The forgetting curve in practice: what forgetting means for corporate training

The term forgetting curve shows up regularly in articles about training and learning, often paired with a graph that plunges steeply downward. From that, people conclude that employees forget most of their training within days. That is too simple a picture: the forgetting curve is interesting, but its practical application for corporate training needs more nuance.

A quick recap: what is the forgetting curve?

The forgetting curve refers to Hermann Ebbinghaus's research into the forgetting of learned information, and it formed an important basis for later memory research. But the commonly shared internet graphic should not be read as a universal prediction of the percentage of knowledge every employee forgets at any given moment: people learn different kinds of information under different circumstances. Here, we dig into what that actually means for corporate training.

Recognition versus recall

Say you open an old training document and see a procedure: you think, 'oh yes, I remember that'. That is recognition. But say you close the document and ask yourself which three steps you need to follow. Now you have to recall. Those two performances can differ quite a bit, and for knowledge retention, that independent recall is exactly what matters.

What does this mean for trainings?

The practical lesson from memory research is not 'everyone forgets their training'. The better lesson is: if knowledge needs to stay important, design moments where that knowledge gets retrieved and used again. That shifts the focus from fear of forgetting to actively maintaining knowledge.

The first weeks matter, but they are not magic

It makes sense to plan a follow-up activity shortly after a training, for example a first knowledge check in week 1, a follow-up in week 2, a new application in week 4, and a retention measurement in week 8 or 12. But there is no reason to pretend one specific schedule is scientifically optimal for every training: the right interval depends on the desired retention and the nature of the knowledge. Research on spacing supports the idea that optimal intervals depend on the desired retention period.

The forgetting curve isn't a problem you have to beat

A better way to look at it: forgetting is part of the learning process, and training design should account for that. You can retrieve, apply, connect, practise, test, and contextualise knowledge again, which keeps the learning process actively going instead of waiting for forgetting to strike.

What this means for HR

For HR and L&D, the important question is not 'was the training evaluated?', but 'what happens to the knowledge?' That can lead to a different set of KPIs: retention after 30 days, retention after 90 days, application, mistakes, behaviour, and real-world results, covered in more depth in 10 KPIs to measure knowledge retention.

An illustrative example

Say 100 employees take a compliance training. Right after the training, the average knowledge score is 90%, after 30 days it is 78%, after 60 days 74%, and after a short retention intervention 82%. These exact figures are just an illustrative example here, not a research result, but they do show what you can measure: not just whether someone learned, but how their knowledge develops over time.

And that creates a commercial opportunity

For training providers, this means a training does not necessarily have to end at the evaluation. You can offer a follow-up of training, retention programme, measurement, and reporting. That turns the service from a one-off event into a longer learning journey, exactly the model behind Stiqqo.

Conclusion

The forgetting curve should not be used as a marketing trick with spectacular percentages. The real insight is far more interesting: knowledge changes over time, and learning design can account for that change. That is why every training deserves an answer to the question: what happens once the training is over? That is where knowledge retention begins.