1. Statistics In Practice
“Statistician Role in Massive Growth of Technology Era”
By: Febriandi Rahmatulloh
Studium General Sharing Sessions Material

2. Short B.I.O
• Name: Febriandi Rahmatulloh
• Occupation: Customer Experience Analytic Expert
Etisalat Mobily –Riyadh - Saudi Arabia
• Education : 2002 - 2005 Bachelor Statistics Gadjah Mada State Univ
2008 - 2010 Magister Statistics Bogor Agri State Institute
• Working Experience :
– 2010-2012 (Manager CRM Insight AXIS Telekom Indonesia)
– 2009-2010 (Sr Analyst XL Axiata)
– 2007-2009 ( Analyst Indonesia Stock Exchange)
– 2006 ( Support Staff OPEC-Vienna Austria)
• Subject Interest, Applied statistics for :
– Data Mining
– Applied Stats Computing
– Applied Analytic for CRM, CEX, CLM
– BTL Marketing
– Big data, Text Mining, Voice Recognition Analytics FRA

3. What can we do after?
• Research Agency
• Government
• Private Business Sector 1. Wealth Opportunity
• National Organization 2. Learn Opportunity
3. Improve Creativity
• International Organization
• Other..
FRA

4. Become Statistician
• Needs to interact with other discipline to make tools works
(Interdiscpliner) but Sense of solving problem with statistical
idea is most important. Core competency are:
– Applied Statistics  In/Out Class
– Business & finance (Macro Micro)  Out Class
– IT  In/Out Class ,Languages & Personality  Out Class
• Nature of statistician daily task are supporting to :
– Understanding Problem
– Finding : Find a hidden pattern/detail to solve problem.
– Explaining : Ability to generate clear and simple
explanations from finding.
FRA

5. Why statistician become sexy Job?
Tight Competition
Technology Massive Growth
Customize & Personalize
Reach Information
Product/Policy
Intelligent Effective & Efficient Business/Organization
War on Analytic
FRA

6. In which Area Statistician Take Part
Miner /Modeller Insight utilization to increase
Extraction Group
And Analytic Group Profitability/efficiency
Cleand & Clear Data Operational
Insight Factory
Execution Group
HERE
REGARDING 3P=PRODUCT PRICE & POLICY
FRA

7. Nature of Data in Massive Technology Era
Super Extra Large Size
Hyper cube Multi Dimension
Text,ASCII,Url etc. High Frequency
Near Real Time
Spatial Temporal Lot of Variable
Transactional
Need IT Knowledge, Business Knowledge and Statistical Sense
For transforming data to become meaningful insight / knowledge
FRA

8. Technical Statistics Method Currently Used
In business analytic process - several statistical tools used for:
1. Develop basic model: Support other model, lifetime valuation and segmentation (K-
means cluster, Cox Regress)
2. Econometric Model : Doing what if analysis, interpolation and extrapolation (forecasting
time series regression)
3. Acquisitions: Predatory acquisition model, best replication
4. Retention : move to competitor prevention (logit reg, CART, C5.0, Quest, CHAID, SVM
Ridge)
5. Stimulation : Propensity product
Criteria to select best model : Logic business, Best Lift, Best Gain, Small gap are between
wizard and ROC curve.
How its run:
1. Factory Wise : Up to several hundred models per year
2. Automatic scheduled .
3. Real time response.
FRA

9. Understanding Business Questions
1. We must make specific customize product /offer/policy for every distinct person /
company  Base segmentation
2. I need to know product purchasing cycle to manage crosseling  Sequential market
basket
3. Can we identify customer that will be go to another competitor product next month
then let us identify what offer that fit for retain them dependency model with
binary/ordinal/multi classifier
4. We must find out what offer that fit to retain customer in every segment and give us
(+) ROI Experimental design + Financial Calc
5. How many base will be retained per month for next 1 year, how many revenue will be
generated from them ridge & financial valuation (FV,PV)
6. We will give special treatment for customer that high circle of friend, centre from that
link/network or bridge from their network Social Networks/Graph Theory
FRA

10. Deliver Result
1. Problem solving mostly unique and simple
2. Board of decision makers only need final result with reasonable
:logic process  and result.
3. Ability to presenting result in simple and clear manner
1. Slide 5-10
2. Begin slide with 1 slide resume of analysis and followed by 1
slide of simple methodology data extraction, logic to solving
problem, variable used, sample used
3. Clear and clear color pattern background of slide
4. Show only pointers not text line /text book
FRA

11. Conclusion
1. Opportunity for statistician in
next several decade still wide
open .
2. It important to learn language and
develop personality since its
become core competency beside
statistical sense it self..
3. Statistics is important but it will
become powerful if we can
combine statistics with other
dicipline (ie. Business and IT).
4. Our ability to fast addapting on
ner techonlogy & method for
solving problem will be critical in
the future regarding massive FRA
growth in tecology .

12. Questions ?
Thank you
FRA