The Strategy Map is a strategic tool that enables companies to formulate, control and communicate their strategy and positively influence their performance. Introduced in 2000, the methodology for developing Strategy Maps has evolved over the past two decades, but still relies exclusively on human input. In practice, Strategy Map causalities - the core elements of this tool - are determined by managers' opinions and judgments, which can lead to a lack of accuracy, completeness and longitudinal perspective. Although authors in the literature have pointed out these problems in the past, there are few recommendations on how to address them. In this paper, we propose a methodological framework which uses operational data and data mining techniques to systematize the detection of causalities in Strategy Maps. We apply time series techniques and Granger causality tests to increase the efficiency of such strategic tool. We demonstrate the feasibility and relevance of this methodology using data from skeyes, the Belgian air traffic control company.