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Business Analytics: A Strategic Imperative

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Business Analytics: A Strategic Imperative

  1. 1. Business Analytics A Strategic Imperative SAS Forum India 2014 23rd April – Grand Hyatt, Mumbai
  2. 2. 1 • Introduction to Idea Cellular • Data transforming world around us – Data Analytics drivers & emerging trends • Strategic importance of analytics for an Indian Telco – Challenges faced by Indian Telcos • Data Analytics at !dea – CLM @ !dea • Benefits Contents
  3. 3. Introduction to Idea Cellular
  4. 4. 3 • Part of Aditya Birla Group – $40Bn Global Conglomerate; presence in 36 countries – Over 1.4 lac employees belonging to 42 different nationalities • 3rd largest Pan India Mobile Service operator – Listed; $ 8Bn + market capitalisation – $ 4Bn + revenues & 600 Bn + minutes of usage per annum – Ranks among top 10 country operators globally in terms of traffic – 135 Mn + subscribers getting coverage from 1 lac + towers – Leaders in Mobile Number Portability – Ranked # 1 in telecom sector at Asia Communication Awards 2013 • ‘India’s Best Companies to Work for Study – 2013’ & ‘Best Place to Work’ Introduction – Idea Cellular
  5. 5. Data Transforming World Around Us
  6. 6. 2009 2011 2015 2020 5 Global Data growing exponentially 0.8 ZB 1.9 ZB 7.9 ZB 35 ZB CAGR (2009-20) 41.0% Implication on an organisation • Need for large storage capacity • Need for quick retrieval of data • Enable informed decision making effectively, leveraging large datasets. Data captured by organisations to understand customers, suppliers, partners & operations. 1 Zettabyte (ZB) = 1 Bn Terabyte (TB) Source : Nasscom Big data report
  7. 7. 6 Managing Volume, Variety & Velocity Volume • Volume - Large quantity of data • 22 Bn GB of data is generated everyday globally • Variety - Diverse set of data • Competition & Customer related • Campaign & Channel related • Social Networking feeds • Velocity – Speed of data inflow • 14 Bn + Mobile Minutes generated everyday in India • 30 Mn + passengers travel from rail everyday in India • 20 Mn + ATM /POS transactions everyday in India • 17 Mn + internet searches everyday in India Source : RBI & comScore Indian Digital Future 2013
  8. 8. Key Industries using Data Analytics Financial Services Retail Healthcare /Pharma Manufacturing Telecom 7 Data Analytics across Industries •Claims & Renewal Analytics •Sales Force Analytics •Collection & Recovery Scorecards •Portfolio Analytics •Pricing & Risk Analytics •Demand Forecasting •Marketing Mix Analytics •Performance Analysis •Category Management •Trade Promotion Optimization •Evidence Based Medicine •Drug Treatment Effectiveness •Clinical Analytics •Average Length of Stay •Key Opinion Analysis • Collection Management • Subscriber Profiling • Competition Benchmarking • Churn Management • Revenue Assurance • Customized Offerings & Up- Selling • Demand Forecasting & SKU Rationalisation • Media ROI Optimizations • Route & Distribution Optimization • Vendor Performance Management
  9. 9. 8 Drivers for Data Analytics • Sales Reporting & Tracking • Cost Reduction • Risk Management • Better view to Financial data • Regulatory Compliance Drivers for BI & Analytics • Innovation • Competitive Differentiation • Reducing costs & Increasing Efficiencies • Growth • Insights for future strategy Organization Benefits
  10. 10. • Increased focus on Predictive Analytics – Historical events Vs forecasting future trends • Real Time Analytics – Quicker decision making with help of real time data. • Social Media Analytics – Focus on deriving customer insights based on social media behaviour – Real time inputs from Facebook, Twitter, Linkedln etc. • Integration of ERP & Analytics Software – Integration of data generation and data analysis through BI mart • Drive appropriate Variables & KPIs for enhanced business results 9 Emerging Trends in Data Analytics
  11. 11. Data Analytics @ Indian Telco
  12. 12. 1. Hypercompetitive landscape ; 12 operators across & 6- 9 operators / circle – Price war; small operators operating at half rates compared to big ones 11 Indian Telcos – Challenges (1/2) 49.4 35.1 32.0 23.5 14.6 9.2 6.6 3.1 3.0 2.9 ARPU (USD) 15.9 4.9 6.5 6.1 9.1 4.3 10.8 10 4.1 2,300 1,700 1,401 1,215 717 465 440 278 242 Usage/Sub (MB) Price/GB (USD) 2. Low ARPUs & low rates to global standards 3. Low entry /exit barrier for customers • High acquisition - High churn market
  13. 13. 4. Hyperactive Regulatory – EMF# regulations, various penalties (form related & telemarketing) – New acquisition guidelines; increased cost of acquisition by 20% – TCPR* guidelines; leading to revenue erosion of $300 Mn+. 5. Artificial Spectrum scarcity leading to high auction bids and increased debt – 3G & 4G auctions, one of the most expensive globally, $22Bn + – Spectrum charges & license fees, even after acquiring spectrum through auction – ROI < 1%, Net Debt to EBITDA ratio 4.5 & Consolidated Gross Block – $120 Bn 12 Indian Telcos – Challenges (2/2) *Telecom Consumer Protection Regulation # Electro Magnetic Force
  14. 14. Size • 2nd largest in the world, after China • 900 Mn Mobile users; 200 Mn Mobile Internet users & 40 Mn Smartphones Diversity • 22 circles or service areas ranging from 7 Mn to 70 Mn subs • Tele-density varying from 50% to 240% !!! Growth • Net additions of 6 – 7 Mn every month • Data traffic growth 90% overall in 2013; 150% for 3G 13 Telecom Market Scenario in India
