20131203 09 big_data_telekommunikation_roland_berger_consultants_tiefengraber

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Praxis Telekommunikation
Für Telekommunikationsunternehmen ist es mit Big Data auf Grund der verfügbaren Kundendaten, möglich, diese Beziehungen besser zu monetarisieren. Mobily, Saudi Arabiens Telekommunikationsunternehmen mit rund 20 Millionen Kunden, beauftragte Roland Berger eine “Big Data Monetization Strategy“ zu erarbeiten. Wie das Unternehmen dadurch seine eigene Leistungsfähigkeit steigert und seine Kunden mit passgenauen Serviceleistungen anspricht, das erzählte Andreas Tiefengraber von Roland Berger Strategy Consultants beim Werbeplanung.at Summit SPEZIAL am 3. Dezember 2013 in der Uni Wien.

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20131203 09 big_data_telekommunikation_roland_berger_consultants_tiefengraber

  1. 1. Praxis: Telekommunikation Andreas Tiefengraber Roland Berger
  2. 2. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 2 BIG DATA monetization Focus Telecommunication December 2013 Andreas Peter Tiefengraber 20131127 Werbeplanung Big Data APT.pptx 2
  3. 3. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 3 DATA PRODUCTION DATA PRODUCTION and therefore the amount of available data is EXPLODING – this trend is expected to continue the coming years Rapid growth of data – Indicators and development COMMENTS 2m 30 bn Emails sent every day Search queries received by Google every minute Pieces of content shared on Facebook every month 450 bn > 5 bn 1m Business transactions on the internet in 2020 every year People using mobile phones worldwide Transactions handled by Walmart every hour DATA SIZE 294 bn >  Global data production has reached astonishing levels, mostly driven by cheap computing and increasing online activity >  Volume of business data worldwide expected to double every 1.2 years Big data Information overload Relevant data TODAY SOURCE DC, Big Data Meets Big Data Analytics (SAS), ROLAND BERGER THE FUTURE 20131127 Werbeplanung Big Data APT.pptx 3
  4. 4. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 4 DATA IS THE NEW OIL The new paradigm everybody is talking about – DATA-IS THE NEW OIL "I suspect that when the history is written two hundred years from now, a trend will emerge as something very important that happened in human thinking during the time when we were alive, and that is that we are becoming rational, analytical and data-driven in a far wider range of activity than we ever have been before." independent.co.uk "Data is the next intel inside." Tim O'Reilly (2005) Source: Roland Berger, Press research "Data is the new oil." Ann Winblad (2012) "Data is becoming the new raw material in business" Rollin Ford (2012) Larry Summers, Former President of Harvard and Chief Economic Advisor to Barack Obama 20131127 Werbeplanung Big Data APT.pptx 4
  5. 5. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 5 DIGITALIZATION BACK-UP BIG DATA MONETIZATION becomes a key capability to unleash the power of data that is generated through DIGITALIZATION R&D Procurement Operations Marketing Sales Information& Communication DIGITAL TRANSFORMATION CREATES… DIGITALIZATION Source: Roland Berger Data-driven R&D E-Procurement Enterprise systems Digital Marketing BIG DATA Big data usually includes data sets with sizes beyond the ability of commonly used software tools to manage and process the data with tolerable time and effort. BIG DATA TOOLS Recent Big data approaches comprise hardware, databases, analytics software and predictive models to analyze big data effectively to reveal dependencies and thereby new insights. E-Commerce BIG DATA MONETIZATION Social Media Leverages insights from predictive models to identify new revenue and cost savings opportunities – within the current business or through new business models. 20131127 Werbeplanung Big Data APT.pptx 5
  6. 6. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 6 BIG DATA CHARACTERIZATION BIG DATA is characterized by massive data volume, velocity and variety – too large and complex to process with traditional tools As DATA grows exponentially… 1m Pieces of content shared on Facebook every month Transactions handled by Walmart every hour DATA SIZE 30 bn Est. No. of business transactions on the internet in 2020 p.a. Relevant data Source: Roland Berger 1 450 bn Information overload TODAY BIG DATA deals with massive data… VOLUME 3 VARIETY BIG DATA 2 VELOCITY THE FUTURE 20131127 Werbeplanung Big Data APT.pptx 6
