Sergej Zimpel

HR Analytics is one of the main HR and Recruiting trends in 2017. However, it is also a very complex topic and I got the impression that most people do not really know what it is about and why it got so important. It’s high time to speak to an expert in this field.

Bastian Lücke has a PhD in Experimental Psychology and he is one of the main promoters of HR Analytics in Germany. He currently works as Data Science Project Lead at Loopline Systems and will be joining the People Analytics team at Haufe umantis next year.

Hi Bastian, please tell us who you are and what brought you the the HR Analytics topic

I have been interested in questions that are at the heart of HR Analytics for my entire academic and professional career without being aware of their relevance to HR Analytics (other terms often used interchangeably: People Analytics, Workforce Analytics) as the term didn’t exist yet.

During my studies, I spent a lot of time studying corporate finance and law. But I was also interested in alternative perspectives on finance and investment that went beyond more traditional financial models and built on research in psychology and behavioral economics.

After my studies, I was even more interested in the broad question what determines human behavior, in particular in a social context. So I decided to do a PhD in experimental social psychology and worked in research groups on group processes and various psychology departments for the next 7 years.

However, I didn’t have the feeling I was creating an actual impact with all these empirical insights/research and decided to work in international HR consulting for a few years building a team developing and validating psychometric questionnaires and HR online tools but also conducting more and more HR Analytics projects.

In my current position I’m helping to develop an HR Analytics product that enables companies to integrate their HR data (and beyond) so they can access it whenever they want in real time while providing best practice HR Analytics analyses and reporting.

So in hindsight, my seemingly erratic collection of skills, experiences and interests fit the eclectic requirements of HR Analytics (conducting empirical analyses/research based in psychological research, aligning various stakeholder perspectives (e.g. investors, HR practitioners and employees) surprisingly well. I hope that the path to HR Analytics will be clearer from the start to current/future generations that are passionate about HR Analytics now that it is receiving more and more recognition and is developing into a “normal” role at more companies.

“The two most important stakeholder groups during this process are C-level/management and employees”

In retrospect my motivation to focus on HR Analytics has been twofold: First, to understand human behavior in organizations/companies and to enable decision making on impact measures based on empirical research. Secondly to contribute to company’s’ understanding of their own organization and to enable them to improve their employees’ work experience. The two most important stakeholder groups during this process are C-level/management and employees. Companies do have the goal to create value, and I very much believe that HR Analytics can contribute to this goal. But employees also spend a tremendous amount of their lifetime and energy on their work and I believe this is a tremendous responsibility – and also huge potential as surveys (e.g. by Gallup) show over and over again that most employees are disengaged at work.

The interests of shareholders/management and employees are often presented as competing goals. I disagree. I believe that it is very much possible to increase shareholder value and improve employees’ work experience and HR Analytics is the means to do so.

Companies investing in HR Analytics have gained important experiences over the past years as to what skills, competencies and experiences are required for an impactful People Analytics team. My hope is that this will make it easier for people interested in HR Analytics to get started on this career track and define learning and development goals for themselves along the way.

“HR Analytics” is one of the big buzzwords of 2017. Still a lot of people do not really know, what it is actually about. How would you describe the concept to someone who has never heard about it yet?

My quick and rather technical answer would be that HR Analytics is the combination of diverse skillsets such as data science, psychological research, (HR/strategy) consulting and statistics to enable strategic decision making in HR based on empirical evidence.

There are many forms this process can take on: It can be pretty basic to introduce operational and strategic reporting and metrics in HR. It can be focused on specific use cases such as an empirical assessment of the best sourcing channels and selection data points for certain role profiles/job families. It could be an in-depth analysis what drives voluntary fluctuation in your company, or what makes your best sales people so great, so you can hire and train for exactly these characteristics. It could also be the goal to find a way to match your employees and their motivations and talents with internal career opportunities, to assess the impact of organizational programs such as a re-org or merger or assessing the impact certain leadership styles have on your employee’s’ health and engagement. These are just a few examples of what HR Analytics includes.

