The path to a data-driven organization

Today, the most successful organizations use data to gain a competitive advantage, supporting the same critical business decision-making processes. In this way, all analytics applications developed to provide essential information have a set of four components, all of them equally important: data, process, organizational model, technology, people, and culture.


Any informed decision-making process begins with data, which is meaningless in itself. Determining the context is critical for proper analysis and use by organizations, as well as for achieving a broader knowledge of data.

The process and organizational model

Data literacy can be defined as the ability to read, write, and communicate data in its context, including an understanding of sources, analytical methods, applied techniques, and above all, the ability to describe a use case, application, and resultant value. Organizations will need to think deeply about their degree of analytical maturity and the data strategy that must be implemented to gain a competitive advantage in their sector of activity. However, the equation enters four pillars: technology, governance model, organizational structure, and business value.

With regard to technology and the governance model, it is necessary to develop skills in data management, information governance and analytics, as well as define a governance structure with proper definition of responsibilities and decision-making processes. One of the most interesting and least unanimous points among companies is the organizational structure. It is possible to find success cases where the data and analytics activities management model is central and many other cases where there is a decentralized or hybrid model.

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