Date: Wednesday, November 29, 2017
Time: 12:00 - 14:00
Venue: Tokyo American Club, New York Bridge Room
Speaker: Neil Seeman, Faculty, Institute of Health Policy, Management & Evaluation, Dalla Lana School of Public Health
Hosting Committees: Healthcare Committee, Sales Development Committee
Member Fee: ¥4,000
Guest Fee: ¥7,400
Meal: Plated Lunch Course
Registration/Cancellation Deadline: Friday, November 24, 12:00
What's the best way to measure emerging risks in real-time in a changing world? When it comes to data for prediction, it turns out that bigger is not better. It is a mistake to assume that larger data sets are better than smaller ones, or that old concepts such as “representativeness” of non-random sampling are bias-free. In this talk, Professor Neil Seeman, a leading authority in the science of randomness in data collection, will introduce some key concepts in data sampling that can help marketers improve the accuracy of their predictions.
Starting with some tried and tested ideas from basic science, Professor Seeman will show how constantly questioning our assumptions about data and understanding the limitations of our knowledge can prevent predictions from going astray. He will also discuss a new method of random sampling of general Internet users from all over the world. This method accurately predicted Mr. Trump's win in the U.S. presidential election, the turnout model that decided Brexit in the UK, the Fall of Mubarak during the Arab Spring in 2011, and the precise outcome of the Italian constitutional referendum in 2016.
Don't miss this opportunity to learn how the latest discoveries in data sampling can help us see into the future.
About the Speaker:
Professor Neil Seeman is the developer of RDIT, which randomly samples general Internet users all over the world. He founded RIWI Corp., a global survey, message testing and predictive analytics technology company collecting data from every part of the world. As CEO of RIWI, Neil leads overall strategy for the company globally, with a focus on healthcare and international security solutions. RIWI's innovative technology reinvented randomness in data collection and has won numerous research industry innovation awards.
Professor Seeman’s academic work has appeared in major journals such as Nature, Synapse, the Canadian Medical Association Journal, the Journal of Affective Disorders, Healthcare Quarterly, Healthcare Papers, and Healthcare Management Review.
John W. Carlson III, Chair
William Bishop, Andrew Joyce, Yuko Kidoguchi, Takeo Morooka, Toshio Nagase, R. Byron Sigel, Vice Chairs
Marie Kissel, Board Liaison
ACCJ Healthcare Committee
Carlo La Porta, Thomas Shockley, Eric Wedemeyer, Co-Chairs
Reiko Osa, Kjell Yadon, Vice Chairs
Nancy Ngou, Board Liaison
ACCJ Sales Development Committee
NOTE 1: This event is OFF THE RECORD.
NOTE 2: If you cancel after the stated deadline, the full meeting fee will be charged to your account. Sorry, no substitutions or walk-ins.