“We are a data-driven company,” is a familiar refrain we hear from business leaders and managers. This is evidence of a fundamental shift in mindset, reflecting the fact that leaders have now understood and internalized the concept of the data-driven enterprise.

However, when attempting to restructure and reorganize data flows and processes and bring in new ways of working with data, particularly CDOs, CIOs and data teams often run into what feels like a brick wall. Acceptance and lip service may have been paid to a data strategy, but the application of the strategy is fraught with hurdles.

The realization comes soon enough: Data culture and its manifestation in the day-to-day running of the business can make or all too often break any carefully crafted strategies. So, understanding what data culture means within each organization is critical to its success.

At BARC, we see data culture as part of the corporate culture. It refers to all the values, norms and attitudes in an organization that are the basis for actions and decisions related to the handling of data and analytics. The manifestation of data culture can come in different flavors. For example, it can influence where investments are made to improve the BI and analytics landscape and it can dictate the number and roles of the employees who are working with data.

Due to steadily growing interest in the topic, we conducted this survey to better understand the flavors of data culture within organizations, the hurdles they are facing, the initiatives that are underway and of course the wins that have already been achieved with these measures. We learned that 81 percent of our respondents consider data or information as an asset.

This supports the hypothesis that more organizations are recognizing the integral value data and analytics can bring to their business. Following this trend, when we asked about data culture specifically, 76 percent of participants stated that their company is striving for a data culture.

Such figures are encouraging as they support the hypothesis that a mind shift is taking hold. The new mindset realizes that the road to the digital business is not only paved with technological innovations and no single company can purchase its way to data-driven decisions and processes.

Instead, the softer, more difficult structures will enable the ultimate transformation to becoming a fully data-driven business. Together with the lessons learned from this study and the BARC Data Culture Framework, we hope to provide resources that help leaders to ride the wave of this new mindset and begin to build their data culture.

The state of data culture

In the past seven years, a notable change has occurred. The share of businesses with partially or purely data-driven decisions has risen from 14 percent to 34 percent. This substantial increase is emblematic of the importance of data culture. Though many businesses acknowledge that some decisions are still based on gut feeling, the trend is developing in the right direction.

The survey results also reveal that decisions at operational level are still less data-driven compared to management and executive levels. In addition to the growing importance of data for decision-making, the survey records a high emphasis on data as an asset and as a general enabler for improved processes as well as revenue and cost-saving efforts. Organizations are also using data to improve their own processes and create a smoother work stream.

Organization is critical to the success of data culture

To successfully develop a data culture requires clear leadership and well-defined responsibilities. This is exactly the issue that emerges from the study results. 31 percent of laggards have yet to assign responsibilities for their data culture to a department or person.

In contrast, the best-in-class companies have already implemented the organizational measures to embed a data-driven culture. In other words, they plan their data culture initiatives more carefully.

In the majority of cases, responsibilities lie with a dedicated person such as the Chief Data Officer or a data office. In the absence of these roles, leadership must assume responsibility. Best-in-class companies are more successful in spreading their message company-wide, while laggards still focus on establishing a data culture within their finance and accounting departments.

In time, every data culture initiative is valuable

Our survey respondents confirm that all data culture initiatives are important. Currently, the most implemented approaches clearly pertain to access, governance and strategy. Organizations that are still early in the process of shaping their data culture seem to fare better when focusing their strategy on establishing a data democracy. More than a third of them have planned specific initiatives for data governance and data access.

To succeed in these areas, employees must also be able to attain the level of data literacy that is needed to fulfill their role. Respondents largely report that this is not yet the case in practice. Employees’ lack of knowledge where data and analytics is concerned is the second most common challenge to data culture, hitting best-in-class companies and laggards almost equally hard.

The return on investment of data culture

Respondents to this survey strive for the same goals, such as cost reduction, revenue growth and competitive advantage. Of interest here is whether these goals are achieved with an improved data culture. Indeed, this is the case for many organizations. In particular, companies have been able to improve their decision-making process, reduce costs and improve their processes with the help of data.

A harder goal appears to be achieving competitive advantage. Granted, this is a much broader and less clear goal than improved decision-making, but it is one that continues to incentivize leaders to work on their data culture.

The biggest obstacles to establishing a data culture

A huge pain point for many professionals is a lack of management commitment to data culture initiatives, data-driven decisions and improved data handling. Related to this issue is the motivation of employees on a broader level. Two scenarios are frequently mentioned here: employees who have a longer tenure are less open to change in general and employees who are less data literate feel a lot of anxiety around potential changes.

The more mature a company’s data culture initiatives are, the more detailed the description of the hurdles becomes. For example, teams who have been actively working on their data culture report a critical problem once their initiatives are launched and specific projects are completed. It takes substantial change management to keep working on and improving a data culture.

