What’s the value of this measure?

Organizational learning and development has undergone significant change in recent decades. While organizations still carry out formal classroom-based learning, informal methods—like learning from a colleague in the flow of work—are increasingly vital to today’s L&D landscape. These changes, along with advances in technology, are driving a shift in the ways that HR functions track and measure learning.

The number of learning days per employee is a good example of a measure that may appear dated in light of recent advances in learning and learning measurement. However, this measure is far from obsolete and still has a lot of value for decision-making when used in the right way. In this article, we’ll show how this old measure has new value that makes it worth preserving on your HR dashboard.

See more: 3 strategies to protect your employee learning budget for 2025

Breaking down number of learning days

The number of learning days per employee is a common and longstanding L&D measure that tracks the number of days (or, for some organizations, hours) dedicated to formal learning. There are several reasons why this measure has been a mainstay on many HR dashboards:

• It’s relatively easy to track.
• It’s easily understood by a variety of stakeholders (e.g., candidates, employees, managers, executives and investors).
• It has a place in many annual financial and human capital reports as well as voluntary reporting frameworks like the Workforce Disclosure Initiative.
• Because it’s so common, it is easy to find benchmarking peers (i.e., organizations that are similar in terms of factors like revenue, headcount, industry, region and more).

Data from the American Productivity & Quality Center (APQC) shows that organizations provide a median of six learning days per employee. Organizations at the 75th percentile of our dataset provide the most learning days with eight or more, while those at the 25th percentile provide four or fewer.

Traditional measure, new limitations

Despite its widespread use, a lot of HR leaders are starting to ask if the number of learning days is still a relevant and useful measure. There are two big reasons why it looks increasingly dated:

1. It does not capture a growing portion of the learning that is taking place in organizations today.
2. Changing technology and measurement capabilities mean that more sophisticated assessments of learning performance are now available.

We address each of these concerns in more detail below.

Demand for informal learning is growing

While many organizations still use formal learning, informal learning—which can include everything from knowledge sharing between colleagues to observation, discussion boards, collaborative work and much more—is a more practical and effective option in many scenarios. There are several reasons why informal learning is often a better fit for today’s learning needs:

• Learning needs are unpredictable and fast-changing, so there is less time to meet them when they arise.
• The focus or topics for learning are more frequently novel. For example, existing content or expertise related to AI may not be available for formal learning in some organizations, but people can teach and mentor each other.
• Learning capacity is limited. Lean workforces mean there is often little slack for taking time away from work to learn. Informal learning can happen directly in the flow of work in many cases.
• Learners expect a degree of personalization and customization. Learners who experience these in their other interactions with HR, as well as in their daily life as consumers, are looking for the same from their learning experiences.

More broadly, compared to formal learning, informal learning can be a more practical way of delivering learning that is just in time (i.e., doesn’t need lead time), in just the right amount (for attention and memorability) and in just the right way (for each learner’s preferred style).

Measurement capabilities are growing more sophisticated

As demand for informal learning continues to increase, a similar expansion is taking place in terms of the ability to track and measure informal learning. For example, online knowledge repositories, expertise location systems and organizational social networks can all capture activities that are indicative of informal learning.

On its own, the number of learning days does not provide as holistic a picture of learning as is now available in many organizations. Input or activity measures (like the number of learning days) can be important early indicators of whether you are dedicating enough time to meet your learning needs. But input or activity measures come with limitations: On their own, they don’t provide much insight into learning efficiency or effectiveness.

For example, the number of learning days measure doesn’t tell you whether those days were spent learning what the organization or employee needs, what methods were used to learn, who did the learning or what topics were covered. It doesn’t tell you whether learning actually took place, whether it was delivered in ways that make the best use of learners’ time or whether learning has been applied on the job to improve performance. Given improvements in data quality, consistency, integration and accessibility, it’s now possible to explore questions like these.

