An organizational culture consists of the common behavior and shared standards and values that determine how people in an organization deal with each other, their work, their managers and the external environment. Nowadays however, data is increasingly penetrating organizations and challenging the prevailing culture. Facts based on data are increasingly being used as the basis for making decisions. As a result, cultural values such as ‘experience’, ‘hierarchy’ and ‘tradition’ have become much less relevant. This has a significant impact on the way that people in organizations deal with each other and with their managers. Next to that, the content of work is also changing due to data. It therefore labels organizational culture as a crucial element of a holistic data strategy. This article discusses the various elements that define a successful, data-driven culture. These elements are based on what we learned from experience, and are illustrated along the Hofstede dimensions, one of the most tried and tested methods for mapping culture.
Low versus high power distance
Flat organizations involve employees directly in decision-making processes and give them plenty of freedom to organize their own work. This stimulates and optimizes employee curiosity and creativity. Employees in a flat organization also work in a result-oriented way, which promotes experimentation, testing and a critical attitude. A culture that embraces and encourages experimentation (and, consequently, failure) is therefore crucial in digital transformation. The alternative – an organizational culture with hierarchy as a linchpin – works the opposite way and is therefore not conducive to a data-driven organization. In a hierarchical culture, achieving an optimal result often means compromising between the best possible solution for the organization and the best result in the eyes of direct managers. The latter is the behavior that is rewarded. In a flat organization, tangible results are more important than getting in the good books. This means qualitative output trumps staying behind a desk from nine to five. This encourages employee productivity and a pursuit for the best output in the most efficient way.
Collectivism versus individualism
In the early stages of a digital transformation process, the data team is often small and is made up of a few tech-savvy employees with a high level of intrinsic motivation. Within that team, a culture of individualism is favorable. Nurturing the personal interests of the team members may outweigh the interests of the organization in these early stages. Because they’re the ones driving the transition, they value receiving as much encouragement as possible to continually challenge the status quo, as well as the freedom to experiment. As the transition to a data-driven organization has crossed the threshold and reaches maturity, the importance of a collective culture manifests. For example, enhancing the impact of data projects requires increased collaboration with interdisciplinary teams. Business owners are appointed, and projects are given more direction based on the company-wide vision and strategy. As a consequence, individualism will have to make way for collectivism. Without this shift, the efforts will result in an uncoordinated R&D department full of hobbyists carrying out numerous experiments and PoCs, not integrated in organizational processes and adopted by the wider organization. In a data-driven organizational culture where collectivism thrives, there is clarity about digital ambitions and the route to achieving these. Especially for organizations that equal the sum of acquisitions, divisions and departments, a common culture and identity is crucial.
Low versus high uncertainty avoidance
A risk-averse mindset is not conducive to realizing a data-driven organizational culture. However, this mindset is a natural, reflexive response to organizational growth. Once an organization reaches a certain size, it becomes tempting to prioritize stability, continuity and protection of position. Unfortunately, this often goes hand in hand with a conservative mindset that is instinctively negative towards anything that deviates from what has proved successful in the past. The reasoning behind this is that if newly launched products or services ultimately fail to meet customer expectations, this will seriously dent the company’s reputation and possibly cost it customers. This ensures a decline in the speed and power of innovation because ‘something’ new must always first be thoroughly examined. The long drawn-out process of introducing the VAR in football is a striking illustration of the effect of a conservative, risk-averse culture on the speed with which innovations are adopted. This is in stark contrast to the speed with which comparable technology was implemented for hockey. The proliferation of rules, procedures and bureaucracy is typical for a risk-averse organizational culture. These are created to prevent mistakes being made, while a data-driven organizational culture actually benefits from experimentation, testing assumptions and evaluating results: in other words, a data-driven culture embraces the idea that it’s all right to make mistakes, preferably as many and fast as possible. That is, as long as we learn from these mistakes and transfer this knowledge to business operations, to enable the implementation of more innovative methods.
Outside-In versus Inside-Out
The success of data-driven innovation is entirely determined by the degree to which innovations meet the user’s needs. Each data-driven innovation should start out by seeking to improve the degree to which needs are met. The ultimate example of a culture in which customer experience is central comes from Amazon. In the company’s Seattle board room, a chair is always kept available for the customer, who Jeff Bezos describes as ‘the most important person in the room’. This keeps the organization aware of the people on whose behalf they are making decisions. Amazon uses advanced data analysis as a means of precisely identifying individual customer needs. With this as the starting point, innovations become the means for the improvement of services, not an end in itself.
Long-term versus short-term orientation
The ability to reinvent oneself is not a standard component of an organization’s culture. In this respect, one of the key obstacles is short-term thinking, which negatively affects the transition to a data-driven organization. The consequences of short-term thinking as a cultural characteristic are exemplified by the way organizations tend to manage innovative initiatives and ventures. The managers who are made responsible for these projects are often in the process of building their career. This means that their personal drivers are their main priority, meaning they will primarily invest in achieving many results and establishing a track record of successes as soon as possible. As a result, the emphasis is almost always on a fast performance peak. It takes time to invest sustainably in the further development of innovations, to integrate them into existing business processes, and the benefits are often uncertain. In addition, the results are more difficult to time than the outcomes of simply optimizing the current business. The latter is what’s usually rewarded and expected. However, the aim of digital transformation is to innovate, making a long-term contribution to the organization’s competitive advantage. Experiments are only truly successful until they make it out of the lab. However, experience shows that implementing a new reality does not happen overnight.
Fertile ground for a data-driven organization
Even if organizations have access to and invested in the most advanced technologies that can be unleashed on high-quality data by a highly skilled workforce, it will all be to no avail if a data culture has not yet been forged. Fertile ground for a data-driven organization is created by a culture without hierarchy, a culture where the group is given priority over each individual in it, a culture that doesn’t shy away from risks, a culture that considers their customers king and a culture that aims to make a lasting impact on the organization, even if it means it will take time.
