Automated analysis of external environment factors for strategic management
a conceptual and methodological framework
Abstract
The external environment of organisations has become increasingly turbulent and interconnected. Political shocks, regulatory changes, technological disruptions, social shifts and environmental pressures interact in complex ways and propagate quickly across sectors and regions. Traditional approaches to environmental analysis in strategic management-such as expert-based PESTEL matrices and qualitative industry reports-are often slow, subjective and difficult to update systematically. At the same time, organisations have access to a growing volume of heterogeneous data, including official statistics, administrative registers, news flows, regulatory texts, company reports and market indicators.
This article develops a conceptual and methodological framework for the automated analysis of external general and specific environment factors. The framework integrates classic strategic-management concepts with contemporary data and AI techniques. It is built around a transformation chain from factor to event, indicator and signal for decision support. The proposed system relies on multilingual natural language processing (NLP) to extract factor-related events from unstructured text, a knowledge representation layer (ontology and knowledge graph) to structure factors, actors and relations, and time-series and causal models to quantify the evolution and effects of environment indicators. Composite indices of the external environment are constructed with explicit treatment of uncertainty. Validation combines backtesting, sensitivity analysis and expert assessment.
The article is conceptual and methodological in nature, but it is designed with empirical application in a few sectors over the period 2018–2025. The expected contribution is a portable methodology and prototype architecture that organisations can adapt for systematic monitoring of risks and opportunities in their external environment, and which can later be integrated with forecasting and financial-analysis systems.
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