1. © 2015 TM Forum | 1 Analytics Big Data Repository (ABDR) ABDR Catalyst Project: Phase 5

2. © 2015 TM Forum | 2 The Digital Service Provider Challenge 2 I own a wealth of data and need to extract value through analytics I have a data goldmine I want to test multiple use cases and leveraging actionable intelligence from my data I need to innovate My data comes from disparate sources and is often duplicated in various applications I need the complete picture As a CSP, becoming a Digital Service Provider (DSP) through digital transformation, I face many challenges: I need a 360-degree customer view in order to deliver enriched, personalized digital experiences I rely on data analytics the cost to extract and analyze volumes of data I am hindered by For maintaining revenue assurance, guaranteeing privacy and data security, while delivering process improvements I am accountable

3. © 2015 TM Forum | 3 Analytics Big Data Repository (ABDR) Key Benefits:  Boosts innovation by ensuring that the data is highly available  Faster time to implement new use cases and test new concepts  Avoiding data replication by organizing data in a way that you can reuse it efficiently  Saving in ETL costs & time  Savings in hardware costs (storage & processing power) The ABDR is a unified layer that provides standard data definitions in order to support multiple use cases and multiple analytics systems (defined in GB979-D)

4. © 2015 TM Forum | 4 Analytics Big Data Repository (ABDR) Analytics Big Data Repository (Hadoop / Columnar DB / unstructured DB / DB) Tool 1 Unlimited Use Cases Tool 2 Unlimited Use Cases Tool 3 Unlimited Use cases Tool n Unlimited Use cases XDRsDPICRMSocial Media ETL / ELT / Map Reduction Streaming Processing Internal data (OLAP/ DB / Hadoop …)

5. © 2015 TM Forum | 5 Use Cases - Demonstrating Business Value ABDR Use Cases Guarding Revenue Revenue Assurance Fraud Management Prescriptive Analytics Cognitive Troubleshooting Predictive Customer Intelligence Margin Assurance Individual services driving customer and product offering profitability Roaming and 3rd Party Margins Multi-level Margin Analysis Customer Experience in a Hyper-connected World Location based targeted ad triangulation Customer Experience – FAN 360, OTT Solution Digital oil field – Video data mining Operational Benefits  Faster Implementation and ROI  Lower CAPEX. Data analysis, integration, ETL/ELT design and implementation, performed once and reused.  Lower OPEX – simpler maintenance and lower storage and processing footprint  Leverage Entities, Business Process across Initiatives  Single Source of Truth – Data Model  End to end solution for content starting from production to distribution & delivery Customer Experience Benefits  Improved customer experience through segmentation and personalization  Proactive and expedited resolution of customer issues Revenue Benefits  Protect and Improve Margins  Increase profitability  Enable meaningful insights around the audience  Reuse CapEx and OpEx across projects Business Benefits

6. © 2015 TM Forum | 6 ABDR - Data Dictionary Revenue Assurance Fraud Management Cognitive Troubleshooting Predictive Customer Intelligence Product Offering Profitability Roaming and 3rd Party Margins Multi-level Margin Analysis Ad Sales Effectiveness DPI Switch Voice CDRs Switch Data CDRs, SMSC CDRS Billing Rated CDRs HLR Billing Accounts Billing Subscribers Billing PlanCustomer SubscriptionService Cost- Revenue Contact History Resolutions OffersSymptomsDeviceRegion ABDR Data Entities

7. © 2015 TM Forum | 7 $46.3 B Annual Fraud Loss Frost & Sullivan 2014 (CFCA) 1.5% Average RA Loss <50% ever recovered TM Forum 2016 Amdocs – Use cases Sponsored Data Content makers provide video and other content to CSPs users without it counting against the users' data allowance. –Revenue Assurance – detection of incorrect settlement with partners for sponsored data –Fraud Management – detection of internal fraud that permitted a third party to provide sponsored data for free Benefits to our customers from using the ABDR Faster Implementation and ROI Lower CAPEX. Data analysis, integration, ETL/ELT design and implementation, performed once and reused. Lower OPEX – simpler maintenance and lower storage and processing footprint

8. © 2015 TM Forum | 8 Prescriptive Analytics Use Cases Predictive Customer Experience The ABDR fuels the analytics process that enables customer segmentation analysis to identify the products and services adoption using customer- centric data such as location and time. Organizations can create dynamic pricing and campaigns and test them in a realistic simulation to validate 100% of the experience prior to any possible impact on the customer. Cognitive Troubleshooting Data from the ABDR is used to seed a cognitive engine that becomes smarter with use and will learn to resolve customer issues proactively through a process of symptom analysis, diagnosis and treatment. Predictive Performance and Customer Segmentation Analysis for a more Personalized Customer Experience Benefits for DSPs Provides critical visibility, insight and answers to help meet online conversion and customer retention objectives. Combines digital, behavioral, sentiment and predictive analytics for actionable insights. Faster, more intelligent data aggregation for improved resolution time and accuracy, leading to better customer experience.

