1. BUSINESS ANALYTICS

2. “THE EXTENSIVE USE OF DATA, STATISTICAL AND QUANTITATIVE ANALYSIS, EXPLANATORY AND PREDICTIVE MODELS, AND FACT-BASED MANAGEMENT TO DRIVE DECISIONS AND ACTIONS.” DAVENPORT AND HARRIS (2007) COMPETING ON ANALYTICS: THE NEW SCIENCE OF WINNING 2

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4. Back in Business, by Ronald K. Klimberg and Virginia Miori, OR/MS Today, Vol 37, No 5, October 2010, [http://www.informs.org/ORMS-Today/Public-Articles/October-Volume-37-Number-5/Back-in-Business]http://www.informs.org/ORMS-Today/Public-Articles/October-Volume-37-Number-5/Back-in-Business 4 “The essence of analytics lies in the application of logic and mental processes to find meaning in data.”

5. ANALYTICS Big Data Big Money Big Change Big Benefits Big Demand 5

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8. 8 Data Explosionhttp://tedxtalks.ted.com/video/TEDxPhilly-Robert-J-Moore-The-d

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11. Competing on Analytics by Thomas Davenport, HBR (January 2006) 11

12. 12 http://www.moneyball-movie.com/trailer

13. http://movies.yahoo.com/feature/moneyball.html Competing on Analytics by Thomas Davenport, HBR (January 2006) 13

14. CHANGES IN THE ANALYTICAL LANDSCAPE Analytical Modelers Management Historically… Historically, analytics have typically been handled in the “back office,” and information was shared only by a few individuals. Models SAS, Advanced Business Analytics Course 14

15. CHANGES IN THE ANALYTICAL LANDSCAPE Analytical Modelers Customer Service Retail Logistics Promotions OPERATIONS TARGET Customers Stockholders Suppliers Employees Now… Now analytics are being pushed out to the “front office” and are directly impacting company performance. There are clear, tangible benefits that management will track. Data mining is a critical part of business analytics. Proliferation of Models SAS, Advanced Business Analytics Course 15

16. THE DATA Experimental Opportunistic PurposeResearchOperational ValueScientificCommercial GenerationActivelyPassively controlledobserved SizeSmallMassive HygieneCleanDirty StateStaticDynamic SAS, Advanced Business Analytics Course 16

17. THE METHODOLOGY: WHAT WE LEARNED NOT TO DO Prediction is more important than inference. Metrics are used “because they work,” not based on theory. p-values are rough guides rather than firm decision cutoffs. Interpretation of a model might be irrelevant. The preliminary value of a model is determined by its ability to predict a holdout sample. Long-term value of a model is determined by its ability to continue to perform well on new data over time. Models are retired as customer behavior shifts, market trends emerge, and so on. SAS, Advanced Business Analytics Course 17

18. USING ANALYTICS INTELLIGENTLY Intelligent use of analytics results in the following: Better understanding of how technological, economic, and marketplace shifts affect business performance Ability to consistently and reliably distinguish between effective and ineffective interventions Efficient use of assets, reduced waste in supplies, and better management of time and resources Risk-reduction via measurable outcomes and reproducible findings Early detection of market trends hidden in massive data Continuous improvement in decision making over time SAS, Advanced Business Analytics Course 18

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23. Competitive Advantage Basic Reporting What happened? Ad Hoc Reporting How many, how often, where? Dynamic ReportingWhere exactly are the problems? Reporting with Early WarningWhat actions are needed? Basic Statistical Analysis Why is this happening? Forecasting What if these trends continue? Predictive Modeling What will happen next? Decision OptimizationWhat is the best decision? Data Information Intelligence Advanced Analytics Basic Analytics Reporting Decision Support Decision Guidance Achieving Success with Analytics SAS, Advanced Business Analytics Course 23

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26. HIRING SUCCESS 26

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28. 28 QUAN 4630: Business Analytics

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31. OPPORTUNISTIC DATA Operational data is typically not collected with data analysis in mind. Multiple business units produce a silo-based data system. This makes business analytics different from experimental statistics and especially challenging. SAS, Advanced Business Analytics Course 31