original definition predictive analytics spss jan 15, 2003 intriduction slides
DESCRIPTION
In 2003 the SPSS Senior Management & Marketing under the leadership of Jack Noonan, Dyke Hensen & Matt Cutler coined the phrase "Predictive Analytics" to explain to the market and to the analysts how SPSS differed from BI companies like BO and Cognos. This file contains the presentation by Matt Cutler introducing PA and the definition to the SPSS employees on January 15 2003TRANSCRIPT
Copyright 2003, SPSS Inc. Copyright 2003, SPSS Inc. Copyright 2003, SPSS Inc. Copyright 2003, SPSS Inc. 11
Predictive Analytics: Defined
Predictive Analytics: Defined
Matt CutlerVice President, Corporate Marketing
January 15, 2003
Copyright 2003, SPSS Inc. Copyright 2003, SPSS Inc. 2
ObjectiveObjective
Overall impression Term is widely used both internally and externally Market has little common agreement around
exactly what the term means
Definition The 5 C’s of Corporate Communications: clear,
concise, compelling, credible, and coherent
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ApproachApproach
Value statement One sentence that communicates the core value
of Predictive Analytics.
Definition: Several paragraphs Four paragraphs of detailed, dense content that
cover all of the facets Predictive Analytics
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Value StatementValue Statement
Predictive analytics connects data to effective action by drawing reliable
conclusions about current conditions and future events.
Copyright 2003, SPSS Inc. Copyright 2003, SPSS Inc. 5
Definition (Lots Here)Definition (Lots Here)
Predictive analytics, like enterprise resource planning (ERP) and customer relationship management (CRM), is both a business process and a set of related technologies. Predictive analytics leverages an organization’s business knowledge by applying sophisticated analytic techniques to enterprise data. The resulting insights can lead to actions that demonstrably change how people behave as customers, employees, patients, students, and citizens.
The predictive analytics process begins by exploring how specific business issues relate to data describing people’s characteristics, attitudes, and behavior. These numeric and free-form data sets, which originate from both internal systems and third party providers, are cleansed, transformed, and evaluated using statistical, mathematical, and other algorithmic techniques. These techniques generate models for classification, segmentation, forecasting, pattern recognition, sequence and association detection, anomaly identification, profiling, propensity scoring, rule induction, text mining, and advanced visualization.
Combining predictive analytic models with organizational business knowledge provides insight into such critical issues as customer acquisition and retention, up-selling and cross-selling, fraud detection, and outcome improvement. Through measuring uncertainty surrounding these issues, predictive analytics enables proactive risk management, refining key decision making processes through controlled, iterative testing of potential actions and their likely intended—and unintended—consequences. These findings and their corresponding business rules can then be deployed within front-line operational systems to identify new revenue opportunities, measurable cost savings, repeatable process improvements, and sustainable competitive advantages.
Predictive analytics carries strategic and tactical ramifications for organizations that recognize the inherent value locked within their existing enterprise data. Strategically, predictive analytics provides a quantitative foundation for rapidly identifying, objectively evaluating, and confidently pursuing new market opportunities. Tactically, predictive analytics identifies precisely whom to target, how to reach them, when to make contact, and what messages should be communicated.
Top Level OverviewTop Level Overview
Data & AnalysisData & Analysis
Applications & ImpactApplications & Impact
Major RamificationsMajor Ramifications
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Definition: 1st ParagraphTop Level OverviewDefinition: 1st ParagraphTop Level Overview
Predictive analytics, like enterprise resource planning (ERP) and customer relationship management (CRM), is both a business process and a set of related technologies. Predictive analytics leverages an organization’s business knowledge by applying sophisticated analytic techniques to enterprise data. The resulting insights can lead to actions that demonstrably change how people behave as customers, employees, patients, students, and citizens.
