descriptive analytics
What It Means
Descriptive analytics is like being a detective for your business data - it looks at what already happened and explains why it happened. It takes your historical data and turns it into clear reports and insights that help you understand the root causes behind your business outcomes.
Why Chief AI Officers Care
Understanding why events occurred enables better decision-making, helps prevent recurring problems, identifies what drives success so it can be replicated, and provides the foundation for compliance reporting and stakeholder communications.
Real-World Example
When quarterly sales dropped 15%, descriptive analytics might reveal it was due to a combination of a competitor's new product launch, delayed shipments from a key supplier, and reduced marketing spend in two regions - giving leadership specific areas to address.
Common Confusion
Many executives think descriptive analytics predicts the future, but it only explains the past. It tells you why something happened, not what will happen next - that requires predictive analytics.
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare, descriptive analytics analyzes historical patient data, clinical outcomes, and operational metrics to ide...
Finance: In finance, descriptive analytics helps CFOs and finance teams analyze past financial performance by examining historica...
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Includes:
- 6 industry-specific applications
- Relevant regulations by sector
- Real compliance scenarios
- Implementation guidance
Technical Definitions
NISTNational Institute of Standards and Technology
"Insights, reporting, and information answering the question, “Why did something happen?” Descriptive analytics determines information useful to understanding the cause(s) of an event(s)."Source: IEEE_Guide_IPA
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