Actionable insights for the right people at the right time

Photo: Littal Shemer Haim ©

 

 Actionable insights for the right people at the right time 

How would you define a professional expert in the field of data-driven HR? Certainly, there are many definitions to the People Analytics domain, that may include skills, practices, and responsibilities. However, today for a change, I’d like to suggest a different angle: a professional expert is someone you would always want to learn from and be inspired by. I have the honor to host my colleague from Amsterdam, that definitely fits this definition: Hendrik Feddersen, an expert in HR business processes and analytics, who offers “actionable insights to the right people at the right time”, in a European public sector organization. I didn’t spare Feddersen some hard questions in this interview, and I’m grateful for his thought-provoking answers and his contribution to the diverse opinions in our community.

 

The path to expertise

 

LSH: Tell us about yourself, Hendrik, and your background as a People Analytics professional?

HF: Thanks for the interview. I am a senior HR professional, speaker, and the author of HR Analytics Live. I graduated from the Bocconi University in Milan with a degree in Business Administration in 1988 and enjoyed specializing in HR Management, for many years. Having a well-appreciated business acumen, I continuously receive new projects in my current role, to optimize HR processes and HR Information Systems. I’m the Head of Human Resources Information Systems in The European Medicines Agency, which is responsible for the protection and promotion of the public and health, through the evaluation and supervision of medicines.

LSH: There are many paths one can go to reach a People Analytics role. What are the advantages of a path which stems from HRIS offers, and what are the challenges?

HF: At my workplace, I have privileged access an enormous amount of confidential HR data. My skills in extracting data from SAP and the various SuccessFactors Talent Management modules enable that. Fortunately, I have a strength in nudging action-based on my observations and data extraction. Innovation in HR digitalization comes only on the condition that one understands the detailed HR processes and how those are related to HR data. My challenge, however, is to be able to serve all my internal customers promptly and surpassing their expectations. Yet, excellent customer service depends a lot on up-to-date IT tools.

LSH: Besides your academic background, you are most experienced in on-line learning. To advance one’s skills, would you recommend People Analytics domain-specific programs or general data science programs, and why?

HF: Online learning comes from my insatiable desire to self-development. I learned many of the things that I do now at work, in the last five years. It is an interesting question. To advance one’s skills, I would recommend general data science programs. In the open world, I mean, outside the HR domain, there is so much more that is going on, and people are much more open to sharing their bright ideas. People also receive the credit they deserve. My recommendation is to learn in the open world, and then use the new skills in the HR domain.

 

The professional community

 

LSH: Do you think that People Analytics as a profession has an open-source culture? Does openness make a difference in this domain?

HF: I believe that the People Analytics profession doesn’t have an open-source culture. That is a problem, of course, because this way, the People Analytics domain does not develop as fast as data science in general. One of the reasons for this is the HR data, which is, by its nature, sensitive, confidential, and change quickly according to the circumstances. Nevertheless, the People Analytics domain does progress, thanks to proprietary software and thanks to meeting like-minded professionals at conferences.

LSH: Recently, you published a comprehensive open book about People Analytics practices in R. Tell us about your experience in R. How R is better? Are there barriers to start using it?

HF: Unfortunately learning R demands a steep learning curve. I published all my R code examples applicable to HR. There is no point in keeping them for myself. Any comments for improvement are welcome. I currently use R, mostly for quick and compact operations equivalent to Excel macros. R is much easier to read, and it manipulates data ultrafast. The beauty of R is that it can handle vast amounts of data quickly. There are numerous open-source packages to do all sorts of things. For R, there is a community, while there isn’t one for SAP HCM and SuccessFactors, or not one that I am aware of. An open-source programming language is much more fun, and acquired skills are transferable to other companies.

 

A senior’s perspectives

 

LSH: You have a perspective of two decades in a very special organization: The European Medicine Agency. How did data-driven HR change during these years in it?

HF: That’s right; in fact, I have been doing the same HR activities for the last twenty years more or less. However, the sophistication I have been experiencing is impressive, and it never stops. The arrival of SAP HCM and SuccessFactors Talent Management modules were a breakthrough in producing vast amounts of new HR data. Of course, with more data come more responsibilities and more hick-ups.

LSH: How did The European Medicine Agency, which is a data-driven organization by its nature, contribute to the development of People Analytics? What opportunity it offered, in terms of culture, talent, tools, and investments?

HF: At the European Medicine Agency (EMA), colleagues are brilliant and highly educated. At EMA data protection is a strength. We started implementing data protection already in 2001. The new GDPR for European Union institutions and agencies has given us further impulse. It provides me with a lot of work: drafting of records forms, compliance and risk assessment forms, privacy statements and description of processes. The very robust selection procedures are another strength at EMA. We are very objective and transparent in our methods. IT tools are undoubtedly necessary to generate HR data and analyze it afterward. It is also true the other way round: to steer an organization with advanced HR Tech tools, you must use the HR data available. Events take place at a breakneck pace. For example, going paperless meant that several colleagues had to get quickly familiar with HR numbers, digital signatures, and reporting tools.

LSH: We usually use, as People Analytics professionals, the mantra of “impacting the business.” What meaning such a mantra has in the public sector?

HF: The European Medicines Agency (EMA) is, indeed, a part of the public sector. However, since it provides services to patients and the pharmaceutical industry, it is unique. For example, EMA is committed to enabling timely patient access to new medicines. EMA promotes innovation and development of new drugs by European small and medium-sized enterprises. The mantra for us could be creating a supportive and fair work environment for the different generations and nationalities, notwithstanding the pressure to do always better and faster. For me, success is when others in the organization follow my line of thoughts and take actions based on the HR data I am providing.

LSH: What would be your advice to HR professionals who want to be more data-driven? From your experience, what is the right way to start?

HF: I wrote about it recently. HR managers are accustomed to making intuitive decisions based on personal experience or judgment. However, it takes time and patience to identify the correct HR data to base managerial decisions. In my view, it is crucial to gain trust from employees. Data quality is a significant challenge too. Not all HR problems are suitable for People Analytics. The overall aim should be to provide actionable insights to the right people at the right time. To do this, HR needs to have a good understanding of what their audience’s priorities are and be able to show how their analysis directly relates to those goals.

LSH: Thank you, Hendrik! It was a pleasure to host you. I hope you’ll continue sharing your experience and resources. I’ll surely continue to follow your work.

 


About the author:

Littal Shemer Haim brings Data Science into HR activities, to guide organizations to base decision-making about people on data. Her vast experience in applied research, keen usage of statistical modeling, constant exposure to new technologies, and genuine interest in people’s lives, all led her to focus nowadays on HR Data Strategy, People Analytics, and Organizational Research.


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