BARC Recommendations

We created the BARC Data Culture Framework to answer the frequently posed question of how to positively address data culture in an organization. The framework identifies the six most important action areas, thus giving companies a guideline on where to focus their attention. There is no hierarchy among the six action areas.

Strategy, leadership and governance typically specify goals and parameters in which a data culture is promoted or can be restricted. Data access and data literacy are important enablers, while data communication serves as a facilitator for data culture.

BARC's Data Culture Framework

BARC’s Data Culture Framework


Based on the BARC Data Culture Framework, we have identified the following action items:


This survey confirms that the six action areas defined in the BARC Data Culture Framework are all contributing to success in establishing a positive data culture. They should all be addressed, but with differing priorities depending on the maturity of the company. Companies with a less developed data culture should start with the fundamental action areas of data access and data governance, while more advanced companies are better advised to fine-tune data strategies and improve leadership and communication.


Authentic leadership starts with the actions and commitment the leaders themselves show. Nearly two thirds of respondents agreed that they need inspiration from the top through leaders who set a shining example of how to work in a data-driven way. Amongst the most important action items for data leadership are:

  • Instill a data-driven meeting culture.
  • Lead by example: pay particular attention to embodying the data strategy yourself, for example, by emphasizing fact-based decisions.
  • Formulate and communicate the data strategy clearly, explicitly and frequently.
  • Invest in competence development by providing sufficient resources for training and further education in data and analytics.
  • Drive and monitor data and analytics initiatives at an executive level.


Nearly half of the laggards in our study identified the lack of a data strategy as a major obstacle. That is why defining a data strategy is so important. Define a data strategy that:

  • is an integral part of the business strategy and
  • shows clearly how it supports the organization’s strategic goals;
  • is holistic by covering both data and analytics,
  • addresses business, technical and organizational aspects in a balanced manner and
  • addresses data culture in each of these aspects.


The key challenge in setting up data governance is the definition of guidelines that set the necessary boundaries to any activities with data but at the same time support a positive, fearless atmosphere in which to use data and analytics as well as new use cases. Important action items are:

  • Define responsibilities around data with special attention to improving data quality and breaking up data silos, two of the most severe inhibitors of a positive data culture, and even digitalization as a whole.
  • Enable the company-wide availability of conformed KPIs and data products.
  • Ensure that information about data (metadata) is available to data consumers and data product developers, for example, by defining the necessary responsibilities for data producers to provide such information or by implementing tools such as data catalogs and business glossaries.
  • Define data ethics guidelines as an important compass for every employee using or analyzing data and communicate them internally (and maybe also externally).
  • Find the right balance between ensuring security and privacy while making sure they do not kill any creativity and innovation.


Having access to data is the foundation for any activity with data. After all, it is about much more than just technical access to data. Action items are:

  • Provide technical access with interfaces, APIs etc.
  • Establish a “right to know” data access culture whereby all data sources should be accessible to anyone unless they contain secret, personal or other data worthy of protection.
  • Define responsibilities to make data understandable (e.g., by obliging data producers or system owners to publish metadata about data originating from their systems).
  • Enable all relevant employees (and potentially also external stakeholders) to understand and work with data and analytics.
  • Communicate clearly the “rules of engagement” with data in data governance and data ethics guidelines.


Data literacy is the ability to find, evaluate, prepare, analyze and visualize data using appropriate tools, as well as to communicate using data and interpret analysis results. Action items are:

  • Build a long-term and broad educational approach to competence development in many different areas.
  • Make sure that competence development is not just aimed at the employees who already work with data anyway, but also includes almost everyone in the organization.
  • Define diverse data literacy curricula for different job roles, career paths etc.
  • Do not only focus on how to get to and understand data but also how to analyze, use and communicate it.
  • Technology training is one part of data literacy but should not be the main issue.
  • Teach data literate persons to communicate with data and collaborate around data.


There are many stakeholders needed to communicate as broadly and extensively as possible about data:

  • The corporate leadership team should explain how data and analytics drive the business strategy and be very clear about the importance of data sharing, exploring analytics and AI and developing data products or even data-driven business models.
  • The CDO or data and analytics leaders should:
    1. Market the capabilities, data products and success stories to show where data and analytics can help the business;
    2. Create spaces for communication (e.g., community meetings, exchange platforms, internal data and analytics conferences, hackathons etc.); and
    3. Foster peer exchange, public speaking etc.
  • Internal and external communications, public/investor relations and marketing departments should communicate success stories and maybe also the company’s high-level data strategy or data ethics approach both internally and externally.

Infographic of the key findings


BARC Data Culture Survey 22

How To Shape The Culture Of A Data-Driven Organization

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