THE 80/20 RULE IN BIGDATA BY JOSE BERENGUERES & DMITRY EFIMOV Smart Data Summit Dubai | 25 - 26 May 2015 How to optimise your Loyalty program from a non-value-added-activity point of view and other stuff case based on: Airline new customer tier level forecasting for real-time resource allocation of a miles program http://www.journalofbigdata.com/content/1/1/3
Smart data sumit DXB 2015: 80/20 for Airlines
Aug 06, 2015
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THE 80/20 RULE IN BIGDATA
BY JOSE BERENGUERES & DMITRY EFIMOV
Smart Data Summit Dubai | 25 - 26 May 2015
How to optimise your Loyalty program from a non-value-added-activity point of
view and other stuff
case based on: Airline new customer tier level forecasting for real-time resource allocation of a miles program http://www.journalofbigdata.com/content/1/1/3
BACKGROUND: ROBOTICS
BACKGROUND: DESIGN THINKING
BACKGROUND: BIOINSPIRED MANUFACTURING
Loyalty miles program (15,000,000 rows)
demographics, miles, flights
?
Linear Forecasting (42%)
80/20
Today ?
Today ?
Rank, Resource optimisation
Testing the limits: 2 weeks
ordered by miles max to min.
HOW IT WAS DONE…
1.Time Shift CRM events to present*
2.Feature Extraction (Cluster
Dummy Method)
3.Generalized Boosting Machine
(Tree Search)
4.Generalized Linear Model
(Regression based)
5.Blending with grid search (+5%)
*the computer understand dates but it understands better them in terms of “how many days ago”
Conclusion
Software Lock-ins
Asking the right question is the hard part of big data
Huge opportunities in 80/20: Waste optimisation
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