Data Culture: Why It’s So Important And How To Promote It

Data Culture: Why It’s So Important And How To Promote It

Buzzwords about the use of data come up with the handle of digital transformation almost every year. But what do technologies like big data analytics, data science, machine learning, and artificial intelligence have in common? i.e data culture

They are all individual approaches to a much broader solution: the culture of a data-driven company. In this article, we would like to illustrate the importance of holistic data culture and how to establish and promote it.

Big data analytics, data science, machine learning, artificial intelligence – the solutions to today’s problems?

Buzzwords come and go. While the term “Big Data” was still the absolute top in the innovation of data-based work a few years ago, “Data Science” is now cleaning up the field from behind.

But no matter which term is trending, the bottom line is easy to deduce: companies have to, and companies want to work with data.

The question that arises is: What is the most important thing to becoming a data-driven company? Is it the data scientist who anchors machine learning algorithms in the company? Is it the big data analytics platform that takes on fully automated customer care in real-time? Or is it the Data Governance Council that first clear up the data basement, documents it and then makes it available in a structured manner for further processing?

I believe that all of these are simple, albeit enormous, challenges. You can train data scientists, buy infrastructure and hire a few people to anchor data governance. But what is not so easy to establish is the most important thing about the Data-Driven Company: the data culture.

The data culture is the basis for data-based work.

Why is a firmly integrated and shared data culture so influential? According to the hierarchy of needs of the Data-Driven Company, culture is the basis for all data-based work. We see three main reasons for the importance of a comprehensive data culture:


Whether in management or at the forefront of the assembly line: only if data-based solutions are accepted can they generate added value. The first thing to do is to take away fear. Fear that their position is in danger. Afraid that the machine is better. Fear that one cannot rely on the results and instructions of the algorithms.

This fear can only be resolved through knowledge. Only when every cog in the company knows why things happen, how they happen, and their effects can the data-based solutions be accepted. Therefore, the acceptance of data, algorithms and the knowledge of their possibilities is central for every data-driven company.


While we are already working out solutions in terms of acceptance, the first step is to develop solutions. And as in every company, countless construction sites require attention. That is why it is often not easy for management: What use the limited resources for? 

With an established data culture, the inhibition threshold of investing in topics that concern data-based work is lower. Whether essential work such as data governance or innovation using machine learning: If you know about data science’s effects and future potential and related topics, you have them more in focus.


While the two previous points are still passive or controlling, the most critical effect of a coherent data culture is that one also thinks based on data. The best and most important use cases for the use of data – whether artificial intelligence, automation or simply data provision – are usually identified by the persons concerned. 

As a result, it is vital that everyone in the company actively looks for possible uses for data rather than waiting for those use cases to be delivered from outside. Anyone who feels the pain in their daily work often knows the best lever to alleviate it. Therefore, the data culture has to arrive at where things happen.

How can you establish and promote a data culture in the company?

It should be clear that a comprehensive data culture is an advantage. But how can you establish a data culture and promote it in the long term? Here we present three starting points to address these challenges:


As already mentioned, acceptance is best promoted through knowledge. And a broad-based transfer of learning at a more than popular scientific level means an understanding of the methods, options and effects of data-based work. The “Excel course in 2020” aims to bring the use of data, automation, data analysis, data visualization, data science and much more closer to the broadest possible basis within the company. 

To take this step, many starting points must be individually tailored to each company. But basically, it is essential to establish courses, webinars and/or data translators, citizen data scientists, data ambassadors, data consultants or similar roles to guarantee the broadest possible coverage.


While knowledge in the first step is still primarily theoretical, the successes of data-based work must also be made tangible. Through lighthouse projects and, above all, their broad communication, you convey the possibilities and inspire that all employees are looking for use cases in their area.

In addition, successful projects are considered multipliers. If you only know about the potential in other areas, you are also much quicker ready to demand, promote and accept data-based solutions in your area.


The last approach also forms the conclusion based on the Data-Driven Company. Besides, the culture of Executive Support, or rather the Executive buy-in, is the most important to data sustainably anchor and long-term in the company. The management must agree on a vision, a data strategy and continuously represent it to the outside world. 

It is essential to talk about a data vision and pursue the topic in a focused and visible manner for all employees through budget allocation, strategic decisions, and general support. Only if the change is initiated from above but at the same time continuously promoted is there the possibility of establishing a company-wide data culture.

The Tech Spree

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