What is Evidence in Decision Intelligence?
Evidence represents the pertinent data and analytical logic enabling users to authenticate recommendations from a decision intelligence system. It encompasses the insights that prompted the recommendation alongside supporting data utilized by models and the DI platform. Evidence frequently aligns with essential metrics and KPIs, incorporating projected impacts of recommendations expressed using the same measurement terms.
Why it matters
Given the extensive deployment of machine learning models in contemporary decision-making, business users require comprehension, validation, and confidence in these systems. Evidence addresses this need by making model reasoning accessible and understandable, enabling rapid decision-making through efficient and quick validation of the recommendation.
See how Diwo operationalizes Evidence in Decision Intelligence.
Read the decision-intelligence playbooks that put this concept to work at Fortune 50 scale.
Related concepts
A decision intelligence recommendation represents a very specific, actionable suggestion for what decision should be taken to help achieve an improvement against a key business metric. These recommendations are characterized by being clear, measurable, and tailored to enhance specific business outcomes or initiatives.
Diwo's Decision Intelligence Platform generates an opportunity as a result of its analysis. The platform applies business context to identify areas of performance improvement against specific business metrics. These opportunities serve as the foundation for business recommendations that address or explore potential areas of business improvement.
Explainable artificial intelligence (XAI) comprises processes and methods enabling users to comprehend and trust machine learning algorithm outputs. It describes AI models, their expected impact, and potential biases while characterizing model accuracy, fairness, transparency, and decision-making outcomes.
A Business Context Graph (BCG) is an interconnected dataset that's been enriched with meaning. It enables Diwo's applications to apply reasoning against data sources, supporting complex decision-making processes. Traditional databases suffer from static, shallow context, which limits intelligence capabilities—BCG adds the semantic layer required for decision intelligence.