What is Prescriptive Analytics?
Prescriptive analytics is a type of data analytics — the use of technology to help businesses make better decisions through the analysis of raw data. Specifically, prescriptive analytics factors information about possible situations or scenarios, available resources, past performance, and current performance, and suggests a course of action or strategy. It can be used to make decisions on any time horizon, from immediate to long term.
Why it matters
Prescriptive analytics anticipates what, when and — importantly — why something might happen. After considering the possible implications of each decision option, recommendations can be made regarding which decisions will best take advantage of future opportunities or mitigate future risks. Diwo's Decision Intelligence solutions improve upon prescriptive analytics by providing a recommendation for action relative to a user's business situation or question.
See how Diwo operationalizes Prescriptive Analytics.
Read the decision-intelligence playbooks that put this concept to work at Fortune 50 scale.
Related concepts
Decision intelligence is a data-driven process that enables you to rapidly make faster, more accurate fact-based decisions rather than relying on intuition or gut feel. The approach combines decision-making techniques with AI, ML, contextual intelligence, and automation to generate actionable business recommendations. Rather than replacing human judgment, Decision Intelligence augments human ability to make better and more consistent decisions.
Diagnostic analytics is a form of advanced analytics that examines data or content to answer the question, "Why did it happen?" By using diagnostic analytics, companies can gain insights into the causes of patterns they've observed in their data. It can involve a variety of techniques, including drill-down, data discovery, data mining, and correlations.
Machines generate recommendations for decisions, including an expected business outcome — for example: "Buy X units from supplier Y, then you will save $Z million." The machine proposes the decision, but people make it. The user accepts, rejects, or changes the recommendations for a decision.
Diwo's AI-driven Insight Engine framework delivers contextually relevant views into organizational data and business operations. The framework integrates with Diwo's Business Context graph to capture relationships between entities and their impact on decision-making. The engine analyzes trends and time-varying data changes, automatically surfacing and correlating actionable insights.