Analytical culture in companies: maturity levels and how to build it.

What is analytical culture and why does it matter?

Imagine a company where decisions are guided not by intuition, but by precise data. This is the essence of an analytical culture in companies , an evolutionary process that transforms organizations into data-driven innovation machines. According to the International Institute for Analytics, the average global maturity is only 2.2 on a scale of 5, revealing vast growth potential. In Brazil, a McKinsey study shows that only 12% of companies achieve high data maturity, with digital leaders scoring 66 on the A&DQ scale. Building this culture requires overcoming silos, investing in data literacy, and aligning technology with organizational strategy.

The main levels of analytical maturity

Models like Alteryx and Gartner outline clear stages. At Level 1 (Beginner or Descriptive), analyses remain in departmental silos, focusing on ‘what happened’ via static reports. Level 2 (Local or Diagnostic): data supports specific decisions, automating reports to understand ‘why’. Level 3 (Aspirations): analyses encompass the organization, centralizing data for a unified view. Level 4 (Analytical or Predictive): uses AI to predict scenarios, with 55% of companies increasing investments here. Level 5 (Prescriptive): like Netflix and Facebook, recommends optimal actions, maximizing results. Common mistakes include ignoring culture (91.9% of barriers, per Gartner) and low data quality, costing US$12.9 million annually.

How to build: practical examples and mistakes to avoid

To evolve, start by assessing your stage using tools like the IIA-Alteryx model, covering data, organization, and teams. Example: companies at level 3 prioritize centralized BI for quick decisions, avoiding guesswork. Invest in data literacy for all hierarchical levels. Brazilian case studies show digital leaders excelling in organization and capabilities. Common mistakes: underestimating training (prescriptive block), maintaining silos, and prioritizing tech without culture. Success comes from leadership that champions analytics, increasing productivity by 44% with AI.

Trends: The future of analytical culture

By 2026, AI and automation will accelerate maturity, focusing on prescriptive to predictive scenarios. The market demands data literacy as a requirement, transforming stagnant companies into innovators. Companies that invest now gain an advantage, using data to predict and prescribe, as seen in McKinsey leaders. The path? Start small, scale with culture.[1][2][4]