Decoding the secret of Data Culture: These factors truly influence the culture and success of businesses

Artificial Intelligence
Data Science
Strategy

16. March 2023

Team statworx

A data culture is a key factor for effective data utilization

With the increasing digitization, the ability to use data effectively has become a crucial success factor for businesses. This way of thinking and acting is often referred to as data culture and plays an important role in transforming a company into a data-driven organization. By promoting a data culture, businesses can benefit from the flexibility of fact-based decision-making and fully leverage the potential of their data. Such a culture enables faster and demonstrably better decisions and embeds data-driven innovation within the company.

Although the necessity and benefits of a data culture appear obvious, many companies still struggle to establish such a culture. According to a study by New Vantage Partners, only 20% of companies have successfully developed a data culture so far. Furthermore, over 90% of the surveyed companies describe the transformation of culture as the biggest hurdle in the transformation towards a data-driven company.

A data culture fundamentally changes the way of working

The causes of this challenge are diverse, and the necessary changes permeate almost all aspects of everyday work. In an effective data culture, each employee preferably uses data and data analysis for decision-making and gives priority to data and facts over individual “gut feeling.” This way of thinking promotes the continuous search for ways to use data to identify competitive advantages, open up new revenue streams, optimize processes, and make better predictions. By adopting a data culture, companies can fully leverage the potential of their data and drive innovations throughout the organization. This requires recognizing data as an important driving force for decision-making and innovation. This ideal requires new demands on individual employee behavior. Additionally, this requires targeted support of this behavior through suitable conditions such as technical infrastructure and organizational processes.

Three factors significantly shape the data culture

To anchor a data culture sustainably within a company, three factors are crucial:

Can| Skills
Want | Attitude
Do | Actions

statworx uses these three factors to make the abstract concept of data culture tangible and to initiate targeted necessary changes. It is crucial to give equal attention to all factors and to consider them as holistically as possible. Initiatives for cultural development often limit themselves to the aspect of attitude and attempt to anchor specific values separate from other influencing factors. These initiatives usually fail due to the reality of companies that oppose them with their processes, lived rituals, practices, and values, and thus prevent the establishment of the culture (actively).

We have summarized three factors of data culture in a framework for an overview.

1. Can: Skills form the basis for effective data utilization

Skills and competencies are the foundation for effective data management. These include both the methodological and technical skills of employees, as well as the organization’s ability to make data usable.

Ensuring data availability is particularly important for data usability. The “FAIR” standard – Findable, Accessible, Interoperable, Reusable – provides a direction for the essential properties that support this, such as through technologies, knowledge management, and appropriate governance.

At the level of employee skills, the focus is on data literacy – the ability to understand and effectively use data to make informed decisions. This includes a basic understanding of data types and structures, as well as collection and analysis methods. Data literacy also involves the ability to ask the right questions, interpret data correctly, and identify patterns and trends. Develop relevant competencies, such as through upskilling, targeted workforce planning, and hiring data experts.

2. Want: A data culture can only flourish in a suitable value context.

The second factor – Want – deals with the attitudes and intentions of employees and the organization as a whole towards the use of data. For this, both the beliefs and values of individuals and the community within the company must be addressed. There are four aspects are of central importance for a data culture:

Collaboration & community instead of competition & selective partnerships
Transparency & sharing instead of information concealment & data hoarding
Pilot projects & experiments instead of theoretical assessments
Openness & willingness to learn instead of pettiness & rigid thinking
Data as a central decision-making basis instead of individual opinion & gut feeling

Example: Company without a data culture

On an individual level, an employee is convinced that exclusive knowledge and data can provide an advantage. The person has also learned within the organization that this behavior leads to strategic advantages or opportunities for personal positioning, and has been rewarded for such behavior by superiors in the past. The person is therefore convinced that it is absolutely sensible and advantageous to keep data for oneself or within one’s own team and not share it with other departments. The competitive thinking and tendency towards secrecy are firmly anchored as a value.

In general, behavior like described in the example restricts transparency throughout the entire organization and thereby slows down the organization. If not everyone has the same information, it is difficult to make the best possible decision for the entire company. Only through openness and collaboration can the true value of data in the company be utilized. A data-driven company is based on a culture of collaboration, sharing, and learning. When people are encouraged to exchange their ideas and insights, better decisions can be made.

