How to future proof your HR Function. Part 1. Why HR professionals need data?

Intro. Old-timer vs. Tesla

One of the common weak areas most HR professionals recognise in their profession is inability to measure effectiveness of training. Corporate universities, training centres and other providers of corporate learning every year get and spend enormous human and financial resources, but no one can calculate what return they get on this investment – even approximately.

Lazlo Bock, ex-HR VP and HR Director of Google, a couple of years ago made a bold statement about it:

“Last year, U.S. companies spent roughly $90 billion on learning and development efforts, a sum higher than the gross domestic product of 130 countries. This is a staggering sum, especially when you consider that most of that money and time is wasted. Training and development programs are not necessarily the problem. The problem is that there is often no measure of what’s learned or what behaviours change as a result of such massive investments.“

Only the bravest and most proactive HR professionals are not afraid to discuss this problem openly. Most HR professionals when trying to measure their impact tend to use Kirkpatrick model. This model was first introduced over seventy years ago. How many of us drive cars manufactured at that time? Yet many HR professionals still “drive” it. The model itself is not bad, but may we could change it for something more modern? Most companies use Level 1 (so called “smile sheets”) of this framework anyway judging only how training is perceived by participants.

Modern technologies and new methodologies in corporate training can help us to change the situation for better. Tools and methods which can measure effectiveness of training already exist. But do HR professionals really need it?

Most HR professionals are OK – they got their salaries, bonuses and budget for conferences and implementation of the latest versions of HR software – all it without thinking about the ultimate usefulness of their activities.

We will dig a bit deeper into the technical and methodological details on how we can measure effectiveness of T&D process later. Before thinking what should be changed to enable the effectiveness of measurement of training function in the corporate environment, we must first understand why we would need it. What risks and opportunities HR professionals face if they start to measure it?

Advantages of using statistics in L&D

Our experience shows that there are three essential advantages in using statistical data that help to measure effectiveness of training:

  • it helps makes better managerial and personnel decisions,
  • it allows to share responsibility of the results of L&D process,
  • it allows to measure impact of L&D on the business results.

Better managerial and personnel decisions

When HR professionals use statistical data, their recommendations are not subjective anymore. Paraphrasing Edward Deming who said that “without data, you're just another person with an opinion”, using statistics allows HR professionals to be heard by the managerial team as they start to speak the language of business – the language of data.

HR professionals could now base their opinions on metrics. In the past, all departments would use reasonable metrics and only HR and L&D professionals would operate opinions.

Here is one example.

Let’s explain this point in more detail using our system, SNAPSIM™ Learner as an example. The HR manager spots in the system that an employee has high results in learning. But she also has higher than average points of conflicts. It means that she evaluates her behaviours higher than her direct manager.

This situation requires attention or even intervention of HR function as there is a 60% risk that this employee (a good employee) would leave. And HR function is responsible for turnover figures, isn’t it?

Sharing responsibility of L&D process results

When useful data in L&D becomes visual and HR managers and other stakeholders see it, the magic press of statistical pressure shows its power. If an employee neglects learning activities it negatively impacts his/her manager’s status – as our system aggregates all results of all employees. If a line manager doesn’t take assessments of his/her direct reports seriously, then his/her direct manager have lower results.

So now HR professionals share responsibility for efficiency of learning and with line managers and business unit managers.

Here is one example.

Let’s illustrate it again with how this can be identified with our system. The system reports to the HR Director that two branches of the company, Branch A and Branch B are in the zone, that requires their attention. Both branches have high ratios of knowledge transfer, but learning ratios are below average. The system shows what should paid attention to, as time is limited for HR managers as well managers of branches.

In this example, we should investigate why these branches have low learning ratios. Perhaps, it is difficult to recruit people in these regions or may be recruiting process itself needs attention and HR managers who have the ultimate responsibility for it, need to take action. Also, it makes clear who should be contacted first: the manager who has the largest circle in the diagram – it means the one who has the largest number of employees who learn in the system.

Measuring impact of L&D on the business results

ROI in L&D is the Holy Grail of HR professionals who work in learning and development. From the day the first ever corporate training event took place, professionals try to find the way to estimate the impact of training. The latest attempt was Learning Measurement Level 5 by Dr. Phillips. It calculates ROI as a costs/profit ratio. But it is extremely difficult to calculate the value added by learning, or “isolate the effects of project”. Too many factors have impact on costs and profits of the company.

Statistics, however, has a ratio that can replace ROI in evaluating training and development. It is called a correlation ratio which the ratio of two variables. In our case it can be increase in competencies and profit.

For identifying the correlation, a large group of employees should be trained. Only in this case we can measure how increased competencies impact the business results.

Here is one example.

Example. The system reports to the HR manager that training evaluation ratio is almost identical in eLearning programs, but are very different when the system evaluates face-to-face trainings. It means that in one of the branches traditional training is less effective.

In this case we need to investigate further how face-to-face training is designed and delivered and identify positive and negative factors that impact training results.

Interim results

These three simple examples allow us to see how metrics can help HR managers:

  • have a system for informed and targeted system to prevent the best employees leave,
  • identify problem zones in recruitment,
  • reach learning goals more efficiently, increasing the effectiveness of learning process.

It’s not all. Statistical data helps to answer the following example questions:

  • How to identify 10% of employees that are suitable for managerial jobs?
  • What company departments/units have the best /worst collaboration between managers and their direct reports?
  • How to ensure that learning goals are linked to improved performance?
  • How to justify training budget based on data?

All these opportunities have its price. We will discuss risks of implementing new technologies in the next article.

Constraints of managers

Little have changed since Peter Drucker described four dimensions or "realities", in which most managers operate in his classic book "Effective Executive".

Read more »

Try SNAPSIM™ right now!