  7. 7. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 7 SPECIFIC RELEVANCE FOR TELCOS Possessing enormous amounts of VALUABLE CUSTOMER DATA, Telecom operators increasingly warm up to the idea of monetizing it INDUSTRY QUOTES RECENT DEVELOPMENTS "We could make a living just out of analytics" Dir. Technology & Strategy >  Telefónica launched Dynamic Insights, a new unit dedicated to unlocking value from Big Data "We create more than 5,000 campaigns per day based on Big Data" CIO Bharti Airtel >  AT&T (AdWorks) and Sprint (Pinsight Media+) both aggregate subscriber data to improve campaigns "Whether Vodafone will be the "Apple" of Big Data? May well be" CEO Germany >  NTT provides its corporate customers with various Big Data solutions with their high volume processing unit BIG DATA Source: Roland Berger, Press research 20131127 Werbeplanung Big Data APT.pptx 7
  8. 8. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 8 BIG DATA MONETIZATION APPROACHES There is no standard approach for BIG DATA MONETIZATION – We offer help in four different areas which fit companies' needs Roland Berger project approaches – Big Data monetization Any CEO is relatively easy convinced that Big Data is important – but it is important to define the right scope of the first Big Data monetization approach! Source: Roland Berger 1 2 3 4 BIG DATA AUDIT Understand the potential of (big) data to boost top and bottom line impact along the value chain – different options from a 1 day workshop to a 6-8 weeks audit BIG DATA MONETIZATION STRATEGY Capture and prioritize the strategic options to become a big data champion and work out pre-requisites, business case and roadmap to do so CONCEPT DEVELOPMENT FOR BIG DATA APPLICATIONS Work out and implement concepts for concrete big-data applications (e.g. new 1:1 marketing concepts, new products, new business models) IMPLEMENTATION & TRANSFORMATION Ongoing and hands-on support (could be success fee based) to implement and harvest the potential identified and put in place all pre-requisites 20131127 Werbeplanung Big Data APT.pptx 8
  9. 9. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 9 MOBILY BIG DATA MONETIZATION STRATEGY Mobily asked Roland Berger to elaborate its Big Data monetization strategy in order to enhance its business Mobily Big Data Monetization Strategy MOBILY STARTING POINT SELECTED KEY QUESTIONS Valuable data waiting to be monetized >  Innovation as its core value; customers expect Mobily to be first in new services and efficiency >  Significant amount of customer data (e.g. ~20 bn CDRs per month, geo locations, email) >  Capable and scalable IT infrastructure Source: Mobily; Roland Berger >  How to monetize data? >  How should Mobily enhance its ongoing operations? >  How should Mobily introduce new services? >  How should Mobily diversify? >  What are the requirements in terms of >  IT infrastructure, >  organizational structure, >  operating model and >  regulatory changes? 20131127 Werbeplanung Big Data APT.pptx 9
  10. 10. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 10 MOBILE AS A DRIVER Big Data combined with mobile usage drives a revolution of new insights, value creation and customer centricity / benefits Huge jump in mobile advertising revenues Mobile driving success Profiling users through audio and video fingerprints / tags Mobile ecosystem enhancing economic development Personalized recommendations based on past purchases 1 of 10 customer pays with their mobile at Starbucks USA Individual insurances based on observed customer behavior Hugely successful in bringing music through the smartphone Source: Roland Berger … with Big Data as key enabler Incorporating wide data variety to pinpoint movie suggestions 20131127 Werbeplanung Big Data APT.pptx 10
  11. 11. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 11 DATA SOURCES Mobily has the opportunity to utilize the enormous amount of available data for their own operation and diversification Data sources available to Mobily – Illustrative INTERNAL STRUCTURED Mediation Passive network information Cell map information Logs Personal data Shop information CDRs BTS information Billing EXTERNAL Top-ups Self-developed apps Geo-location information ATM location data Distributor POS data Retail customers' information Source: Roland Berger Offers External websites DPIs Click-stream information Complaints Call centre voice calls transcriptions Questionnaires Articles (newspaper, magazines, publications, etc) Census data Partners information (e.g. banking) Ad servers UNSTRUCTURED Transactions Social Media (Twitter, Facebook, etc) Emails 20131127 Werbeplanung Big Data APT.pptx 11
