HR and L&D: next step in digitalisation is efficiency

L&D professionals can't prove they deliver business impact. This should change.

What's the problem with L&D?

Most HR and Learning and Development (L&D) professionals know that Learning and Development market is huge – according to some estimates it will be $240 BN globally in 2022. Impressive amounts of money companies spend on L&D can’t hide the fact that the industry is not efficient – among the most common complaints of L&D professionals is that they fail to prove ROI for training they deliver for employees. Business leaders are ready to spend more on training, they just don’t understand how the training would impact the business results.

As it turns out, digitalisation of the L&D function didn’t solve the problem. The traditional LMS don’t provide metrics needed to link training and business performance. In most HR textbooks this link is presented as a «black box» – everybody understands that there should be a correlation, but it is supposed be unmeasurable. HR professionals can only report data on how much money and time was spent on training.

We are on a mission to change it and to provide HR professionals with metrics for measure the efficiency of L&D function.

How?

We are not the first who try to solve this problem. Regularly, there were attempts to do it, all of them failed. One approach was to calculate ROI in training. The problem with this approach is that it can only be used in sales, compliance and work safety training. In all other cases, too many factors influence the business results and it is not possible to identify the impact of training. So we, after some attempts, decided not to use ROI and find the better way.

Viagra was originally developed to treat cardiovascular problems. Later, the well-known “side effect” was discovered.

What is not well-known, that Viagra can guarantee this side effect to everyone.

The correlation coefficient for Viagra is .38. It means that there is a significant correlation between taking a pill and improved sexual functioning. Tomas Chamorro-Premuzic, the author of “The Talent Delusion: Why Data, Not Intuition, Is the Key to Unlocking Human Potential” uses the example with Viagra to explain how the statistical term for correlation can be used to predict future performance of employees.

We use a similar approach: we analyse the increase in competencies of employees of an organisation and then connect these metrics with business results which come in different flavours: KPI/OKR, sales, costs, profit. We collect data on individual level (for each user) as well as data for each unit and department, so we have plenty of data to analyse.

Why now?

On August 26, 2020, the SEC issued a final rule that modernizes the disclosure requirements in Regulation S-K, Item 101(c). It expands the disclosure requirements for human capital to include any “human capital measures or objectives that management focuses on in managing the business,” including those “measures or objectives that address the development, attraction and retention of personnel.” The SEC specifically noted that it did not adopt more prescriptive requirements because “the exact measures and objectives included in human capital management disclosure may evolve over time and may depend, and vary significantly, based on factors such as the industry, the various regions or jurisdictions in which the registrant operates, the general strategic posture of the registrant . . . and other conditions that affect human capital resources.”

The reasoning for the SEC position is simple: in 2015 only 16% of value in S&P companies was based on physical assets, the rest was based on human capital, human capital has to be reported and measured. The International Integrated Reporting Council, another influential organisation recommends reporting Human Capital matters in detail, including impact and how it decreases or increases over time.

Business leaders are under increasing pressure to provide meaningful reports on how financial capital impacts human capital.

Now these requirements are compulsory for large publicly traded companies, but soon it can become de-facto compliance for all organisations.

Conclusions

HR quickly becomes very digitised. We hear about HR metrics, Big Data, AI and data science. However, most applications of these tool often are used to state the obvious. In one of the business cases published recently a large organisation used Big Data and AI to identify employees who are ready to leave it. Conclusion was that employees who haven’t used vacation for the last 5 years are in this risky group. We don’t need all these tools for simple analysis like that. The promise HR professionals can offer the C-suite with the tool like ours could be as follows

“We need a budget of $N to train our employees. This training would increase the level of competence by N%. Each % in of increased competence will cause %N of increase in profits, so we expect to increase profit by $N as a result of this training”.

We think all the future tools for corporate learning will all tools needed to prove value and impact of L&D on business results.

And we develop one of these tools.

Try SNAPSIM™ right now!