  15. 15. • 14 Bn Voice minutes generated in a day • On-Net, Off-Net, Landline, STD, ISD, Roaming, Toll-free, Video • 2.5 Bn MBs data generated in a day • Billions of charging instances everyday • 20 Mn customer care calls everyday • 2 Mn retailers catering subscribers everyday • 6.5 Lac telecom towers covering 4 Lac Population centres • Market share fought at every tower • 40% Google searches & 30% Facebook users are mobile only 14 Volume- Variety- Velocity for Indian Telcos
  16. 16. Typical lifecycle of a Telco customer Phase 1: New joiner phase Phase 2: Stable phase Phase 3: Churn phase Time (AoN) Revenue ▪ Low entry barrier ▪ Rotational Churn ▪ Low exit barrier
  17. 17. Data Analytics @ !dea
  18. 18. 17 Evolution of Analytics in !dea •Predefined Static reports •Day and Month wise reports •Reports based on data from transactional systems •Drill down hierarchy reports • Time • Geography • Age on Network • Slicing & dicing of reports • Incoming/Outgoing calls • On-net, Offnet, STD, ISD, Roaming • Scorecards & Dashboards • Analyzing KPIs & monitoring trends, through graphs / charts with event based alerts • Prediction Analysis • Customer Churn • Revenue drop •Competition Tracking – Site wise • Acquisitions • Net adds • Traffic • Customer lifecycle management MIS Analytics Advanced analytics Core function under CMO
  19. 19. Data Analytics @ !dea Competition Related Customer Related Campaign Related Service Related Channel Related 18 Site wise • SOGA – Share of Gross Adds •SONA – Share of Net Adds •RMS – Revenue Market Share •Usage – Minutes & Data •Product based Segmentation •Usage based Segmentation • Call Leg based segmentation • Geography based segmentation • AoN based segmentation • Dynamic Churn based programs • Revenue enhancement programs • Cross- sell & Up-sell programs • Brand Track Index • Channel Satisfaction • Activation & Recharge based Retailer Segmentation • Geography & AoN based Distributor Segmentation • Channel commissions & incentives • Customer Satisfaction • Calls @ Call centre • Walk ins @ showrooms • Collection Management • Activation Management
  20. 20. Data Analytics @ !dea Way Forward Data Platform Near Real Time Analytics Near Real Time Promotion Map Platform Integration Visualization 19 • Social Media Analytics • Probe based URL analytics • Customer Experience Management • Customer Profiling and Monetization • Near Real Time Data streaming • Near Real Time Event Processing • Near Real Time Analytical Models • Location Based offers / Ads • Offers Based on recent experience / Behavior • Cross sell / Up sell Offers Based on Recharges / Subscriptions • Ability to process high data volume without preprocessing using IN memory and Associative features • Ability to get business Insights before developing regular KPI • Display of key business KPIs on Map • Ability to highlight Hotspots for easy visual detection • Drill Up/ Drill Down • Switch Between MAP and Tabular display
  21. 21. Customer Lifecycle Management @ !dea
  22. 22. Industrialised systems and processes  Measuring real time campaign impact on top-line and bottom-line  Clear Targets  Campaign library & product catalogues to drive competitive edge; !dea IPR  CLM Objectives & Deliverables 21
  23. 23. Test offers against each segment to find positive contribution to bottom line. Let customer decide the best offer !!! Micro segments (50-100K) based on similarity of usage behaviour through intensive data mining. Exclusive offers to each micro- segment to prevent value destruction !!! Target customers at all stage of lifecycle. Up-sell, cross-sell, retain and train through creative offerings. !!! Tested offers to be scaled to entire set of micro-segments & analyze results on real time basis. Build library of performing offers !!! Micro- Segmentation 2 Creative campaigns 4 Scale & Speed Don’t guess, Test ! 1 3 How CLM in !dea is different? 22
  24. 24. Usage Leg based segmentation Value levers Share of Wallet Usage stimulation Retention Type (SMS, Voice, VAS) Time (Weekend, Night)) Volume (MoU, Count) Duration/Frequency Outgoing/Incoming Primary dimension Primary usage Sub-usage >3 mths Internet/ text users Internet/ text non users Mr. Local Mr. STD Mr. VAS Mr. Balanced xx xx xx xx xx xx High Users < 3 mths xx xx AONMOU/VLR All subs Mr. STD Mr. VAS Mr. Balanced xx xx Mr. Local Micro Segmentation Approach 23 xx xx Campaigns targeting value levers
  25. 25. Automation Advantages • Create & analyze segments with more than 1400 variable options. – More than 4000 campaigns launched in a month. • Automation of communication at touch points – DND scrubbing, scheduling, script banks & vernacular scripts • Automated tracking of promotions – 15 Mn+ subscribers doing 25 Mn+ segmented recharges valuing $ 22 Mn + • Ability to create ‘Dynamic Campaigns’ • Creation of ‘Recurring Campaigns’
  26. 26. 25 Total Impact (ROI) of the offer Not considered right now ROI • Incremental Contribution Gross Revenue • Incremental Revenue • Loyalty Benefits Costs • Incremental Direct Costs • Incremental Network Costs • Execution Costs
  27. 27. Customer Lifecycle Management Phase 1: New joiner phase Phase 2: Stable phase Phase 3: Churn phase Time (AoN) Revenue 2% - 3% gain 6% - 10% gain 4% - 5% gain ▪ Reduce churn ▪ Increase ARPU ▪ ARPU stimulation ▪ Predictive Churn ▪ Recovery Programs ▪ Usage stimulation
  28. 28. Results • 60% revenue base covered under CLM • $ 100 Mn Revenue uplift • 30% EBITDA
  29. 29. Thanks

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