Copyright 2003, SPSS Inc. Copyright 2003, SPSS Inc. 7
Definition: 2nd ParagraphData & AnalysisDefinition: 2nd ParagraphData & Analysis
The predictive analytics process begins by exploring how specific business issues relate to data describing people’s characteristics, attitudes, and behavior. These numeric and free-form data sets, which originate from both internal systems and third party providers, are cleansed, transformed, and evaluated using statistical, mathematical, and other algorithmic techniques. These techniques generate models for classification, segmentation, forecasting, pattern recognition, sequence and association detection, anomaly identification, profiling, propensity scoring, rule induction, text mining, and advanced visualization.
Copyright 2003, SPSS Inc. Copyright 2003, SPSS Inc. 8
Definition: 3rd ParagraphApplications & ImpactDefinition: 3rd ParagraphApplications & Impact
Combining predictive analytic models with organizational business knowledge provides insight into such critical issues as customer acquisition and retention, up-selling and cross-selling, fraud detection, and outcome improvement. Through measuring uncertainty surrounding these issues, predictive analytics enables proactive risk management, refining key decision making processes through controlled, iterative testing of potential actions and their likely intended—and unintended—consequences. These findings and their corresponding business rules can then be deployed within front-line operational systems to identify new revenue opportunities, measurable cost savings, repeatable process improvements, and sustainable competitive advantages.
Copyright 2003, SPSS Inc. Copyright 2003, SPSS Inc. 9
Definition: 4th ParagraphMajor RamificationsDefinition: 4th ParagraphMajor Ramifications
Predictive analytics carries strategic and tactical ramifications for organizations that recognize the inherent value locked within their existing enterprise data. Strategically, predictive analytics provides a quantitative foundation for rapidly identifying, objectively evaluating, and confidently pursuing new market opportunities. Tactically, predictive analytics identifies precisely whom to target, how to reach them, when to make contact, and what messages should be communicated.
Copyright 2003, SPSS Inc. Copyright 2003, SPSS Inc. 10
JB BigWig & Wolfgang StatsJB BigWig & Wolfgang Stats
Predictive analytics, like enterprise resource planning (ERP) and customer relationship management (CRM), is both a business process and a set of related technologies. Predictive analytics leverages an organization’s business knowledge by applying sophisticated analytic techniques to enterprise data. The resulting insights can lead to actions that demonstrably change how people behave as customers, employees, patients, students, and citizens.
The predictive analytics process begins by exploring how specific business issues relate to data describing people’s characteristics, attitudes, and behavior. These numeric and free-form data sets, which originate from both internal systems and third party providers, are cleansed, transformed, and evaluated using statistical, mathematical, and other algorithmic techniques. These techniques generate models for classification, segmentation, forecasting, pattern recognition, sequence and association detection, anomaly identification, profiling, propensity scoring, rule induction, text mining, and advanced visualization.
Combining predictive analytic models with organizational business knowledge provides insight into such critical issues as customer acquisition and retention, up-selling and cross-selling, fraud detection, and outcome improvement. Through measuring uncertainty surrounding these issues, predictive analytics enables proactive risk management, refining key decision making processes through controlled, iterative testing of potential actions and their likely intended—and unintended—consequences. These findings and their corresponding business rules can then be deployed within front-line operational systems to identify new revenue opportunities, measurable cost savings, repeatable process improvements, and sustainable competitive advantages.
Predictive analytics carries strategic and tactical ramifications for organizations that recognize the inherent value locked within their existing enterprise data. Strategically, predictive analytics provides a quantitative foundation for rapidly identifying, objectively evaluating, and confidently pursuing new market opportunities. Tactically, predictive analytics identifies precisely whom to target, how to reach them, when to make contact, and what messages should be communicated.
Business CaseBusiness Case
Technology SpecificsTechnology Specifics
Working TogetherWorking Together
Organizational ImpactOrganizational Impact
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Definition & SPSS TechnologyDefinition & SPSS Technology
Statistics offerings
Data mining & text mining offerings
Web analytics offerings
Market research offerings
OLAP, reporting & visualization offerings
Copyright 2003, SPSS Inc. Copyright 2003, SPSS Inc. 12
Predictive Analytics: DefinedPredictive Analytics: Defined
Predictive analytics connects data to effective action by drawing reliable
conclusions about current conditions and future events.