Data-driven culture for decision making

Data is one of the most valuable assets of organizations. Learning to store, analyze and interpret data not only enables more informed decisions, but, according to a McKinsey report, increases the EBITDA of the companies concerned by 15 to 25 percent. Furthermore, according to a report by the Boston Consulting Group (BCG), most of the 10 most innovative companies in the world base their business on data. These include technology companies such as Apple, Amazon and Microsoft.

However, the vast majority of organizations are still at an early stage in the race to digitize and exploit data. Implementing a data culture is not a simple task. It requires a change of mindset throughout the organization, from top management to front-line employees. On the other hand, those companies facing the data-driven world for the first time have the advantage of being able to redefine a data-driven business culture from scratch and harness the power of information to optimize their operations, improve customer experience and deliver better results.

Recognizing the importance and benefits of a data-driven culture for a company at the forefront, they recommend following certain strategies to achieve a complete and successful development.

Defining a data strategy: commitment starts at the top management level

The first step in implementing a data culture is to get buy-in from senior management. Leaders must be the first to embrace and promote the use of data in decision making, establishing a clear vision of how data will benefit the business. This strategy must be effectively communicated to all levels of the organization, setting clear objectives and ensuring secure access to relevant, high-quality data.

Insights to impact, McKinsey & Company, 2022

Empower employees

All employees, regardless of their role, should have a basic understanding of data concepts, starting with data analysis and visualization. Those profiles that will be working with data on a regular basis will need more specialized training in analytics tools and techniques, encouraging continuous and up-to-date learning.

It is important to develop training programs that include workshops, online courses and seminars. For example, the Harvard Business Review study “What Does It Actually Take to Build a Data-Driven Culture?” discussed how Gulf Bank, one of Kuwait’s leading conventional banks, faced the challenge of changing its corporate culture and fostering a digital mindset. The bank chose to design a “data ambassadors” program consisting of a network of individuals who would lead their teams to provide high standards of data quality. Training and support was also provided for all employees, aligned with the slogan “people, then technology”. Therefore, hands-on lab sessions were organized focusing on data analysis and visualization with practical tasks to apply the acquired knowledge. Additionally, Gulf Bank developed the “Data 101” document, they highlighted the impact of data quality on the success of the bank at all levels, which they then included in all new employee onboarding.

Creating a data infrastructure: the right tools and resources

The level of knowledge gained by employees should be reflected in the resources available within the company. Tools such as Tableau, PowerBI or Google Looker Studio are accessible and intuitive for data visualization and analysis. As the amount of data analyzed increases, centralized and structured storage, including database management systems, big data platforms and cloud solutions, could be chosen.

Similarly, establishing data governance processes will be essential to ensure data security. According to the consulting firm McKinsey, data management in the “data-driven enterprises of 2025” will be prioritized and automated to ensure privacy, security and resilience. To achieve this, it compiles some guidelines to follow:

Reinforce the importance of data security throughout the organization.
Increased awareness and active involvement of consumers in individual data protection rights.
Adoption of automated database management technologies for automated provisioning, processing and management of information.
Adoption of cloud-based data resiliency and storage tools to facilitate automated data backup and restoration.

Promoting collaboration: transparency as a fundamental requirement

Once a solid infrastructure is in place and the team is trained in data processing, it will be important to foster a culture of collaboration where employees share data and knowledge openly. This will enable a comprehensive analysis, comprising different perspectives. One strategy to promote cross-departmental collaboration is to create cross-functional teams and workgroups that include employees from different departments. There are numerous collaboration tools that can help share data and work on projects together, such as project management platforms (Trello, Asana), communication tools (Slack, Microsoft Teams) and shared storage software (Google Drive, Dropbox).

Measuring and monitoring progress: indicators to evaluate performance

In line with the initial strategy, key performance indicators (KPIs) should be chosen to measure the progress of implementing a data-driven culture. These indicators may include the frequency of data use in decision making, the number of employees trained in data analytics, and the improvement in business results since the implementation of new practices. Tracking and monitoring these KPIs will allow strategies to be adjusted as needed, adapting to changes in the business and technology environment.

Demonstrate the benefits of dealing with data.

According to Forbes, sharing success stories across departments, showing how data is improving company performance and productivity, can motivate other employees to adopt a data culture.

Implementing a data culture is a journey, not a destination. It requires time, effort and commitment from the entire organization, from senior management to individual employees. Adopting a data culture not only improves decision making, but also positions the company for success in an increasingly competitive, data-driven business environment.

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