Decision Intelligence (decision-making intelligence) is a discipline that combines data science, artificial intelligence, and behavioral sciences to structure, model, and improve the way organizations make decisions. It is not limited to generating predictions, but rather connects those analyses with concrete actions and their consequences, integrating the business context into the process.
Its relevance lies in the fact that it closes the gap between data and decision. Many companies accumulate predictive models that are never translated into useful actions; Decision Intelligence provides a framework to ensure that analysis truly influences results. It usually relies on:
- Causal models that estimate the effect of each option.
- Simulations of alternative scenarios.
- Business rules that reflect constraints and objectives.
A practical example would be a retail chain that not only predicts demand, but also automatically recommends how much to restock in each store, weighing costs, risk of stockouts, and margins. The key nuance is that it prioritizes decision quality, not just model accuracy.