There’s no point in training employees if you have no idea how it affects them. Imagine investing significant time and resources into eLearning initiatives, only to find that they have little or no effect on employee performance.
Or worse, they aren’t even what employees need, and they have no interest in the training.
To ensure corporate employees have what they need, selecting the right training metrics can make all the difference in ensuring that your efforts translate into tangible improvements. These metrics aren’t mere numbers; they’re the compass that guides you toward achieving greater efficiency, productivity, and satisfaction among your workforce.
This post focuses on various training metrics and offers a list of some of the most helpful indicators to assess the effectiveness of digital training strategies. While butts in seats isn’t ideal, for some training it does offer valuable information and should be a consideration.
The right metrics helps direct training efforts into the most impactful for the business.
The various options in this post will help you choose some of the best options for highlighting the value of training. From tracking completion rates to evaluating knowledge retention and skill application, these metrics are valuable in directing training to the most effective areas.
Whether you’re an HR manager, a learning and development professional, or a corporate leader eager to harness the power of data, this post will equip you with the insights needed to measure and enhance your training outcomes.
Before jumping into some of the essential training metrics, it’s important to understand why these metrics are important in the first place. Let’s start there and then jump into the various metrics that should be considered.
The Importance of Training Metrics in Digital Learning
Without reliable training metrics in place, organizations operate in the dark, unable to discern whether the content resonates, skills are being acquired, or performance is truly improving. It’s not just about training; it’s about how well new employees can use tools or current employees can use new tools.
Training metrics serve as objective indicators that translate learning experiences into measurable outcomes. Metrics provide clarity on how well training aligns with business goals. By tracking the right data points, you can pinpoint strengths, expose gaps, and allocate resources more strategically.
It’s about how well new employees can use tools or current employees can use new tools.
Using metrics to track training is a great way to demonstrate the value of training and show its real business purpose, rather than simply saying it’s important.
Metrics make it essential that training is accountable and continually strives to improve. When metrics are used effectively, stakeholders, from HR managers to senior executives, gain visibility into the return on digital training investments.
It also helps direct resources into more valuable ways of training employees, providing them with what they need. That will make employees feel more supported in the right way by evidence-based training rather than what feels good.
This systematic approach shifts training from a one-off exercise focused on getting butts in seats to an iterative cycle of anlysis, design, delivery, evaluation, and refinement. Ultimately, by recognizing the importance of training metrics in digital learning, organizations will ensure that every dollar spent on upskilling yields tangible benefits in productivity, engagement, and overall business performance.
But what should the business focus on for training? Surely you can’t just throw all the training options against the wall and expect something to stick. There’s value in only some things and waste in others.
Key Performance Indicators (KPIs) for Training Success
Training has to start somewhere to find the essential metrics for measuring digital learning success. The best place to start is by defining key performance indicators (KPIs) for training itself. Yes, the business has its KPIs, but training must also have its own that help the business’s KPIs.
KPIs highlight the most critical aspects of your digital learning strategy and allow you to measure progress against predefined targets that are directly related to the business. While there are dozens of potential KPIs, focusing on a concise set, such as completion rate, assessment scores, and time to competency, ensures clarity and prevents throwing all training types against the wall, hoping something will be effective.
Choosing the right KPIs begins with aligning them to your organization’s or project’s objectives, whether that’s improving sales, reducing error rates, or enhancing customer satisfaction. If it’s a new software launch, then it could be that a basic level of information is provided, and anything beyond that has strategic KPIs planned for how training will help employees.
What is training supposed to impact in the business?
Once selected, these KPIs become the basis for dashboard reporting, trend analysis, and performance reviews. By regularly reviewing KPIs, learning and development teams can identify which modules drive the greatest returns, which require updates, and who may need additional support.
The end goal is not simply to report numbers, but to derive actionable insights that power ongoing optimization of your digital training initiatives and solidify the link between learning investments and business outcomes.
The following are some key considerations to look for and what can be attached to the KPI of a project to drive effective training. Some are more basic metrics that have little impact on employees, while others are more powerful.
Tracking Completion Rates
Completion rate is the most straightforward training metric and, of course, one of the most overused. If anything, this should be used as a secondary metric, as it is merely a vanity metric that holds no value. Well, it’s meaningless if the training is required or heavily encouraged.
The completion rate is the percentage enrolled who finish a course or module. If training is optional, a high completion rate could indicate that the content is relevant and accessible. If optional, a low completion rate may indicate technical barriers, content overload, or a lack of need.
Even if completion is required, there’s still something this could tell you. If completion rates are high and coincide with employees’ proficiency in using the tool, the training has definitely played a role in that. The data can be broken down into various cohorts to see who completed the training and how that compares to employee preparedness to accomplish goals.
Are the branches with the most training completions also the ones that perform the best?
If high completion rates coincide with high employee preparedness, use some tools to increase training completion. This could be better communication, more frequent communication, microlearning “messages” that communicate important points, or even simple reminders.
Sometimes, automated reminders, gamification, and social learning features can also bolster motivation to complete training for those low-completion cohorts. By coupling completion data with other metrics, such as assessment scores and feedback comments, you can build a comprehensive picture of progress and pinpoint the exact roadblocks employees are experiencing.
Assessing Knowledge Retention Levels
Measuring knowledge retention gauges how much of the content has been internalized and can be recalled or applied over time. This training metric is helpful for some content but not always necessary.
When would it not be necessary? I’m glad you asked: When retaining knowledge isn’t necessary. The goal of training isn’t always that employees remember everything; sometimes it’s not necessary to remember anything at all. That’s why there are many types of performance support, which are perfect for helping employees do their work without having to remember unnecessary details.