At an even more aggregated level I would say that HR Analytics is first and foremost a way to truly understand organizations as complex systems. Organizations have often been perceived as simply black boxes or atomic mobiles – as complex organigrams consisting of individual contributors. Needless to say that both perspectives are oversimplifying. I think that HR Analytics is also an attempt to gain a more holistic understanding of organizations and their parts, e.g. what makes certain teams great, if/how you can change culture and how teams and departments are not simply the sum of their members. This holistic perspective is also important along the employee (and HR-) journey; how you source and select employees has an influence on your efforts to retain talent.

And why are HR Analytics so important?

I think there are 3 major reasons why HR Analytics are so important: It enables strategic decision making in HR based on empirical evidence. It helps to establish HR as an essential department for achieving company strategy and it enables HR to create impact and improve the entire organization based on insights, not only once but as a continuously ongoing effort.

Let’s stay with the medical metaphor. Jeffrey Pfeffer, professor for organization theory and human resource management at the University of Stanford, likens the current status of the leadership industry in his book “Leadership BS” to the state of modern medicine in the early 20th century: There was certainly a need for the value medicine could provide to patients in principle – it’s potential value was clear. But the quality/effectiveness of the products and services as well as their price varied widely. Many products were completely inefficient contrary to their promises and at best based in pseudo-science, but their branding and mass marketing so successful that they still sold very well. Many remedies contained opiates, so they had a pleasant short term effect (even though not the promised impact) and were great for customer retention; but the negative long-term effects more than outweighed these pleasant side effects, such as opiate addiction and the still existing medical condition it had been supposed to cure.

I think this metaphor that Jeffrey Pfeffer applies to the leadership industry can be expanded to pretty much all of HR. The impact of many HR interventions is often not clear: Trainings are only assessed with “feel-good” sheets, the success of organizational change programs remains often unclear. New hires are still often selected based on gut feeling. How does a leadership development program exactly add value to the company? What aspects really impact employees’ engagement and wellbeing and in return have an impact on retention, absenteeism and productivity? How do you control for non-conscious biases in HR decision making? In medicine it was seminal work based on rigid empirical research conducted e.g. by the British Medical Association that helped to define what was best practices saving lives and what is – often harmful – quackery. I think HR is facing a similar challenge and HR Analytics can be a crucial contributor for achieving this goal.

Don’t get me wrong, there are of course many smart people in HR doing great impactful work. But to base strategic HR decisions on systematic empirical evidence is still more of a nice to have than a must have.

“HR is for many reasons too often confined to administrative and operational work”

It’s this newly gained credibility that will enable HR to be perceived as an integral department in every company as evidenced by the increasing number of CHRO positions. HR is for many reasons too often confined to administrative and operational work. I think adopting an HR Analytics mindset means taking a more holistic view of the organization, basing decisions in empirical evidence and being able to communicate to C-level how HR work has contributed to overall company goals.

Taking a longer term perspective, I believe that HR Analytics will also be an integral factor for every company with the goal of becoming a learning organization and staying competitive in a disruptive business environment.

Take the automobile industry as an example: It’s core product has remained unchanged for more than a hundred years, leading to company cultures that focus on efficiency and deep production expertise and incremental innovation, that often has been outsourced to suppliers. These companies are now facing a radical shift in market demand, towards new products that require much less deep production expertise as building an electric car requires a fraction of the parts of a combustion engine based car. Even more the business models these companies’ past successes are based on are shifting away from simply selling cars towards providing mobility (without ownership) and data-based services.

Finding and keeping talents that enable the development of new innovative products and services is of particular importance in this business environment. So is changing organizations and their culture and norms from a focus on incremental improvement to a focus on more radical innovation in both products and business models.

A great employer brand will be crucial for attracting and retaining the sought after talent that enables your company to stay ahead of the competition, in particular in the current demand driven competitive labor market for highly qualified talent. Building a great employer brand in return is the result of a profound understanding of what makes your employees happy, engaged, developing and productive, that is not only based on great recruiting, a great company culture, a great incentive system or a good retention model alone, but a holistic understanding of your company that requires mature HR Analytics.

But why did it suddenly get so important in 2017?

HR Analytics has been around for more than 10 years and many companies have substantially improved their HR Analytics capabilities over the past years. But you’re right that this hasn’t been a linear trend, but that interest has exponentially increased over the past 2-3 years. Several factors have likely contributed:

Data availability in HR has significantly increased over the past years. This is closely related to increased investments and a product development boom in both existing HR products and new HR startups.

