The first step to becoming data-driven is defining a clear roadmap that can be shared across the organization. This means your strategic vision needs to be translated into an action plan that combines both business, technical and organizational elements.

Many initiatives fail on the ‘garbage in, garbage out’ principle, so it is critical to establish a setup to continuously validate, access, explore and expand the foundation of quality data.

Generating insights from data only creates value once it is in the hands and heads of the right decision-makers. So a key step is to turn the insights from the data into accessible reports and tools that can be used in day-to-day planning and operational discussions.

One of the most common challenges that companies face is changing the mindset and culture around using data. The key to this challenge is in building up the organization’s capabilities and ways of working to drive the levels of data literacy and usage.

To successfully apply AI in day-to-day business, it is crucial to establish strong connections to overall business goals. AI should not be a black box. Transparency will create a continuous learning loop between AI efforts and the organization, promoting governance and new business value.