Enhancing your team’s performance by building a data culture

Defining what a data culture is can vary by organization. A data culture is the shared values, attitudes, and behaviors that enable organizations to become data-centric. At Databricks, we think about data culture through gaining insights, making data-driven decisions, improving business performance, and enabling AI. Although having a data culture is becoming a more common topic among data executives, many organizations aren’t there yet – and they should be.

There are many studies that showcase the importance of having a data-centric culture in accelerating business performance. Forrester shares that “organizations that use data to drive insights for decision-making are almost three times more likely to achieve double-digit growth”. Similarly, MIT states “data-driven culture results in increased revenue, improved profitability, and enhanced operating efficiencies”. 

Challenges with building a data culture

Although organizations may believe that building a data culture is important, there are many challenges that prevent organizations from doing it successfully. The most common pitfalls are 1) lack of data talent and skills within the existing workforce, 2) constant and rapid change in the tech landscape, and 3) requirements of organizations to fundamentally change how they work. 

How to start your data culture journey

Starting a data culture journey can be daunting to organizations, but here are five steps that every organization can take to begin improving their data-centric habits.

1. Assess current and desired future states

A key part of starting your data culture journey is assessing where your organization is and where you want to go. Conducting a data & AI culture maturity assessment across leadership, skills & talent, collaboration, attitude, and outcomes is a way to assess your current state. All organizations fall somewhere on the spectrum, however in order to build a strong data culture, moving towards Data Native is key, which includes everyone being a champion of data & AI and using it in every collaboration cross-functionally.

2. Get buy-in from the organization

Change is hard. Creating a compelling and inspiring vision that continuously creates willingness is a critical step in moving the org further. To get buy-in, you need to assess your organization’s capabilities with their willingness to be invested in the changes. The key is to maximize both capabilities, to ensure that the organization has the ability to drive change, and buy-in, to ensure that the right stakeholders are engaged. If both capabilities and buy-in are increased, this will lead to teams being inspired.

3. Organize for success, balancing flexibility with empowerment

Following buy-in, you must ensure that your organization chart is built in a way that maximizes success. While it is not always possible to change your org structure, the key is to think about how we break down silos, improve collaboration, and think of data-as-product. Finding the right champion in each business unit who is willing to go all in with making data the center of their strategies is important. Another critical point is the product mindset for the data team, ensuring that the incentives being created can work with each other and support each other's success.

4. Build capability across the organization 

Developing capabilities, while meeting users where they are, is the way to ensure success. Through role-based, experiential, and community learning, there are many avenues to explore to ensure your organization has the right skills, such as analyzing data to work cross-functionally and using data to support decision-making, to drive desired business outcomes.

5. Manage data culture as a program

Having a persistent data culture can not be a one-time initiative. It must be setup as a continuous and evolving program where building capability, reinforcing behaviors, and measuring success are at its core. Determining key milestones and metrics early on will determine the success of the program. Having a regular cadence of inspection of the program will also ensure touch points for evaluation and adjustments for any changes. 

Becoming a data-native organization is a journey for most organizations. Databricks can partner with you along the journey and help develop a data culture maturity plan, establish a Center of Excellence, and build a process of continuous learning. Start your generative AI journey today through Databricks Academy.