From a Senior (HR) management position HR Analytics are increasingly no longer perceived as a vanity project for the most successful companies in the world such as Google, Microsoft or Shell. But rather as an important factor in the modernization of HR as a business function that is here to stay and an integral component for rethinking the way HR has been working.

At the same time, the cost of entry for using HR Analytics has dropped. There has been a wealth of grey and white literature publications, success stories and conference presentations on HR Analytics and more and more scalable HR Analytics are coming to market, allowing companies to improve their HR Analytics capability even without hiring a costly team of highly trained specialists, a customized approach to HR Analytics and unknown ROI.

The DACH region has been particularly slow in its adoption of HR Analytics adoption. One likely reason is the legal situation in this region, e.g. rather restrictive data security laws as well as importance of co-determination and workers councils that is rather unique in international comparison. A second reason is possibly a difference in company culture. German SMEs are often simply less likely to embrace radical innovation than let’s say a company in Silicon Valley that has disruptive innovation as a core value.

What are the main issues and challenges when companies implementing HR Analytics?

In my experience issues are likely to occur when expectations and resources are not matched. Yes, it is absolutely possible to have an employee conduct an HR Analytics project as a one-off project in part-time. But it will just be a proof of concept, you won’t get a full HR Analytics function out of it. Building strategic HR Analytics capabilities will require some investment in building a team with internal and external talent, buying the capability from a consulting firm or investing into software that provides the required HR functionality. Unrealistic and inflated expectations combined with an underinvestment will most likely result in frustration of all stakeholders involved.

A second potential challenge is an approach that sees HR Analytics as a mere technical Analytics-add-on to HR. I think it is crucial to connect this new HR Analytics ability to senior management (e.g. connecting HR Analytics research questions and strategic organizational goals) but also including other relevant stakeholders, most importantly the employees, in the process of generating research questions. On the other hand it’s essential that these insights generate a tangible impact on a more operational (e.g. new selection data points for the recruiting process) or strategic level (improving your employer brand, introducing a tool that matches employees with new opportunities depending on their interests and competencies).

This is also why I don’t think the name HR Analytics is appropriate, as it sounds like “HR as before, but now with 20% more Analytics”. It’s time to rethink HR, and using analytics, data points and a perspective that goes beyond HR is an important part in achieving this goal.

Some people are afraid to get reduced to numbers and table entries. What would you tell them to allay these fears?

I would first of all describe to them the alternative, the current status quo in many companies. This status quo means that organizations are still a black box for management and HR. If there are initiatives to improve the organization, then it is often not clear if they result in the desired impact (or how). Most likely this lack of understanding will have negative implications for the employees, or at least work at these companies won’t be as great as it could be.

A second concern in a company without HR Analytics are biases. Biases are a general tendency of human decision making; most of the time we are not aware of our own biases. Biases also tend to be robust, meaning that even if you know about these biases, you will still fall for them non-consciously. A typical bias is e.g. discrimination against gender, age, etc. in recruiting and career promotion, but there are many more biases. HR Analytics is the best way I am aware of to discover and address these biases at an organizational level.

My take is that HR Analytics are just a tool. How it can be used needs to be accompanied by a normative framework how it should be used, and for what goals. Part of this normative framework are explicit and encoded moral and ethical standards of conduct and laws (e.g. data protection laws). A second pillar of this normative framework is based on governance and organizational culture and more implicit. If there is for example a norm of development and support instead of individual blaming and guilt, HR Analytics could e.g. only be used to improve the understanding of the entire organization, but not to single out single employees (and sanction/punish them) and/or to provide impact that is also in the interest of the employees (e.g. match employees with internal career opportunities, support employees in their development process, understand better what is frustrating employees and causing non-voluntary fluctuation). In this more positive scenario employees would miss out on a great number of benefits without HR Analytics.

I strongly believe that companies that are pushing for business results while ignoring the goals and interests of their employees will always underperform compared to companies who align business goals with people goals.

From an HR perspective I don’t HR Analytics will replace “classical” HR work, but rather help to transform it and make it more impactful; HR Analytics will help make conscious decisions what does and what does not work, it will help communicate the status quo and implementation of company strategy in an organizational realm and particular from an employee perspective. And last but not least it will help to make organizations better places to work at for their employees.