This presentation was made for a hypothetical telecom company, to be presented to the management, persuading them to adopt big data/analytics in company.

1. Adopting Analytics
Amarjeet Singh
Bitanshu Das
Namita Pandey
Roma Agrawal
“Key To The Future”

2. AGENDA
 What are the current challenges faced by us?
 How can analytics help us?
 What are our challenges in implementing analytics?
 What are our proposed plans for implementing analytics?
 What benefits will we reap?
 What will be our next steps?

3. “ In God we trust, all others bring data”
- W. Edwards Deming

6. AGENDA
 What are the current challenges faced by us ?
 How can analytics help us ?
 What are our challenges in implementing analytics ?
 What are our proposed plans for implementing analytics?
 What benefits will we reap ?
 What will be our next steps ?

7. Reasons :
Flat ARPU
 Increased market competition causing slashed tariffs
 SMS volume hampered by messengers like WhatsApp & WeChat
 Call volume decreased by apps like Viber & Skype
 Unlimited data packs
 Network Congestion

9. Reasons :
Customer Churn
 Competitors introducing new plans & services
 Service Quality
 Consumer Psychology

10. AGENDA
 What are the current challenges faced by us ?
 How can analytics help us ?
 What are our challenges in implementing analytics ?
 What are our proposed plans for implementing analytics?
 What benefits will we reap ?
 What will be our next steps ?

11. Fixing Flat ARPU
 Personalized advertisement
 Innovative Customized tariffs
 Value added services for high end customers
 Monetize customer data
 Capped data plans

12. Preventing
Customer Churn
 Customer Understanding
 Social Media and Sentiment Analytics
 Predict the Reason and Solve
 Innovate and Deliver Constantly

13. AGENDA
 What are the current challenges faced by us ?
 How can analytics help us?
 What are our challenges in implementing analytics?
 What are our proposed plans for implementing analytics?
 What benefits will we reap ?
 What will be our next steps ?

15.  New data center
setup
 Depends on choice
of implementation
(hiring analysts or
partner with
analytics service
providers)
Budget

16. AGENDA
 What are the current challenges faced by us ?
 How can analytics help us ?
 What are our challenges in implementing analytics ?
 What are our proposed plans for implementing analytics?
 What benefits will we reap ?
 What will be our next steps ?

17. Data
Implementation
 Develop an enterprise-wide data architecture.
Analytical Model
 Hiring/Training analytics professionals.
 Identify key areas for deploying analytics.
Tools
 Setting up of hardware, intuitive tools and software

18. AGENDA
 What are the current challenges faced by us ?
 How can analytics help us ?
 What are our challenges in implementing analytics ?
 What are our proposed plans for implementing analytics?
 What benefits will we reap ?
 What will be our next steps ?

19.  Better Management and Operation of cell phone tower
 Attractive plans and services
 Customer Satisfaction

20. Increase in ARPU
 Our Current ARPU :
 Data ARPU – 56Rs.
 Voice ARPU – 143Rs.
After implementing big data analytics
 Data ARPU
 Almost 11% increase in the 1st
year
 34% increase in 2nd year
 Voice ARPU
 More Than 15% increase in 1st
year
 Almost 33% increase in 2nd
year.
Increase in ARPU
56
143
62
165
75
190
DATA ARPU VOICE ARPU
3rd Qrtr 2014 3rd Qrtr 20115 3rd Qrtr 2016

21. Decrease in Churn Rate
 Present Current Churn Rate :
21%
After implementing big data
analytics
 Churn Rate in 1st Year : 10%
 Churn Rate in 2nd Year : 6%
Decrease in Churn Rate
21%
10%
6%
CHURN RATE
3rd Qrtr 2014 3rd Qrtr 20115 3rd Qrtr 2016

22. Success Stories
 Global Telecom (Philippines)
 Expected one-year payback
period.
 Uses big data analytics to
improve effectiveness of
promotion by 600%.
 More than 95% reduction in
the time and cost of
developing new promotions.
 Improved uptake of services
through the smart delivery of
promotional offers
 Increased market share and
revenue
700
600
500
400
300
200
100
0
Big Data Analytics Effect on
Increase in
Sales %age
Promotion
Older Promotional Model
New Promotional Model

23. Success Stories
 Ufone (Pakistan)
 Deploying big data analytics
to improve marketing offer
acceptance rate 25% to
50%.
 Had a churn rate of 2.4%-
3% per month before
changing strategies.
 Present churn rate stands
4%
3%
3%
2%
2%
1%
1%
at 0.4% per month. 0%
Big Data Analytics Effect on Churn
Decreasing
Churn Rate
Rate
Older Churn Rate
Present Churn Rate

24. Success Stories
 XO Communications (US)
 Using predictive analytics
to improve customer
experience resulted in $15
million per year.
 ROI 376%
 Churn rate reduction 8%
first year and 18% second
year.
Fig – Initial Investment

26. 6000000
5000000
4000000
3000000
2000000
1000000
0
Financial Analysis
Pre-Start Year 1 Year 2
Net Cash flow before taxes Net Cash flow after taxes

28. AGENDA
 What are the current challenges faced by us ?
 How can analytics help us ?
 What are our challenges in implementing analytics ?
 What are our proposed plans for implementing analytics?
 What benefits will we reap ?
 What will be our next steps ?

29.  Feasibility Study
 The Choice : Outsourcing or setting up a new department

30. “CSPs that act swiftly to capitalize on the
insights locked inside the vast volume, velocity
and variety of big data will position themselves
to keep ahead of the competition, improve
customer experience, drive new products,
increase productivity, predict future trends, and
especially, make money. “

31. Questions ??

32. Thank you…