Old measure, new value

There is still value in the traditional number of learning days measure. In fact, rather than rendering this measure obsolete, advances in technology, data and analytics allow us to do more with this measure than ever. With relative ease, HR leaders can now use the number of learning days in conjunction with a variety of “new” outcome measures and apply more sophisticated analytics to generate further insights.

Adding ‘new’ measures

Increasingly, HR and workforce technologies are being integrated or replaced with new, fully integrated systems. This, in turn, facilitates the collection of consistent data that can be connected in new ways. For example, it’s now a lot easier for HR leaders to connect an input measure like the number of learning days to an outcome measure that sits outside the learning system, such as the percentage change in employee performance ratings. Together, these datapoints can better inform decisions than they would separately.

Outcome measures supply key data points that allow us to put the number of learning days in context. Without these measures, we don’t really know if organizations at the 75th percentile (with eight learning days per year) are really doing better than those at the 25th percentile (with only four learning days). It could actually be the case that an organization with only four learning days is highly efficient and more effective than those that offer twice the number of learning days.

Applying analytics

Analytics tools and technology not only provide the ability to combine the number of learning days with a wide variety of outcome measures but can also provide deeper insight about these measures to answer L&D questions aimed at improving learning efficiency and effectiveness.

For example, analytics can help you identify the ideal number of learning days for your organization, whether your goal is to improve performance ratings, increase the number of internal promotions, or meet employee and retention targets. While it’s useful to be able to benchmark the number of learning days you offer relative to your talent competitors, it’s also useful (perhaps even more so) to understand how many learning days you need to keep your high performers from leaving to work for a competitor.

Examples of evidence-based decisions using the number of learning days measure

Through our research, APQC has consistently found that evidence-based decision-making is a key HR objective. In combination with the right outcome measures and analytics, the number of learning days can enable L&D professionals and HR more broadly to provide data-driven decision-making support to the business. This can be especially valuable as organizations work to drive continuous improvement and transformation in HR and beyond.

Below are some examples of scenarios and decisions that can be supported by using the learning days measure in conjunction with outcome measures and analytics. For each scenario/decision, we provide questions that you can ask using data and analytics to push deeper.

• Our learning budget has been cut, and we need to pare down our learning curriculum. Where can we make cuts that will have the least impact on overall learning outcomes? Which courses have the highest average number of learning hours per employee and the lowest positive change in average performance rating post completion?
• Our turnover rate for high-performing, mid-career employees has been steadily increasing. What could we do to reverse this trend? Is there a difference in the average number of learning days for high performers who leave versus high performers who stay? On average, do high performers who leave have a lower average number of learning days? Alternatively, do they have a higher number of learning days, but a longer duration since their last promotion?
• We need to speed up time to productivity. Would more internal hiring (moving or promoting existing employees) and less external hiring help us reach this objective? Do internal hires need fewer learning days to reach full productivity? Are they equally or more satisfied with their onboarding experience, and do they have the same or better performance ratings at one year performing the role?
• Managers and employees both say that it is hard for them to get away from work to attend learning courses and programs. Can we find ways to reduce the amount of time employees are away from work to learn without negatively impacting learning outcomes? Do employees using adaptive learning technologies need fewer hours or learning days to complete the same learning objectives (courses or programs)? Do they also express satisfaction with their learning experience and demonstrate learning acquisition on post-course assessments?
• Our pilot of a new knowledge sharing, expertise location and collaboration platform is wrapping up. Should we roll it out more broadly within our organization? Do employees who use the new system the most use fewer formal learning days? Are their learning outcomes as good or better compared to employees with lower system usage and higher learning days?

Key takeaways

As L&D continues to evolve, HR and talent leaders may need to look to traditional measures like the number of learning days per employee in new ways to continue providing valuable insights. Far from being obsolete, these measures—combined with other measures and analytics—can support HR in meeting the demand for data-driven decision-making on behalf of the business. Beyond L&D, it’s worth asking where you can use analytics and outcome measures to breathe new life into old measures as the HR landscape continues to evolve.

Data in this content was accurate at the time of publication. For the most current data, visit www.apqc.org.