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Establishing a correlation between KPIs, tasks, and skills

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The first step in applying the principles of Analytics in T&D is to determine the skills needed to accomplish tasks that impact Key Performance Indicators (KPIs).

Continuing the series of posts started in “What is analytics in corporate training?,” in which we present the full potential of this approach and a summary of the four steps that make up the Reframe Learning way of putting it into practice. It is now time to discuss the first step in this journey: determining the connections between KPIs, tasks, and skills.

This is the stage where you create a “neural map” or “mental map,” which acts as a complete guide for everything that you will do throughout the training process.

From a conceptual standpoint, it is a basic and logical process, but it is incredibly time-consuming and difficult due to the large amount of data and variables that must be examined and processed. Before effectively drawing up the correlations between KPIs, tasks, skills, and training, always starting from a specific function, it is important to unravel each of these aspects, starting with the job description itself.

The term “unraveling” refers to analyzing and separating all the information related to the work performed by each individual in that role until we get to the task.

Each position and function in an organizational structure is made up of a set of tasks that have an impact on the company’s results (KPIs). In an ideal scenario, when the demand for training is driven by objective and measurable data (again, KPIs), it is clear that the next steps can only be addressed after each task has been identified. As well as positively impact these indicators.

After identifying each task, it is necessary to link each of them to the set of KSA (Knowledge, Skills, and Attitudes) necessary to perform. The question to be asked here is: what abilities do people require to perform such tasks well?

Naturally, the next step is to link these skills to the training, determining which program will strengthen these skills in a way that will positively impact how those duties are carried out.

In essence, the relationship we share is as follows:

As a result, we have a causal relationship. This relationship allows us to claim, that if the chosen (and applied) training is successful, it will have an impact on a certain set of skills. This will improve the execution of the tasks in question, and, in turn, increase the KPIs.

T&D Analytics: less guesswork, more data-driven

The basic reasoning behind the entire process of defining tasks, skills, and training, as previously said, is simple. The difficult part is putting together the neural/mental map that will connect all of the data and help determine which training programs will be chosen or rejected.

The fact that the correlations are not all linear adds a level of complexity to anyone involved in creating this neural/mental map. Some competencies will impact more than one task, learning activities that will develop one or more skills, etc.

To summarize, if you want to have an impact on such KPIs, you must focus on a certain set of tasks, skills, and provide appropriate training programs. This process of grouping by needs will enhance the general outcomes.

As a result, the basic premise is that the need for training is proven by measurable and objective data. Demand arises from a KPI that can (and should) be improved.

There will be less guesswork and more “data-driven” decisions. In T&D, this is the essence of analytics.

Analytics in T&D: establishing correlations in practice

As you can see, this entire process simply does not exist without reliable data and information. And where do we get this? From interviews and workshops.

Starting from each function, we identify a large list of tasks, which are broken down into a set of knowledge, skills, and attitudes. Each of these lists are discussed, validated, and consolidated in groups. This concludes the process. After dedicating eight hours of conversations to each function, involving professionals, stakeholders, and the training area, it is possible to break down the job description, identify tasks, and skills, and determine these correlations. All accomplished through the use of visual maps made with post-it’s in the classroom (in-person or virtual).

Afterward, this mosaic is assembled behind the scenes, with the addition of an analysis of the complete existing training portfolio (and relating each one of them to the skills that must be developed). A development roadmap is then built.

Of course, the following section of the analysis will focus on the correlation between tasks and KPIs. Then there is the discussion with the managers who chose the KPIs to be analyzed in the first place. This can be a meeting or a workshop (for more managers to participate) to determine which tasks will impact the KPIs. This makes the entire process much more streamlined. This mapping can be accomplished by simple research, for example, but a conversation is more likely to yield useful information.

And that is the entire process of establishing correlations between KPIs, tasks, and skills. This, however, is only the first step.

See you in the next installment of this series. We will be discussing the second stage, titled “Analytics in T&D,” in which individual analyses are conducted to examine how the team is performing and determine which training sessions are appropriate for each individual.



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