Even possible declarations of intent, such as mission statements and manifestos without tangible measures, will change little in the attitude of employees. The big challenge is to anchor the values sustainably and to make them the guiding action principle for all employees, which is actively lived in everyday business. If this succeeds, the organization is on the best way to create the required data mindset to bring an effective and successful data culture to life. Our transformation framework can help to establish and make these values visible.

We recommend starting to build a data culture step by step because even small experimental projects create added value, serve as positive examples, and build trust. The practical testing of a new innovation, even only in a limited scope, usually brings faster and better results than a theoretical assessment. Ultimately, it is about placing the value of data at the forefront.

3. Do: Behavior creates the framework and is simultaneously the visible result of a data culture.

The two factors mentioned above ultimately aim to ensure that employees and the organization as a whole adapt their behavior. Only an actively lived data culture can be successful. Therefore, everyday behavior – Do – plays a central role in establishing a data culture.

The behavior of an organization can be examined and influenced primarily in two dimensions.

These factors are:

Activities and rituals
Structural elements of the organization

Activities and rituals

Activities and rituals refer to the daily collaboration between employees of an organization. They manifest themselves in all forms of collaboration, from meeting procedures to handling feedback and risks to the annual Christmas party. It is crucial which patterns the collaboration follows and which behavior is rewarded or punished.

Experience shows that teams that are already familiar with agile methods such as Scrum find the transformation to data-driven decisions easier. Teams that follow strong hierarchies and act risk-averse, on the other hand, have more difficulty overcoming this challenge. One reason for this is that agile ways of working reinforce collaboration between different roles and thus create the foundation for a productive work environment. In this context, the role of leadership, especially senior leadership, is crucial. The individuals at the C-level must necessarily lead by example from the beginning, introduce rituals and activities, and act together as the central driver of the transformation.

Structure elements of the organization

While activities and rituals emerge from teams and are not always predetermined, the second dimension reflects a stronger formalization. It refers to the structure elements of an organization. These provide the formal framework for decisions and thus shape behavior, as well as the emergence and anchoring of values and attitudes.

Internal and external structure elements are distinguished. Internal structure elements are mainly visible within the organization, such as roles, processes, hierarchy levels, or committees. By adapting and restructuring roles, necessary skills can be reflected within the company. Furthermore, rewards and promotions for employees can create an incentive to adopt and pass on the behavior themselves to colleagues. The division of the working environment is also part of the internal structure. Since the work in data-driven companies is based on close collaboration and requires individuals with different skills, it makes sense to create a space for open exchange that allows communication and collaboration.

External structure elements reflect internal behavior outward. Thus, internal structure elements influence the perception of the company from the outside. This is reflected, for example, in clear communication, the structure of the website, job advertisements, and marketing messages.

Companies should design their external behavior to be in line with the values of the organization and thus support their own structures. In this way, a harmonious alignment between the internal and external positioning of the company can be achieved.

First small steps can already create significant changes

Our experience has shown that the coordinated design of skills, willingness, and action results in a sustainable data culture. It is now clear that a data culture cannot be created overnight, but it is also no longer possible to do without it. It has proven useful to divide this challenge into small steps. With first pilot projects, such as establishing a data culture in just one team and initiatives for particularly committed employees who want to drive change, trust is created in the cultural shift. Positive individual experiences serve as a helpful catalyst for the transformation of the entire organization.

The philosopher and visionary R. Buckminster Fuller once said, “You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete.” Because with the advancement of technology, companies must be able to adapt to fully tap their potential. This allows decisions to be made faster and more accurately than ever before, drives innovation, and increasingly optimizes processes. The sustainable establishment of a data culture will give companies a competitive advantage in the market. In the future, data culture will be an essential part of any successful business strategy. Companies that do not embrace this will be left behind.

However, the use of data is a major problem for many companies. Often, data quality and data compilation stand in the way. Even though many companies already have data solutions, they are not optimally utilized. This means that much information remains unused and cannot be incorporated into decision-making.