Done right, learning and development (L&D) can be a strategic driver of employee productivity, agility, internal mobility and, ultimately, business growth. While these benefits are widely observed among HR pros, quantifying this impact still poses a challenge to many. As with any business function, it’s essential to evaluate whether the resources, time and effort invested in employee training and education are yielding the desired outcomes.
By understanding how to measure learning outcomes, you will be equipped with the knowledge to optimize your L&D strategy, boost employee performance and drive overall organizational success.
Let's take a closer look at what metrics matter most and what methodologies yield the most reliable results.
How to measure training effectiveness
Measuring training effectiveness requires more than one data point. For meaningful insights, you’ll need to gather multiple types of data and take great care in your analysis. Remember, you can make numbers say anything. But if you want something useful, pay close attention to your methodology to ensure your conclusions accurately reflect program results.
Let’s take a look at the quantitative (statistics-based) and qualitative (less measurable) data to consider in your analysis.
Quantitative data points provide hard numbers for:
- Program completion rates
- Employee learner grades and scores
- Program engagement
- Program ROI
Qualitative data points attempt to assess less measurable, but highly important factors in L&D success, such as:
- Employee satisfaction: How has the experience of learning affected employee satisfaction?
- Employee performance: Has learning translated into improved performance or productivity?
- Employee learning capacity: Has the employee excelled in their learning program and would they be a good candidate for additional education or leadership training?
- Skills gap coverage: Are the company’s skills gaps being addressed by employee learning?
- Real-world application of skills: Does employee learning extend beyond theoretical concepts?
Whether it’s a training course, on-the-job learning, a degree program or some other form of skill-building, both quantitative and qualitative data should be evaluated regardless of how the learning initiative is structured.
Data collection methods for measuring training
Collecting quantitative data
Most modern training and education solutions come with pre-built dashboards that automate data collection and synthesize all of your key quantitative metrics, providing snapshots of what’s happening across your L&D programs. Review these metrics quarterly for trends or comparative insights among programs. This exercise can not only help you optimize your program, but it can also help make the case to continue your L&D efforts or expand them.
You can also pull data from other areas within the company to inform or confirm your findings, but be mindful of drawing conclusions around cause and effect. For example, improved retention rates can be a key indicator of learning effectiveness, but they are not solely affected by L&D. In this case, there’s a correlation between the two data sets but no clear cause and effect.
Collecting qualitative data
Drawing valid conclusions from qualitative data can be all the more challenging. While gathering this data typically requires a more creative approach, qualitative insights can help you pinpoint some of the most important information you need to know to ensure training success.
For insight into program structure, use your regular employee surveys to delve into preferences between on-the-job training vs workforce education, the UX of your training software, accessibility of content, the applicability of materials, etc, and then cross-reference those results with the relevant quantitative data.
Employee goals and performance
Insights on employee performance can be even more nebulous. Just because an employee attends a class or completes a certification doesn’t guarantee an improvement in their performance. If they’re not hitting performance goals, the issue may be with the individual, but keep a close eye for more systemic issues within your training itself.
Leverage manager/direct report discussions to go directly to the source — asking employees themselves if they’ve noticed an improvement in their skills or productivity. Seek out manager feedback as well. Have they noticed their direct reports using new skills or showing improvement? Are they taking on higher-level responsibilities or do they seem more engaged?
Frameworks for measuring training effectiveness
There are countless different methodologies that exist for measuring training and learning. Here are three that stand out as the most credible, widely used approaches:
Kirkpatrick four-level evaluation model
The Kirkpatrick model looks to answer whether a learning program has delivered its desired outcomes for defined KPIs. It does so by looking at whether employees have found the program relevant and engaging, acquired the intended knowledge and skills (including soft skills like confidence and attitude) and applied what they learn to their job.
The Phillips model bases its analyses on a similar set of criteria to Kirkpatrick, but adds a crucial fifth piece to learning evaluation: ROI, where business impact is translated into financial returns. Leadership often wants to know if their investment in your learning program is worth the money. Phillips helps answer this.
Anderson model of learning evaluation
Like the Phillips model, the Anderson model wants to improve upon the industry-standard Kirkpatrick model. It does so most notably by delineating between the quality of the training materials and the delivery of the training itself, making it easier to identify the fault line when an L&D program fails.
The power of data-driven training and development
Consistently tracking metrics allows you to keep your finger on the pulse of your L&D program impact and then react quickly to downturns or unexpected outcomes. Also, you can more easily identify opportunities for improvement by closely watching trends in your findings.
By pulling from a wide variety of data types and sources, you’re well on your way to reliable data sets and conclusions, along with a clear picture of the effectiveness of your L&D strategy.