But when knowledge retention is important, it’s essential to measure this training metric. That’s because it directly influences an employee’s ability to perform tasks accurately and efficiently when they have to perform it often.
Retention can be assessed through quizzes, periodic refreshers, and spaced repetition exercises embedded within your digital learning platform.
Employees must know what they must know only and where they can reference the rest.
When retention is essential, implementing follow-up assessments at intervals, such as 30, 60, or 90 days post-training, helps determine how well employees retain information. It also helps uncover where reinforcement might be needed after training.
Analyzing retention data alongside completion rates enables you to distinguish between individuals who complete courses but quickly forget the content and those who genuinely master the concepts. This insight informs the development of supplementary resources, such as job aids and interactive simulations, to enhance long-term retention and proficiency.
Just keep in mind that knowledge retention isn’t always the goal of training. Sometimes it’s simply to build the base knowledge so employees are familiar with something and know where to go to find more information. Always know when to assess knowledge retention and when it’s a metric you can disregard.
Measuring Skill Application and Practical Proficiency
Assessing completion and knowledge alone does not guarantee on-the-job competence. Skill application metrics indicate whether employees can effectively translate learned concepts into practical, real-world actions.
For software training using digital learning strategies, scenario-based simulations can be used to assess employees. It’s possible to even use testing out as a strategy to allow tech-savvy employees or those familiar with the topic not to waste their time.
Tracking performance in training offers a more accurate picture of practical proficiency. Evaluating skill application requires clear rubrics and performance benchmarks tied to specific job functions. For instance, a sales training program might measure call-handling effectiveness, objection resolution, and upselling success rates in simulated calls.
Can they apply the skills they learned and are they as proficient as they need to be?
By knowing when skills can be applied and when employees become proficient, organizations can pinpoint areas where people excel or struggle. When it’s essential that employees can apply what they’ve learned and impact extends beyond simple performance, measure their skill application and practical proficiency.
If the cost is too high and the benefit isn’t high enough, it may not be necessary to use this level of metric tracking. Sometimes employees need the basics to get started, but the impact of not knowing it isn’t great enough to justify the implementation. There’s a fine balance between needing this level of metric and the benefits it will provide.
Evaluating Training Impact on Job Performance
Ultimately, the true value of digital training lies in its impact on job performance. Can employees perform their job more effectively after training than they could before?
Measuring this impact involves comparing key business metrics, such as productivity rates, error frequency, and customer satisfaction, before and after training interventions. By establishing baseline performance data, you can attribute subsequent improvements directly to training and quantify return.
For greater precision, consider control groups and staggered rollout plans that allow you to isolate the effects of training from other variables. Sales effectiveness is a great place to apply this metric and figure out if the training has an impact. For technical training, the test should likely be applied further upstream than training to ensure the technical change will benefit employees or the bottom line.
If employees are performing their job better after training then that’s a huge success.
There are many ways to figure out if training has positively impacted the job. Case studies, manager observations, and performance reviews provide qualitative context, illustrating how employees apply new skills in their daily work.
When combined with quantitative data, these insights enable you to demonstrate the contribution of training to strategic goals, justify further investment, and expand digital learning offerings when there’s a clear benefit.
Feedback and Surveys
While you can’t make any decisions for training based solely on feedback and surveys, the information is still valuable. People aren’t the best judges of whether they learned or not, but they can tell you what they thought of the content. That’s enough to at least make some adjustments based on that information, though nothing too impactful will come of it.
Feedback and surveys are metrics that capture employee perceptions and can help identify areas for improvement. Post-training surveys gather immediate responses on content relevancy, effectiveness, and user experience. Periodic pulse surveys and focus groups can probe deeper into long-term attitudes and suggestions for improvement.
What people think is an important part of training metrics.
Analyzing survey data alongside other training metrics illuminates gaps between learning expectations and actual outcomes. Qualitative feedback can uncover usability issues, content complexity, or missed topic areas that quantitative data alone might overlook.
By systematically aggregating and acting on this feedback, you will foster a learning culture that drives continuous improvements. When this feedback is implemented, it will almost undoubtedly enhance satisfaction, engagement, and ultimately, training success.
Implementing Data-Driven Decisions for Training Optimization
Data-driven decision-making is essential to training that makes a difference. For training that isn’t tied to a new software tool, making it data-driven is vital; otherwise, there’s no real point to it.
By synthesizing insights from completion rates, knowledge retention, skill application, performance impact, and feedback, you create a practical approach to training that has real business purpose. Advanced analytics tools, such as predictive models and learning dashboards, can show outcomes and highlight high-impact methods for improving training.
Armed with robust training metrics, L&D professionals can prioritize content updates, personalize learning pathways, and allocate resources to areas with the greatest return. Regularly reviewing data points in stakeholder meetings ensures alignment with evolving business objectives. This ensures that training investments are being made in the correct places, resulting in positive business impacts.
Ultimately, embedding data-driven practices into your digital training strategy paves the way for sustained performance gains and lasting organizational success.
Wrap Up
Selecting and tracking the right training metrics is essential for demonstrating the impact of digital training. From completion rates and retention assessments to real-world skill application and performance gains, each metric offers a unique lens on program effectiveness.
By adopting a holistic, data-driven approach when it makes sense and continuously refining your strategy based on insights, you can ensure that training delivers the right value to the business. It should provide value, empower employees, and drive sustainable business performance.
Not every project we work on requires metrics to measure, but there’s always an underlying reason for training. That could be that employees are required to learn something before being given access, or they need a basic understanding before access to software is provided.
Whatever the need, we’re skilled at building technical training that has a positive impact on employees. Schedule a free consultation, and we’ll discuss how we can help with training and identifying the right metrics to measure digital learning success.