Dr. Derler, can you tell us a bit about your professional journey? How did you become the principal of research and value at Visier?

The way people and organisations affect, inspire and frustrate each other has always fascinated me. Early on in my career, I studied Philosophy in Europe, and on the side, I worked in various sales and customer service roles. During all these years, I observed the effectiveness and failures of good and bad leadership and management, and the effect on employees and customers. I took up a postgraduate degree in economics with a focus on leadership and organisations. Upon graduation, I joined the management consulting world as an HR and talent management research analyst where I got the chance to study HR and talent management practices of thousands of companies from a business, talent, and social psychology-based perspective.

Speaking to and learning from hundreds of HR and talent management professionals over the years made it very clear to me that there is one critical component for understanding the optimal way to utilize human capability and engagement for the organization: access to people data, and the ability to use it for the betterment of organisations and its workforce. So, when I joined Visier, a company that is unquestionably the market leader in people analytics, to research best practices in people analytics, my background in quantitative and qualitative research, storytelling and continuous learning about new practices and technologies came in handy. I strongly believe that no organisation can do meaningful and effective HR without working closely with their people analytics function; today’s business world is too complex to be based on mere assumptions and past experiences, so all HR programs and practices should start and end with data.

In your research, what have you found to be the biggest challenges that people managers face when it comes to handling people-data?

Most managers are used to making decisions based on financial and business-related data, but the inclusion of people data in their decision-making processes is still a muscle that needs to be built. In my interviews with leaders about the many challenges they face when trying to integrate people data into everyday workflows, a few issues came up more than others: first, the translation of people data seen on a screen into the actual business context is not always a straightforward exercise. For example, what does a “turnover rate” mean for their business, what are the reasons for a high or low turnover rate, how does their rate compare to other leaders or their competitors, and what should they be doing to improve it? To make these people data points useful and informative, managers need to see the benefit of using facts (=data points) versus gut feelings for their decision making. This precludes trusting the data, overcoming existing opinions and experiences, but also being able to learn to tolerate a residual level of ambiguity that comes with using real people data.

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