaways to help you and your team start moving towards a predictive skills data model:

  1. Assess your Learning Experiences: Don't just ask your LMS administrator whether your content is 'skills-tagged.' Ask them what the heart of the activities you're delivering are. If it's not a) at least 50% practice + simulation-based and b) trackable, you probably don't have much skills data.

  2. Ensure Practice is As Lifelike as Possible: As you start to introduce simulation and practice, bring the highest standards of quality to your experience designs. Learners will resist obviously-fake or out-of-touch scenarios. If you can put a veteran through the experience and even they think it's realistic, relevant, and valuable, then you're ready to deliver to a new employee.

  3. Align your Learning Skills Lexicon to Operations: To eventually use skills data to predict business performance, you need your data to be organized under the same performance and customer experience skills lexicon you use in your operations day-to-day. Bring Operations and L&D to the same table to make sure you're speaking the same language.

If you want to jump-start your organization's journey towards predictive skills data, be sure to reach out for more info here.


Discover what Bright can do for your business.

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