L&D and the Correlation-Causation Fallacy

L&D and the CorrelationCausation

Fallacy

Opinion Piece

Correlation vs Causation

Correlation is any statistical relationship or association between two data sets, aka two results that occur at roughly the same time. The key word here is any – meaning those results can be purely coincidental and therefore unrelated.

Causation is the undeniable event in which there is a cause and effect. A happened, so B occurred.

Correlation vs Causation

There’s the idea that correlation implies causation. This is rarely the case. Correlation can be easily exploited. If correlation implied causation, you could argue the number of films Nicolas Cage has appeared in correlates to visitors at Disneyland Paris.

Correlation in L&D

While correlation is a useful statistical technique, it shouldn’t be used to prove return on investment (ROI) in L&D. Why? There’s no room for loose threads when showing impact and justifying decisions to executives.

Justifying Spend

L&D leaders know they need to justify spending. Most look solely at ROI through the lens of their role, considering traditional KPIs such as knowledge gain, time to proficiency etc.

And only then will they use improvements on these metrics to correlate L&D to business performance. Which – for the most part – is quite the leap.

What Business Leaders Want

What business leaders want from their L&D investment is the dial to be moved on strategically impactful metrics such as revenue per employee, profitability, talent retention and team effectiveness.

If you can show causation to these types of business metrics, you become a truly strategically impactful L&D function.

Correlation: What’s It Good For?

Correlation is better used as a grounding point for hypothesis testing, such as ‘Do higher log in rates this month directly cause higher completion rates?’.

Causation is the process of proving logins lead directly to completions.

Avoid Assumptions

Falling victim to the correlation fallacy can lead to ineffective training solutions, an absence of quantifiable business impact and the loss of the L&D budget altogether.

It's important to avoid assuming causation and use data analytics to make informed decisions about the impact of training on business performance.

Learning Technology

Learning technologies have historically focused on retrospective analytics due to the perceived challenges of L&D as a cost centre with limited impact. However, this reactive approach alone is insufficient.

Learning Technology

The key is to gather data before learning happens, through processes such as workforce planning gap analyses and capability frameworks mapped to business strategy, to prove true causation in L&D results.

By starting learning on a consistent digital platform and gathering data from the outset, the correlation and causation debate can be minimised, leading to better business impact data.

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