Benjamin Dammertz: In our Webtalk a while ago we talked about the different aspects of a digital transformation, ie strategy, technology, data and culture. There were various questions about the last two topics in particular, what that means in practice and what experience you were able to gather. Let's talk about a topic that is currently being intensively discussed: data literacy, can you please define it?
Markus Pfründer: Data literacy is the ability to read, understand and analyze data and to draw conclusions from it. For organizations of all types and sizes, it is vital that employees develop and continually improve this skill. There is statistical evidence that companies with higher data literacy have higher shareholder value.
Benjamin Dammertz: Understood, data literacy is important. But why is it like that?
Markus Pfründer: This is due to the fact that the volume of data, driven in part by digitization, is increasing at an explosive rate. In most cases, however, companies can only derive real value from data if employees are able to generate insights, be it about customers, employees, suppliers or other points of reference
Benjamin Dammertz: Can you please be more specific? What does that mean in corporate reality?
Markus Pfründer: The more complex the issues that are to be solved with data become, the more important it is to anchor literacy in the organization. Senior management often underestimates how big the gap is and how difficult it can be to close it. What is important here is a vision, a plan for achieving goals and continuous training. Of course, not everyone in an organization needs to become a data analyst. However, concrete measures such as the introduction and measurement of North Star KPIs are important. Many teams don't really know what goal they are working towards. It helps to go through a definitional process together. And then it's time to measure and improve. And start again.
Benjamin Dammertz: Finally, the question: What do you recommend companies to best do to improve the data literacy of their employees?
Markus Pfründer: That is of course always to be seen in the respective company context. In general, however, it can be said that it requires an intelligent combination of several factors. These are more formal aspects such as defining metrics or roles, articulating a comprehensible vision, and probably most importantly, exemplifying and also demanding the use of data for decision-making.
We would like to thank Markus Pfründer for the interview!
