jim grayson, ph.d. management science and operations management professor
TRANSCRIPT
BUSINESS ANALYTICS
Jim Grayson, Ph.D.Management Science and Operations Management Professor
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Agenda
• What is Analytics?• Why should you care?• What should you do?
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Why Should You Care?
JOBS!
MONEY!
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“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
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What is analytics?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.
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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, [http://www.informs.org/ORMS-Today/Public-Articles/October-Volume-37-Number-5/Back-in-Business]
“The essence of analytics lies in the application of logic and mental processes to find meaning in data.”
ITSTATS
BUSINESS
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But you have to change your decision-making culture
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Data Explosion http://tedxtalks.ted.com/video/TEDxPhilly-Robert-J-Moore-The-d
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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
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
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Changes in the Analytical Landscape
Analytical ModelersCustomerService
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
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Co
mp
etit
ive
Ad
van
tag
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Basic Reporting What happened?
Ad Hoc Reporting How many, how often, where?
Dynamic Reporting Where exactly are the problems?
Reporting with Early Warning What actions are needed?
Basic Statistical Analysis Why is this happening?
Forecasting What if these trends continue?
Predictive Modeling What will happen next?
Decision Optimization What is the best decision?
Data Information Intelligence
Advanced Analytics
Basic Analytics
Reporting
Decision Support Decision Guidance
Achieving Success with AnalyticsSAS, Advanced Business Analytics Course
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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.
SAS, Advanced Business Analytics Course
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Now What Should You Do?
• 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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