In the third post of our series on “Training Analytics”, we discuss the importance of individualized analyses, an essential step to assess team member performance and guide the training development program.
In the first post of this series, “What is analytics in corporate training,” we present the general concept of how data analysis can positively impact Learning and Development programs. The four basic steps of this process are as follows: (1) Establishing a correlation between KPIs, tasks, and skills; (2) Individualized Analyses; (3) Optimized Instructional Actions; and (4) The Moment of Truth.
Following our schedule, we arrive at the post that will detail the importance of “Individualized Analyses,” central for an accurate diagnosis of the current stage of the workforce. After all, it is possible to assess the team’s performance and determine which training sessions each person needs using the correlations explained in the previous post.
The process is straightforward and contains no surprises. There are, however, some pitfalls to consider.
In practice, after you have assembled the neural map, it is time to comprehend the current state of affairs in terms of team performance, analyzing how each person’s (or group of people’s) performance, and the levels of their key performance indicators (KPIs).
After building the neural map and establishing the correlations between KPIs, tasks, and skills, it is time to radiograph how the teams are performing and generating results for the organization.
It is a process that, ideally, should include many research mechanisms (control group, market) as well as statistical analysis. This ensures that we have a fair, isonomy-based study from start to finish. Your main goal should be to build a reliable database.
The first point of attention (and trap to avoid) is that it is pointless to compare a 2010 indicator with one from 2020, for example. This analysis as a whole must be done carefully to retrieve the most up-to-date and reliable data possible.
A common mistake is “wanting” to find data by making educated guesses, distorting reality, and compromising the analysis. Just as it is not possible to compare indicators from distant eras, it is also not possible to establish a parallel between the performance of a team during a special period (promotional campaign, for example) and a regular period or even different regions and markets. In a context like this, countless variables can impact the results at any given time. Therefore, isolating these variables is crucial.
T&D Analytics: contextualizing the performance of each individual
L&D Analytics: contextualizing the performance of each individual
In addition to avoiding any type of data distortion, it is essential to always consider the context in which those indicators were generated, as this will increase the reliability of the data obtained.
The classic disconnection between reality and training must be avoided at all costs.
For this, the individualized analysis must be just that: a detailed study of each KPI that has to be improved for each individual (or group of individuals) in the team. This is always in the context of experience, which is usually quite different from the training rooms, complete with projection screens and air conditioning.
The real world has additional challenges that must be addressed in this analysis, or else training as a whole will be contaminated. And we only obtain this information if we talk to people, leaders, and followers.
L&D Analytics: selecting training
You can define the training required for each individual based on a careful and isonomic individualized analysis. The existing custom learning solutions, combined with current needs, are a good starting point. The goal now is to connect the training to skills that need to be improved.
One last point to highlight, in the form of a question: should we train people who have good learning analytics? Our answer is no.
The justification for this is simple: high-performance professionals, who are performing well and delivering great results, do not need to devote time to that will target areas of improvement that they do not need. These professionals must be challenged, prepared for new roles, promotions, and so on.
That is what the company’s leaders should be considering.
In other words, allow training to focus on KPIs that are not good, resulting in a general improvement in individual performance. If such KPIs were highlighted, it is because they are strategic and must be worked on. Remember this the next time someone tells you to focus solely on your “strengths” and ignore your “weaknesses.”
As a reminder, this entire process can, of course, be automated (depending on the volume of people involved in the training – because it is natural that there are many similarities in profile in larger groups). In this case, the next step of the Training Analytics process, called “Optimized Instructional Actions,” will be essential for our assertiveness and speed.