Training and financial performance: what the studies say

Which "performance" are we talking about?

Studies on training measure different things, which must be distinguished before comparing their conclusions:

Type of outcome	Example indicators	Link with training
HR outcomes	Retention, engagement, skills	Most direct
Operational performance	Productivity, quality, lead times	Intermediate
Financial performance	Profit, profitability, market value	Most indirect

The further the outcome is from the training, the more other factors come into play (prices, competition, the economic cycle) and the harder it is to isolate the effect of the training itself.

What do studies show about productivity?

Two benchmark econometric studies compare the effect of training on productivity and on wages:

• Dearden, Reed and Van Reenen (2006). Using a panel of British industries covering 1983 to 1996, a one-point increase in the share of workers trained (for example from 10% to 11%) is associated with about 0.6% more value added per worker and 0.3% higher wages. The authors conclude that studies measuring the effect of training through wages alone underestimate it.
• Konings and Vanormelingen (2015). Using Belgian firm data, the productivity gain of a trained worker is substantially higher than the wage gain. In the working-paper version (IZA, 2010), the productivity premium is estimated at 23% and the wage premium at 12%.

Both studies suggest that the company keeps part of the gain produced by the training it pays for.

And on financial results?

The findings are more nuanced:

• Tharenou, Saks and Moore (2007), meta-analysis of 67 studies: training is positively related to HR outcomes and organisational performance, but only very weakly to financial outcomes. The link is stronger when training is aligned with company strategy.
• Kim and Ployhart (2014), Journal of Applied Psychology: across 359 firms followed for more than twelve years, selective staffing and internal training influence profit growth through labour productivity. Firms that staff and train more effectively outperform their competitors before, during and after the 2008-2009 recession, even after controlling for prior profitability.
• Garavan et al. (2021), meta-analysis of 119 studies: training is positively and directly related to organisational performance, and the link grows stronger over time. The quality and the quantity of training produce comparable effects.

In short: the effect runs through productivity and skills, it takes time, and it gets diluted when you look for it directly in the income statement.

Why causality remains hard to establish

Three biases complicate interpretation:

• Selection. Companies that train the most are often also the best managed or the most profitable. Training can be a consequence of performance as much as a cause.
• Reverse causality. A growing company has more resources and more training needs.
• Heterogeneity. "Training" covers actions of very uneven quality. A positive average can hide programmes with no effect.

The studies cited above use methods designed to limit these biases (panel data, control variables, production-function estimation). They reduce uncertainty without removing it.

The cost of not training: what a company can measure itself

Training costs are visible and budgeted. Costs linked to a lack of skills are scattered across other budget lines. This asymmetry encourages cutting the visible expense. Rather than relying on market averages, a company can quantify these costs with its own data:

Cost linked to missing skills	Indicator	Internal source
Errors and rework	Defect rate, returns, complaints	Quality, customer service
Slow skills ramp-up	Time before a new hire works autonomously	Managers, HR
Dependence on a few experts	Number of people who master a critical skill	Skills mapping
Departures	Voluntary turnover rate, reasons for leaving	HRIS, exit interviews
Replacement	Recruitment cost and vacancy duration	Invoices, recruitment tracking

This table does not produce an ROI. It provides the baseline needed to then measure the effect of a programme (see How to measure the ROI of a training plan and Skills mapping).

Figures to handle with care

Some figures circulate widely without a verifiable source. One example is a statistic attributed to ATD (formerly ASTD), according to which companies that invest most in training have 218% higher income per employee. We could not find the original publication or its date, so the figure is not used here. The same caution applies to engagement or retention ranges presented without a named study.

Vendor case studies and self-reported surveys can be useful for ideas. They do not replace measurement on your own data.