Las Vegas|October 28 - 30, 2008

Wednesday | Thursday | Presenting Organizations

Select a session below session for a detailed description:

Sessions: Thursday, Oct. 30
1:15 - 2:00 The Other 21 People on the Team: Where Are Your Advanced Modeling Techniques Most Likely to Fail? Looking Beyond Slots and Cards for Data Destination: Customer Insight
Accelerating Merchandising with the Consumer in Mind Through Global Merchandising Processes Credit Risk Management
2:15 - 3:00 Knowledge Storm: Getting Business Executives on Board with Analytics and Data Strategies Survive and Thrive in an Uncertain Economy
Fraud as part of an Enterprise Risk Management Strategy Competitive Advantage: Exploring Price Optimization
3:15 - 4:00 The On-Demand Generation Analytics at American Express – Driving Merchant Value Triangulating Customer Retention Efforts
Transforming Retail into a Customer-Centric Enterprise The Big Bang in Business Intelligence

The Other 21 People on the Team: Where Are Your Advanced Modeling Techniques Most Likely to Fail?
Advanced statistical models depend on the basics of data validity and integrity. The transactional data many rely on to populate these models limits their usefulness. Data usually comes from systems that are geared toward the generation and acquisition of data, but not its validation. The data also does not reflect what might happen if you change all the rules and go beyond the boundaries of existing data. We look to staff modeling projects with the best talent we can find – are we doing the same with those parts of the organization responsible for maintaining the data that feeds the models?

Speaker: Wayne S. Obetz, PhD, Senior Manager, Quantitative Commercial Insight, AstraZeneca

About The Speaker
In addition to his experience in marketing analytics, Wayne Obetz has forecasting experience in the pharmaceutical and consumer packaged goods industries. His research interests include optimizing forecasts for the lifecycle stage of a product and identifying and eliminating inefficient and ineffective forecasting and analytics practices.