9. © 2015 TM Forum | 9 Customer Experience Use Cases  OTT Solution – How to effectively deliver entertainment to customer?  Wearables – How to monitor vitals effectively to maximize customer performance? How to deliver “Player/Team” performance to customers?  Monetization Opportunities – Where and how to advertise to maximize the impact?  Security & Compliance – How to strike the balance between security of content and customer’s data?  Support – How to deliver better customer experience with Augmented Reality? DistributionDistribution IoTIoT Ad Decision GovernanceGovernance Customer Support -Identify -Profile -Target

10. © 2015 TM Forum | 10 Margin Assurance - Use Case Overview Often there is no direct match between what is provisioned to BSS and OSS and what happens on the revenue and cost side.  Correlate unprofitable subscriptions to services, static and dynamic analysis  Cluster similarly configured subscriptions to detect (bad) margin drivers  Discount stacking Individual services driving customer and product offering profitability Detect margin leakage or potential for improving margins in interaction with 3rd parties.  Roaming and interconnect margins  Dealer and channel margins Roaming and 3rd party margins Different notions and levels of margin help identifying potential improvements:  Direct margins for roaming and 3rd party margins  Total margins for profitability of providing services over the network and the impact of overhead expenses  Bill-to-pay margins for payment behavior and bad debt: what really ends up in the operator’s pockets? Multi-level margin analysis “SAP wants to provide a comprehensive, industry-ready and easy-to-adopt Big Data repository and analytic applications to our CSP customers. ABDR provides a rock-solid and big-data-ready framework for this. This will allow CSP’s to draw tangible value from Big Data much quicker. By adopting ABDR’s approach and adding our entities to it, we are able to quickly and comprehensively build out both our repository and analytic use cases.“ Why ABDR?

11. © 2015 TM Forum | 11 Benefits for DSPs Enabling faster deployment, implementation, and ROI from your Big Data Analytics initiative by:  Enabling re-use of data for multiple use cases & heterogeneous platforms and systems  Validating and demonstrating real life big data analytics infrastructure and use cases in a commercial software  Mapping and predefining the required data in a ‘data dictionary’ for each use case

12. © 2015 TM Forum | 12 Upon completion of ABDR Catalyst Phase 5 the project team has achieved the following: ABDR Catalyst Accomplishments  Defined and developed an innovative approach for a unified Analytics Big Data Repository (ABDR)  Nurtured the program from a proof of concept into a mature concept, which has been proven over several cycles and is being adopted by a growing number of DSPs.  Created a solid foundation for a Data Dictionary of standardized data entities.

13. © 2015 TM Forum | 13 Frameworx Contribution  Creating a new and innovative concept for a unified Analytics Big Data Repository (ABDR)  Initiate work to further develop ABDR as a sub-project of the big data analytics team  New use cases for GB979  Validation and demonstration of the best practices and use cases in GB979

14. © 2015 TM Forum | 14 The Champions and Sponsors of the ABDR Catalyst Project Analytics Big Data Repository (ABDR) Supported by

15. © 2015 TM Forum | 15 What Service Providers are saying… “Service providers own a goldmine of data, and big data analytics is becoming an important asset and competence. Yet how to fully extract its value is still a challenge. We are pleased to support the TM Forum's Big Data Guidebook and ABDR Catalyst project, which will help us to make a leap forward in extracting the value of big data analytics.” -- Lifen Zhao, Project Manager, China Mobile “The harmonizing of Big Data in defined and unique ways are becoming an ever increasing asset as we’re leveraging data to create and support emerging opportunities. Our involvement in the catalyst project establishes the importance of unified Analytics Big Data Repository, key analytics, and use cases vehicle to achieve increased value, revenue assurance, performance effectiveness and continuous improvement programs.” -- Internal Customer Analytics, Cox Communication Orange supports the major digital developments that are transforming our society with the belief that digital accelerates progress for everyone. Data is the foundation of digital and the challenge is be able to facilitate and accelerate the generation of value from data. Data analytics allows streamlining business processes and improving omni-channel customer experience by personalizing and enriching it together with guaranteeing privacy of its customers. TM Forum is the right platform to share best practices amongst all players and to capitalize on digital transformation. The catalyst project ABDR demonstrates very promising unified Analytics Big Data Repository and some key analytics use cases. − Sophie Nachman, Standards and Institutional Relationships, Orange

16. © 2015 TM Forum | 16 What’s Next for the ABDR?  Developing new and validating existing big data analytics use cases as defined in GB-979-A, and as part of TM Forum Frameworx  Continue to build the Data Dictionary for rapid implementation of use cases  Use cases are created and demonstrated in commercial products  Stay tuned! ABDR Going Forward

17. © 2015 TM Forum | 17 Delivering the automation to drive business agility Thank you ABDR Catalyst Project: Phase 5