Trouble Tracking Proficiency?

“Understanding an employee’s proficiency and engagement in a learning program is emerging as a far more effective measure of whether training investments have paid off, or where knowledge and skills gaps still exist.” – Training Journal

One of the things we hear most often from our partners is that they struggle with how to quantify the performance of their programs. They have a hard time determining how proficient their learners are post-training, and anticipating how accurately they’ll apply what they’ve learned back on the job.

Is that something you’re organization’s experiencing as well?

Here’s the thing: today’s L&D teams are up against some pretty serious challenges. Not only do they often feel overwhelmed by their training to-do lists, but they’re also battling resource and technology constraints that hem in their ability to measure programs as effectively as possible. For example, most L&D teams don’t have access to dedicated data scientists who can pluck value out of raw learning and performance data. This means, they have to rely on the data from:

• Their own analysis of pre and post assessments
• Post-learning satisfaction surveys
• Legacy technologies that are not sophisticated enough to evaluate learning at the proficiency level

We get it. It’s a real catch 22.

But, the fact remains that proficiency is a pretty important metric to track. There are loads of reasons for this. It makes it easier to identify and remediate knowledge gaps. It helps L&D define where they need to focus additional training resources that will lead to real word gains in terms of business objectives. And perhaps just as importantly, it helps L&D quantifiably demonstrate the ROI of their programs to the c-suite

So the question becomes: how can you evaluate proficiency without further stressing your L&D team?

Based on our experiences, we think the answer is lies in choosing a technology partner that can help move your analytics across the proficiency goal line. Here are four things that learning departments can do to improve their ability to measure proficiency:

• Built-In Data Science – Engage with eLearning technology partners that have built-in data science capabilities, thus removing the burden of data analysis from the shoulders of L&D
• AI-Powered Technologies – Choose technologies that leverage AI and machine learning to determine the depth and degree of mastery and predict future knowledge application by mapping and evaluating learner performance AND behavioral metrics
• Confidence Builders – Look for solutions that not only measure learner confidence but actually build confidence – a key indicator of proficiency
• Fully Integrate Employee Proficiency Data – Find a technology solution that can leverage collected external performance data to complete a full feedback loop with exponential results

By integrating a learning technology that delivers on the points above, organizations will have an easier time building proficient workforces and measuring proficiency in a quantifiable way. This will help L&D reach its highest callings – mastery, confidence and application – and ensure they have a seat at the table with the c-suite.

Fulcrum Labs moves organizations beyond traditional training metrics and allows them to delve more deeply into the knowledge, skills and proficiencies of their workforce.

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