Becoming data-driven pays off - But how do you get there?

Today C-level executives and decision-makers need to navigate a variety of buzzwords. One of the most interesting, with the most significant potential, if you ask me, is to become a data-driven organization. Being a data-driven organization is primarily associated with opportunities to sharpen your offering and at the same time become more successful, increase the degree of innovation, and become more sustainable. Yet, despite all the arguments in favor, it isn't easy to become entirely data-driven in practice. Why? I will try to give my perspective on that.

From the inside to the outside world

I should start by outlining what we mean by a data-driven organization. First, it can be described as an organization that makes tactical and strategic decisions based on data. This differs quite significantly from traditional decision-making, mainly based on gut feeling, personal experiences, or even just bold hopes.

Data-driven organizations use data to investigate and develop several different areas. This can be, for example, analyzing customer experience, identifying new customer behaviors, addressing problems within the organization, evaluating new products and services, investigating new growth opportunities or new sustainable revenue models. In addition, data applied correctly can contribute and bring significant benefits in everything from understanding internal processes to understanding the market and world around you.

Better results with the data drive

Several studies underpin the benefits of being data-driven. For example, a survey from Forrester Consulting shows that data-driven organizations are 162% more likely to exceed their revenue targets than non-data-driven organizations. The Harvard Business Review also mentions that data-driven organizations perform remarkably better than their less data-driven competitors, with 6% higher profitability and 5% better productivity.

How does an organization become data-driven, then? Of course, it is not trivial to become data-driven. Still, in short, I believe that all organizations that have access to and generate data can become data-driven. There are several essential cornerstones in becoming data-driven. One is access to data. Everyone in an organization must access the data required to create insights, innovation, and make informed decisions. Access to data can be facilitated in several different ways. One way that has become popular in recent years is to manage data as a product owned by domain areas. These domain areas take ownership of their respective data and make it available to other domains. If you are more interested in what this type of architecture looks like, both organizationally and technically, I recommend delving into complementary concepts such as Data Mesh and Data Fabric. However, you choose to solve the challenges, access to relevant and quality data is crucial in becoming data-driven.

Foster a culture

In addition to accessing data, technology is a component that is often attributed the most attention and weight. So, of course, technology is important to become data-driven. According to Gartner, significant investments are made in solutions for data and analytics also throughout the pandemic. It is good that the area for data and analytics remains a priority, but as I said, it is often the technology that gets the most focus. Unfortunately, to become data-driven, it is not enough to have the right technology in place. Usually, the real challenges are found in other areas.

To become a data-driven organization, people must change how they behave - and that isn't easy. It is also clear from surveys in this area. For example, Harvard Business Review Analytic Services has published a survey showing that nearly 75% of organizations do not have a leadership that supports a data-driven culture or promotes innovation based on analysis and new insights. The survey also shows that 24% of those surveyed state that their corporate culture limits access to information, and 20% think that the organizational structure is a constraint for using data analysis. It becomes complicated to become a data-driven organization with such an attitude.

Lead by example

A successful data-driven organization needs to have a clear leadership that supports, points out the direction, and prioritizes the data-driven development. There is also a need for clear and robust change management that can lead the organization towards becoming more hypothetical and insight-driven. Once the conditions are in place, there will be an organic growth where new hypotheses, insights, business models, and products or services based on data are created. Only then can an organization become data-driven.

In summary. For me, the most crucial insight is that an organization that wants to become truly data-driven must provide employees with the data they need, when they need it and at the same time give them the freedom to act and deliver based on it. In addition, data and decision-making linked to data needs to be democratized.

So before you cast those all too lustful glances at exciting new analytics services, hybrid clouds, and AI solutions, think about how you can promote a data-driven culture in your organization.