  12. 12. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 12 TELCO BD VALUE CHAIN In the value chain of Big Data monetization, Telcos can play a range of roles, from pure datamart to end-to-end service provider Data I DATA GENERATION Information II INFORMATION PROCESSING Value III INFORMATION ENABLED ACTIVITIES Services IV THIRD PARTY SERVICES KEY ACTIVITIES >  Acquire customer data >  Structure data >  Storage and tagging >  Define data analysis >  Privacy management algorithms REQUIREMENTS >  Infrastructure to record >  Hardware and software >  Aligned organization to >  Suite of services to analyze structured and store without make use of insights catered to 3rd parties and unstructured data >  Potential clients privacy invasion >  New organization in real time benefiting from insights >  Partners POTENTIAL ROLE OF TELCOS >  Full aggregator of complete digital and physical life data set (e.g. location, spend, surfing, email, calls) Datamart Provider Source: Roland Berger >  Improve existing services >  Offer new services >  Set up new entity (double sided business model) >  Provider of the >  User and/or provider of >  Provide data to new information processing relevant insights based entity platform deployed to on end-to-end Big Data >  Run new entity (in extract insights from management partnership) data Big data platform provider End-to-end business service provider Separate Big Data entity 20131127 Werbeplanung Big Data APT.pptx 12
  13. 13. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 13 STRATEGY – KEY DELIVERABLES Mobily's Big Data monetization Strategy was built on 8 KEY DELIVERABLES AS-IS ASSESSMENT DATA PROTECTION OPERATING MODEL IT ARCHITECTURE ROADMAP BUSINESS PLAN PROOF OF CONCEPT INDUSTRY/USE CASES Source: Roland Berger 20131127 Werbeplanung Big Data APT.pptx 13
  14. 14. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 14 THE 6 KEY SUCCESS FACTORS We have identified 6 KEY SUCCESS FACTORS on the path to a leading big data player – From data capturing to skill development Key lessons learnt from big data champions 1 CAPTURE & GENERATE ALL RELEVANT DATA … generates a digital blue-print of our life 2 STORE & PROCESS ALL TYPES OF DATA … combines its own with external data e.g. weather 3 TRANSLATE DATA TO INSIGHTS …links all relevant data to predict our needs 4 MAKE INSIGHTS CONSUMABLE … increased its value by 1,000% through analytics 5 FOSTER A DATA-DRIVEN CULTURE … expects all employees "to feel like they are capable of using data" 6 ACQUIRE & DEVELOP SKILLS … announced the launch of a global software center and a USD 1 billion investment to build software and a team of appr. 1000 data scientists and 9,000 software engineers Source: Roland Berger 20131127 Werbeplanung Big Data APT.pptx 14
  15. 15. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 15 4 AREAS OF MONETIZATION There are four distinct areas on HOW TO MONETIZE BIG DATA – In the short to mid term main value creation will be internally BIG DATA VALUE CREATION INTERNAL > Optimization of current business model (e.g. faster, more targeted, more effective and efficient processes along the entire value chain) Revenue: TOPLINE >  Identify & acquire new customers >  Boost share of wallet >  Boost customer loyalty >  Boost customer recommendations + 3-7% Cost savings: - X-X% Internal vs. external: EXTERNAL > New business models to create value out of big data – often with third parties (e. g. data brokerage, new data-enabled products & services) Source: Roland Berger BOTTOMLINE >  SPEND less / reduce OPEX >  INVEST smarter / reduce CAPEX $ 6:1 20131127 Werbeplanung Big Data APT.pptx 15
  16. 16. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech INTERNAL VALUE CREATION 16 ILLUSTRATIVE We jointly identified and selected 200+ valuable use cases, which were consolidated in 6 areas of Big Data impact Use case assessment (selection of use cases) Calling screen configuration: Customers will be notified if they can initiate a local or international call based on their location Review and monitor Improve Sales & Distribution through customers' usage providing real-team performance data behavior to Give network priority to VIP customers in proactively avoid customer churn areas where the network is congested before it happens Assigning favorite numbers: Customers Re-identification of users who are frequent international callers and using different SIM card, haven't assigned their IFN based on their motion and Time Based Charging: Different charging behavioral profile to be done at different time of day. Analyze customer data and design specific offers and promotions to enhance up selling and cross selling Real-time deep packet inspection of network performance to optimize traffic routing and steer network quality of service Analyze structured data (such as actual subscriber usage) and unstructured or semi-structured data types (such as log files, click streams and text from e-mails), to provide more accurate and personalized offer recommendations Source: Roland Berger Consolidated areas Big Data impact 1. Reporting accuracy 2. Prediction accuracy 3. Customer profiles 4. Analysis time 5. Real-time action 6. Mobility patterns 20131127 Werbeplanung Big Data APT.pptx 16
