Roadmap for top managers from descriptive statistics to causal management

Over the past decade, corporate analytics systems have rapidly evolved from manual reporting to scalable business intelligence platforms with advanced dashboards, as well as predictive and recommendation models. As a result, a significant portion of management decisions continue to rely on correlations that rarely answer the key question: what will happen if we intervene and modify pricing policy, inventory levels, technology, training programmes, marketing communications, or institutional rules? The lack of an operational bridge between ‘description/forecast' and “causality” creates systemic risks: false attributions, scaling of ‘false victories,' overconfidence in short-term correlations, and chronic underinvestment in interventions with high expected value but with a weak historical track record in the data. Therefore, there is a growing need for a roadmap that moves the firm from a ‘watch and guess' mode to a mode of managed causality.