How to assess the impact of your L&D programs: a scientific approach

This is a complex question that many Human Resources Departments ask themselves. Indeed, one of the objectives of deploying a system is to have a satisfactory return on investment (KING). This, of course, means Measure its effectiveness but above all to conduct this evaluation in the most effective manner rigorous possible.

A resolutely scientific approach

The scientific community recommends the use of randomized controlled trials (Randomized Controlled Trial, RCT), simply because it's the best way to do things seriously.

A randomized controlled trial is a type of experimental protocol which aims to highlight a causal relationship between two variables. For example, a professional development program (i.e. the variable of interest) on the adoption of new managerial behaviors (i.e. the measured variable).

You have to keep in mind that we always start from a hypothesis. Therefore, in this example, we expect to see a positive effect of the variable of interest on the measured variable.

The randomized controlled trial uses a very rigorous research protocol whose objective is therefore to highlight an impact (or lack of impact...!) by minimizing potential experimentation biases. How rigorous is this type of protocol? And how does it work?

‍A... controlled test

A randomized controlled trial brings together several groups which are “variants” of the variable of interest. For example, if our variable of interest is the training system, we will have At the very least a group that follows him, called “experimental group”, and a band that doesn't follow him, called”control group“. These variants represent both modalities of the variable of interest.

The idea of this type of experimentation is to compare results of the variable measured between the different groups.

In our example, the implementation of new managerial rituals.

A... randomized trial

It is imperative that the assignment of participants to one of the two groups be done from random way.

And, to avoid some experimentation biases, individuals ideally don't know which of the groups they've been assigned to. We then speak of a study conducted in blinds.

It is necessary thatA certain number of participants be divided into each of the groups. The more important it is, the more we can consider that the characteristics of individuals in both groups are representative of the same reference population. That's what we call statistical equivalence, essential for subsequent analyses.

If we note, as expected, that the experimental group has better performances than the control group and that statistical equivalence is well respected, then we can conclude that this is due to the monitoring of the skills development program.

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The point to remember here is that the more the causes that can have an effect on our results are controlled, the more it is possible to talk about causal link between our variable of interest and our measured variable. In other words, the more rigorously the research protocol is designed, the more we will be able to interpret the results in terms of impact and therefore, in this context, to conclude that a device is effective.

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The company Fifty offers an eDoing tool that helps employees take action as part of training, transformation or post-training. Sensitive to the concept of experimentation and scientific proof, Fifty is testing the effectiveness of its eDoing solution by adopting a scientific approach. To measure the real impact of a device, talking about research is good; but conducting experiments is better! Stop Talking, Start Doing

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* depends on statistical power.

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