  17. 17. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 17 OPERATING MODEL ILLUSTRATIVE Best practice examples confirm that Data, Tools & Processes and R&D are best done centrally while A&M fits better decentrally Input from best practices BEST PRACTICE Centralized Ensures cohesion with company-wide standards Efficient use of resources for development Operational speed and local adaptation and feedback loops Decentralized Data, tools and processes Source: Roland Berger Research & development Analytics and management 20131127 Werbeplanung Big Data APT.pptx 17
  18. 18. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 18 PROOF OF CONCEPT Mobily already analyses social media; in our project we conducted an ANALYSIS of UNSTRUCTURED DATA to showcase Big Data Twitter analysis How is this useful >  Social media analysis currently already executed by Mobily >  With Big Data proof of concept additional analyses performed in very short timeframe >  2 million (16 GB) Tweets analyzed on Amazon Web Services >  Geo-location dimension, customer sentiment and social graphs >  Determine where are your most vocal customers >  Gauge the reaction e.g. on new price plans, promotions, product launches, etc. per area >  Influence your opinion leaders >  Quickly respond to negative or positive communications Riyadh Saudi Global Social graph 20131127 Werbeplanung Big Data APT.pptx 18
  19. 19. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 19 PROOF OF CONCEPT During the project we ran PROOF OF CONCEPTS with Mobily's own data (CDR) e.g. Base station performance linked to customer value Under utilized Source: Roland Berger Congested 20131127 Werbeplanung Big Data APT.pptx 19
  20. 20. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 20 INTERNAL CHALLENGES Using Big Data requires to CHANGE THE COMPANY in three domains: Mentalities, Organization and Technology Internal challenges due to Big Data A Mentalities Mentalities >  Accept that data treatment will improve human decision making and not replace it >  Accept to change the business processes to include it Organization >  DMO1) should be responsible of the right usage and changes around INTERNAL data seen as an asset for the CHALLENGES company B C >  All Business Line will be potentially affected: Marketing, product Organization Technology management, HR, IT, Top executives Technology >  Smallest changes to operate >  Ensure right management of Data projects 1) Data Management Office Source: Roland Berger 20131127 Werbeplanung Big Data APT.pptx 20
  21. 21. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech YOUR CONTACT Looking forward to hearing from you ANDREAS TIEFENGRABER +43 1 536 02 201 andreas.tiefengraber@rolandberger.com Principal InfoCom CEE Thank you for your attention! Source: Roland Berger 20131127 Werbeplanung Big Data APT.pptx 21
  22. 22. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 22 RB CASE REFERENCES Our BIG DATA REFERENCES – We help leading international companies to become a big data champion Case references BIG DATA PROJECT TOPICS >  Development of business models based on "Big data" >  Development of consumer-insights from generated from loyalty card data >  Identification of multi-channel customer behavior >  Growth of market share with new channel-based CRM system >  Analysis of transactional customer data for service improvement >  Market potential, business model and technology for offerings based on telematics data 20131127 Werbeplanung Big Data APT.pptx 22
  23. 23. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech PUBLICATIONS We have demonstrated THOUGHT LEADERSHIP with many highly recognized publications Selected publications on Customer Data Monetization In Data We Trust Shopper Insights Big Data – Big Picture Rediscover Your Customer Cloud Economy Geo-analysis 20131127 Werbeplanung Big Data APT.pptx 23
  24. 24. "A4rb_Premium" – 2012-02_v02 – do not delete this text object! Speech 24 Strategies That Work! 20131127 Werbeplanung Big Data APT.pptx 24

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