1. ITU Workshop on “Quality of Service and Quality of Experience of Multimedia Services in Emerging Networks” (Istanbul, Turkey, 9-11 February 2015) Network Analytics – Taking action on Big Data Alberto Pérez Business Development Consultant, Omnitele alberto.perez@omnitele.com

2. ©Omnitele Ltd. 2015 2 agenda 1.Introduction −About Omnitele 2.Big Data Conceptualisation 3.Case Study Network Analytics for ROI Optimisation 4.Take-outs Summary

3. ©Omnitele Ltd. 2015 3 Maximised Experience, Minimised Cost We provide consulting and expert services for telecom operators and regulators in network strategy, design and quality assurance. Our mission is to maximise mobile subscriber quality of experience and minimise operator network expenditures. Delivering Omnitele Experience The company was founded in 1988 to set up world’s first GSM network. Since then we have completed over 1000 projects in over 80 countries around the globe. Always delivering Omnitele Experience – a fact proven by our long lasting client relationships. International And Independent Our headquarters is located in Helsinki, Finland. We have local presence in the Netherlands and the Hashemite Kingdom of Jordan. Our company is owned by Finnish telecom investors and we are independent of operator groups and network vendors. The Omnitele Way Our unique way of working sets us apart from the competition and gives us a strong identity in the world of telecommunications. We call this the Omnitele Way, which means being Straightforward, Trusted and Intelligent. Omnitele 1-pager: company info in nutshell, can be used in all reports, proposals etc to add company info in concise fashion www.omnitele.com

4. ©Omnitele Ltd. 2015 4 content title Technology Strategy Design and Optimisation Audit and Benchmark Performance Management our services maximised customer experience minimised network cost

5. ©Omnitele Ltd. 2015 5 agenda 1.Introduction −About Omnitele 2.Big Data Conceptualisation 3.Case Study Network Analytics for ROI Optimisation 4.Take-outs Summary

6. ©Omnitele Ltd. 2015 6

7. ©Omnitele Ltd. 2015 7 Conceptualisation Big Data Popular term used to describe the exponential growth and availability of data, both structured and unstructured. In most enterprise scenarios the data is too big or it moves too fast or it exceeds current processing capacity. Big data has the potential to help companies improve operations and make faster, more intelligent decisions. Volume excessive data volume was an issue – with decreasing storage costs the issue is how to determine relevance within large data volumes or use analytics to create value from relevant data Velocity data is streaming in at unprecedented speed and must be dealt with in a timely manner – reacting quickly enough to deal with data is a challenge for most organisations Variety data today comes in all types of formats (structured = databases / unstructured = text documents, email, video, audio, social media, etc.) – managing, merging and governing different varieties of data is not a piece of cake

8. ©Omnitele Ltd. 2015 8 agenda 1.Introduction −About Omnitele 2.Big Data Conceptualisation 3.Case Study Network Analytics for ROI Optimisation 4.Take-outs Summary

9. ©Omnitele Ltd. 2015 9 Levels of Quality and Capacity Optimisation Traffic, Terminal, and Service Forecast Capacity Assurance Predict Quality and Capacity Bottlenecks Recommend most effective solution to sustain QoS targets Cost Optimisation Evaluate Cost vs. Gain of each upgrade Recommend cost optimised solution to sustain QoS targets ROI Optimisation Predict revenue return from expansions Network investment plan with maximised ROI Network Cost Billing data

10. ©Omnitele Ltd. 2015 10 ROI Optimisation for LTE 1.Link QoS improvement to incremental data usage 2.Link data increase to incremental revenues 3.Forecast incremental revenue from LTE per site 4.Prioritise LTE expansions based on ROI 5.Quantify optimal rollout plan for coming years

11. ©Omnitele Ltd. 2015 11 Linking QoS to Data Usage Big impact from poor to moderate Impact saturates with high quality Link is not linear, and very high data rates do not impact notably on data usage

12. ©Omnitele Ltd. 2015 12 Linking Data usage to Revenues Doubling data provides +30% revenue Link differs between subscription types, and thus also between cells

13. ©Omnitele Ltd. 2015 13 If LTE in every site – How customers return revenue? LTE has same impact on traffic, but revenue impact is very different LTE has same impact on traffic, but revenue impact is different Revenue return does not always correlate with incremental data usage STD 89% LTE incremental revenue (USD) during 2015

14. ©Omnitele Ltd. 2015 14 Data increase don’t always correlate with revenues Impact on data 12GB/day Revenue impact 1. year 4.7kUSD Impact on data 10GB/day Revenue impact 1. year 5.8kUSD LTE impact on data and revenue Reason for disparity comes from different customer base

15. ©Omnitele Ltd. 2015 15 Service-base dictates revenue return-rate Most data plans with high allowance utilisation (>70%) = better potential to increase ARPU Many data plans with low allowance utilisation (<10%) = customers with limited potential to increase ARPU Revenue return from data growth can be improved proactively:  Migrate Blackberry to Mobile internet  Revisit bundle offers to improve allowance utilisation Subscription distribution (by % of data)

16. ©Omnitele Ltd. 2015 16 Concluding LTE Business Case and Rollout plan Already 45 sites profitable to implement in the city and main highways 40 fill-in sites around city profitable for 2016 rollout 25 sites outside city not profitable end of 2016, business case verified during 2016 LTE capex covered in 3 years 50% of capex covered during 2015 2015 2016 2017  30% of capex covered during 2016 10% of capex covered during 2016

17. ©Omnitele Ltd. 2015 17 Benefit to operator from Value Based LTE Rollout Plan With Omnitele Value Based Expansion Plan, operator gains maximised impact on bottom line from the LTE rollout:  24% better LTE revenues during rollout, compared to rollout plan relying only on traffic analysis  45% better LTE revenues during rollout, compared to rollout plan relying on only areal selection

18. ©Omnitele Ltd. 2015 18 agenda 1.Introduction −About Omnitele 2.Customer Experience Challenge KPIs that capture End-User experience 3.Methodologies for Monitoring End-User QoS Different approaches – one goal 4.Take-outs Summary

19. ©Omnitele Ltd. 2015 19 Summary 1.Big Data is not a thread, but an opportunity for gaining insights that facilitate decision making 2.Data volume storage is not an issue anymore – MNOs should take advantage and use analytics to create value 3.Omnitele use case provides benefits only using available structured data. Opportunities raise if taking into account more sources

20. ©Omnitele Ltd. 2015 20 content title can be 2 rows thank you for your attention! questions

21. ©Omnitele Ltd. 2015 21 Contact details Omnitele Ltd NamePhone+358 9 695 991 TitleEmailcontact@omnitele.com PhoneWebsitewww.omnitele.com Email AddressOmnitele Ltd. Mäkitorpantie 3B P.O. Box 969 00101 Helsinki, Finland We answer Alberto Pérez Business Development Consultant +358 40 537 80 52 alberto.perez@omnitele.com

22. ©Omnitele Ltd. 2015 22 maximised customer experience minimised network cost www.omnitele.com