Creating a Data-Driven Culture

The amount of data in all areas of life is growing rapidly. People and companies today are constantly generating volumes of data – the speed, variety and complexity of data is also increasing. However, only those who know how to handle data properly and use it for their own purpose can create real added value.

One of the biggest shifts in today’s business world is the transformation from isolated and project-oriented data usage to a completely data-driven culture in organizations. But how can companies transform from an instinct-driven enterprise to one based on data and insights?

To help improve your understanding of this complex subject, this article addresses the following points:

• Definition: What is a data-driven culture?
• Why a data-driven culture matters
• Data-driven culture is currently amongst the hottest business intelligence trends
• Challenges
• BARC recommendations on how to create a data-driven culture

Creating a data-driven culture is about replacing gut feeling with decisions based on data-derived facts, be they simple key figures such as revenue or profit, results from advanced analytics models, or even qualitative data.

The concept of a data-driven culture treats data as the main resource for leveraging insights in every department of the organization. While companies have always been interested in their numbers, the extent of data use is exercised at a higher level within a data-driven culture.

The main aim is to empower all employees to actively use data to enhance their daily work and to fully utilize a company’s potential by making decisions more successful, initiatives more effective and competitive advantages more striking.

The ultimate goal is to build a cultural framework that helps all members of the organization to collaborate to move data at the center of decision-making – from the data owner, to the data scientist, to the business analyst and finally to the employees who use it in their business department. This encompasses coming up with new, data-driven use cases, discovering patterns in data and experimenting with analytics solutions to see what really works in operational processes.

The preconditions for establishing a data-driven culture are access to data, governance of usage and quality of data, methodological knowledge on how to analyze data and appropriate technologies to prepare and analyze data.

Most companies already gain insights from their data. However, a data-driven culture should not be interpreted as blindly following numbers. It should encourage the advancement of data interpretation skills and critical thinking, which enables businesses to not only base their decisions on reliable data, but also to know when it is better not to do so.

There are some major reasons why a data-driven culture matters:

Promoting collaboration between different teams in the organization

Aside from the use of data, collaboration between different teams in the company is the second key factor why a data-driven culture is crucial. The deep insights gained through advanced and predictive analytics by the data science team are the starting point. Those insights generated by data analytics can help other members of the organization in their daily work and connect the ideas of different departments.

Fostering data democratization

This leads directly to the next point. A data-driven culture helps to eliminate gatekeepers that create a bottleneck at the gateway to the data. In most organizations, the IT department acts as the ‘owner’ of the data, while users of this data have to go through it. So a data-driven culture helps to democratize the data to more business users for decision-making.

Developing and launching new products based on company data

Instead of developing a product on the drawing board without any knowledge of customers‘ needs, the intelligent use of data is a key factor in the development of a successful product. Furthermore, existing products can be evaluated and customized based on customer needs. For these reasons, a data-driven culture offers product development teams a glimpse into the future as well as the past.

In BARC’s BI Trend Monitor 2020, data-driven culture was identified by survey respondents as the third most important trend, rising from fifth place in the previous year.

But there are some clear differences in perspective from various company sizes, industries, and geographical regions.

For best-in-class companies, as well as companies based in the UK and Ireland, a data-driven culture is most relevant.

Furthermore, it is interesting to see that this trend is least relevant in Europe, especially in the DACH region (i.e., Germany, Austria and Switzerland). Europe is lagging way behind North America, South America and Asia Pacific.

The relevance of a data-driven culture is obvious. Despite the many benefits it offers, becoming a data-driven company is not that easy.

Although the majority of companies have adequate data management, information obtained in this way is only used to a limited extent for decision-making purposes.

This means that companies collect and process a lot of data, but they don’t trust it enough to make informed decisions. They are still a long way from becoming genuine data-driven companies. But what prevents companies from having a successful data-driven culture?

• Business users consider data to be the domain of the IT department and data scientists/analysts. And the IT department doesn’t want to give away their control over the data that easily. But a data-driven culture starts at the bottom of the company and involves every member of the organization.
• Understanding data as an asset, not as a by-product of business processes: The return on investment is not clear for business users, because data itself does not lead automatically to greater business value. The challenge is to connect the insights of analytics with the problems currently facing the organization in order to improve the business value of the company. 
• Another frequent problem is that data might not be centralized. As a consequence, it may be inaccessible to the employees who need it to make decisions. A data-driven company eliminates data silos, democratizes access to data and consolidates all of the data so that every company member knows where to find it.
• In line with the aforementioned challenge, data is sometimes not in the right format or quality required for the type of analytics being performed. Analyses with data strongly depend on the quality of the data. Poor data quality negatively impacts reliability and can ultimately destroy a company’s business value.
• Security issues and compliance issues: When data is shared within the organization, privacy concerns and security issues arise. Companies need to pay attention to current data protection rules (e.g., GDPR) to avoid fines and the loss of reputation.

In spite of these challenges, a data-driven culture can be reached, but not overnight. Instead, several small steps have to be taken.

1. Clean your data

The first step is to address and improve data quality. New approaches such as machine learning and data mining are a common option when cleaning and structuring data. For this step, external consultants can help to find the right tools and methods.

2. Make data easy to access

After the data cleansing process, companies must ensure that data and information are quick and easy to find, the cost of access is low and information is presented in the right way. This is especially important because the responsibility for data will be given to business users. Companies must create a data governance structure that gives employees greater access to data, instead of restricting it.

3. Improve data literacy

Data literacy is the ability to read data and use it to make better business decisions. This does not mean that you should blindly follow data, but you should be information-driven. Companies should invest in training to support data literacy for end users.

4. Enhance cultural change

In order to complete all these steps, the establishment of a data-driven culture requires the encouragement of critical thinking and the fostering of collaborative decision-making. This time-consuming transformation has to be directed and supported by senior management, especially when it comes to setting up a roadmap, facilitating change and altering the mindset of the organization.