ROI or ROE to evaluate your training courses?
Between ROI (Return On Investment), which promises reassuring figures, and ROE (Return On Expectations), which aims to capture qualitative transformation, training managers juggle metrics that are often insufficient to justify their expenses. What if cognitive science was the key to measuring what really matters from a decision-making perspective?
Traditional methods for evaluating the return on investment in training have major shortcomings. They promise a clarity that is illusory in the face of the complexity of employee learning.
The traditional ROI calculation formula (benefits - costs/costs × 100) seems clear in theory to assess performance. In practice, it faces the impossibility of isolating the direct effect of training on the overall performance of society.
Concrete example : A financial services company invested €80,000 in business training and saw an increase in turnover of €300,000 the following quarter. But how do you isolate the impact of training from other factors such as seasonality, marketing actions or market trends? This difficulty makes calculating traditional ROI often approximate.
Cognitive science research shows that the impact of learning often takes place over the long term, making any attempt to measure ROI immediately and purely financially obsolete.
Post-training questionnaires, the famous “happy sheets” used in the first stage of evaluation, are perhaps the most widespread and the least relevant metric. Studies show an almost non-existent correlation between the immediate satisfaction of employees and the real impact on their skills.
This phenomenon is explained by what cognitive sciences call the “illusion of control”: the subjective feeling of understanding a subject does not in any way indicate the ability to apply it concretely in professions.
Learners can be perfectly satisfied with a training course without having really improved in their mastery of the subject, which is a problem for sponsors and investors.
The completion rate, the time spent on the platform or the number of modules consulted are all indicators that measure activity without guaranteeing real effectiveness for the training function.
An employee can spend hours on a LMS traditional without this resulting in a real transformation of its professional practices or an improvement in the performance ratio.
Commitment does not guarantee learning, just as reading a manual does not guarantee the acquisition of a skill that can be measured by ROI.
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Faced with the limitations of traditional methods, two complementary concepts are emerging to assess the real impact of your training projects.
The ROI of training is calculated according to the formula for the performance ratio: (Financial gains generated - Training costs)/Training costs × 100.
Its main advantage lies in its ability to translate the training impact into language that can be directly understood by CFOs and shareholders.
It makes it possible to compare different investments on a common basis, facilitating annual budgetary decisions and the financial profitability of projects.
In the context of training, costs include not only direct costs (purchase of the solution, average trainer cost) but also indirect costs (time spent in training by learners).
Gains may include improved productivity, reduced losses, or increased sales due to training, with accurate tracking of these elements.
Methodologies such as that of Donald Kirkpatrick and Jack Phillips propose to isolate the effect of training through triangulation and comparative analysis techniques, thus facilitating the calculation of ROI.
Financial ROI fails to capture intangible benefits such as improving the social climate or retaining talent, which are essential to the overall level of risk.
It tends to favor training with a short-term impact at the expense of profound transformations that require more time to be reflected in the net results.
The real value of a competence for the company goes far beyond its immediate monetary translation.
ROE focuses on achieving expectations defined in advance rather than on a financial calculation after the fact, which is fundamentally different from the traditional ROI approach.
This ROE method, developed in response to the limits of return on investment, places transformation objectives at the center of the evaluation system.
It is part of a strategic vision where training is a lever for the development of human equity rather than a simple cost center.
Unlike the ROI that comes after training, the design of training with a ROE approach begins even before the definition of the learning path.
It requires a precise definition of the expectations of stakeholders: learners, managers, management and end customers in order to better assess the expected performance.
This approach makes it possible to align training with measurable goals that are truly relevant to the organization and its human assets.
The return on expectations does not replace the return on investment but complements it by integrating qualitative dimensions that are essential to any informed decision making.
By clearly defining expectations, it paradoxically facilitates subsequent quantitative measurement to calculate ROI more accurately.
The combined approach allows for a more complete and nuanced assessment of the training impact, both from a financial and a skills development.
Beyond debates about return on equity and return on investment, cognitive science offers a robust conceptual framework for evaluating the real effectiveness of training courses.
Studies show that without active review, we lose up to 75% of new information in just 48 hours, and up to 90% after a week. A fact that is ignored in traditional calculations.
A relevant indicator is therefore not immediate knowledge but long-term retention, measurable by tests spaced out over time to better interpret the results.
Educational formats that incorporate techniques such as spacing, active retrieval, and immediate feedback maximize this retention, thus ensuring better benefits for the organization.
The ability to apply knowledge in a new context is the true indicator of successful learning to achieve business goals.
Cognitive science distinguishes declarative knowledge (“knowing that”) from procedural knowledge (“knowing how”), the latter being critical for field impact and team management.
A relevant assessment measures the ability to transfer learning to authentic professional situations, thus giving an important part to the real context.
The ultimate measure of impact lies in the observable and lasting modification of professional behavior, a real difference between effective training and a simple theoretical exercise.
This behavioral transformation is only possible with learning that goes beyond the illusion of mastery to create automations rooted in daily practice.
Cognitive science makes it possible to identify and measure these micro-changes which, combined, produce a major change in the performance of employees.
Didask's educational AI analyzes each learner interaction to accurately identify the bottlenecks and progress made in their learning journey.
This granularity makes it possible to go beyond global measurements to fully understand the learning mechanisms at work, thus offering a clear view on the effectiveness of training.
The data collected reveals not only whether the objective has been achieved, but also how it has been achieved, paving the way for continuous optimizations in the internal rate of return on training.
Machine learning algorithms identify patterns of success and failure, making it possible to predict the likely impact of training on the various jobs concerned.
These predictions make it possible to adjust courses in real time to maximize educational efficiency and return on investment, thus meeting the demand for constant optimization.
The data-driven approach replaces hunches with decisions based on empirical evidence, a key factor for truly effective and profitable training.
The automatic personalization of courses according to the specific needs of each learner maximizes the efficiency of the training, generating a better cost/benefit ratio.
This adaptation considerably reduces the time required to develop skills, generating a higher ROI than conventional standardized approaches in the field of skills real estate investment.
Going from theory to practice requires a structured methodology and tools adapted to your specific business context.
Start by identifying the concrete behaviors that training should change in the field, similar to what Kirkpatrick's first level of assessment offers.
Involve all stakeholders (learners, managers, customers) in defining these objectives to ensure their relevance and alignment with the expectations of the sponsors.
Formulate SMART indicators (Specific, Measurable, Achievable, Achievable, Realistic, Time-Defined) for each objective, thus facilitating accurate monitoring of progress.
Go beyond standard metrics to create a balanced dashboard that integrates quantitative and qualitative indicators that match your specific project.
Distinguish between process indicators (commitment, satisfaction) and impact indicators (field application, performance) to better appreciate the different facets of ROE.
Choose a limited number of truly significant indicators rather than a multitude of superficial data that complicate the interpretation of the results.
ROI or ROE? The real question is not to choose between these two approaches but to transcend them to measure what really matters: the effective transformation of professional behaviors and its impact on business results. Cognitive sciences now offer us the keys to understand and optimize human learning mechanisms, while educational artificial intelligence makes it possible to operationalize this knowledge on a large scale.
At Didask, we have developed a unique approach combining expertise in cognitive science and cutting-edge technology to ensure not only a measurable return on investment, but a real transformation of skills. No longer content yourself with courses whose impact remains unclear or questionable. Adopt an approach based on scientific evidence to maximize every euro invested in the development of your talents and thus improve the overall performance of your human capital.
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