Jim Grayson, Ph.D. Management Science and Operations Management Professor

Agenda What is Analytics? Why should you care? What should you do? 2

Why Should You Care? JOBS! MONEY! 3

“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 4

What is analytics? 5 In that sense, then, “business analytics” can be defined as the broad use of data and quantitative analysis for decision- making within organizations. It encompasses query and reporting, but aspires to greater levels of mathematical sophistication. It includes analytics, of course, but involves harnessing them to meet defined business objectives. Business analytics empowers people in the organization to make better decisions, improve processes and achieve desired outcomes. It brings together the best of data management, analytic methods, and the presentation of results—all in a closed-loop cycle for continuous learning and improvement The New World of “Business Analytics”, Thomas Davenport, March 2010.

6 Better Decisions “… because of big data, managers can measure, and hence know, radically more about their businesses, and directly translate that knowledge into improved decision making and performance.”

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Back in Business, by Ronald K. Klimberg and Virginia Miori, OR/MS Today, Vol 37, No 5, October 2010, [ Articles/October-Volume-37-Number-5/Back-in-Business] Articles/October-Volume-37-Number-5/Back-in-Business 9 “The essence of analytics lies in the application of logic and mental processes to find meaning in data.” IT STATS BUSINESS

10 But you have to change your decision-making culture

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

14 Big Data: The Next Frontier -- Demand for deep analytical talent in the United States could be 50 to 60 percent greater than its projected supply by 2018

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Changes in the Analytical Landscape 21 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

Changes in the Analytical Landscape 22 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

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

Value: Ability to Predict  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. 24 SAS, Advanced Business Analytics Course

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Now What Should You Do? 26 Manage your own set of capabilities: what is your “personal brand”? Proactively “manage” your education – find a mentor; get career help; be a learner “Begin with the end in mind” Don’t imagine you can avoid data

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