Data Culture in Organizations: A Framework for Culture Transition

Abstract

With the ongoing data revolution, entire business processes are being revised and organizations all over the world are facing similar challenges in a changing competitive landscape. The quest of becoming data driven has become a matter of survival. However, surprisingly few companies have made the transition to the extent where data analytics becomes the powerful tool it has the potential to be. And our overall findings indicate that it is overlooked in academia as well. This study maps the disconnection in organizations and ascribe the gap to the lack of an underlying organizational culture, which supports and promotes data driven behavior and a data agenda. We find three general characteristics in our data: (1) data driven decision-making, (2) fail fast and learn fast, and (3) common language, which we refer to as a Data Culture, out of necessity and convenience for a collective term.
We extract 24 relevant documents from McKinsey, and 26 supporting documents, and find that culture is an overlooked component of the organization. Management does not assign the value nor attention it really needs as culture is a complex and fragmented invisible force difficult to measure. However, our data also suggest that if misalignment between the underlying culture and the business strategy is a reality, the organization becomes unhealthy and has difficulty achieving strategic goals – such as using data as the base of decision-making.
We use ideas from Edgar Schein with six culture embedding mechanisms for leaders to influence organizational culture. We modify these mechanisms to fit with big data and suggest 18 actions to act on in the 6A framework. The purpose of the framework is to guide leaders on all levels of an organization towards a data culture. We find that cultural change must start at the top, however middle managers are essential in aligning culture on a department level with the overall business strategy