BIG DATA - How big data transforms our world Kim Escherich Executive Innovation Architect, IBM Global Business Services 1
2 What happens? What is data?
340.282.366.920.938.463.463.374.607.431.768.211.456 50 Connected things 40 Billion 30 20 10 0 2003 2010 2015 2020 People 3 Source: Cisco IoT 2011 infographic
IBM Global Business Services Billions of RFID-tags embedded into our world and across ecosystems Billions of camera phones 4 INSTRUMENTED 2011 IBM
IBM Global Business Services +2 billion Internet-subscribers +20 billion Connected devices 5 INTERCONNECTED 2011 IBM
IBM Global Business Services Zettabytes of Internet traffic IP-traffic exceeded 1 Zettabyte in 2011 a 540.000x increase from 2003. Petaflop Super computers Scientists working to prevent influenza outbreaks, model the viruses with a super-computer operating at one petaflop 6 INTELLIGENT 2011 IBM
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fitbit Let's make fitness a fun, achievable part of everyday life http://www.fitbit.com 8
9 Neurowear Necomimi http://en.necomimi.com/
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12 Big data
We ve Moved into a New Era of Computing 12 terabytes 5 million of Tweets created daily Volume Velocity trade events per second We have for the first time an economy based on a key resource [Information] that is not only renewable, but selfgenerating. 100 s Variety Veracity Only 1 in 3 Running out of it is not a problem, but drowning in it is. John Naisbitt Of video feeds from surveillance cameras Decision makers trust their information
IBM Global Business Services Explosion of Data Means a Lot of Information But Lacking Insight 44x as much Data and Content Over Coming Decade 2020 35 zettabytes 1 in 3 Business leaders frequently make decisions based on information they don t trust, or don t have Business leaders say they don t have access to the information 1 in 2 they need to do their jobs 2009 800,000 petabytes Twitter process 7 terabytes of data every day 80% Of world s data is unstructured 4.6 Billion Mobile Phones World Wide 600M users add approx 30 Billion pieces of content each month 83% of CIOs cited Business intelligence and analytics as part of their visionary plans to enhance competitiveness 60% of CEOs need to do a better job capturing and understanding information rapidly in order to make swift business decisions 2011 IBM
IBM Global Business Services Behavior pattern analysis delivering insights for effective marketing decisions EXPLORATORY PURPOSEFUL PREDICTIVE REAL-TIME & ACTIONABLE Customer Buying Behavior Product Offers, Enhancement & Development Explore patterns that to uncover customer acquisition and retention behavior patterns across all data sources Identify, analyze and visualize feedback about your product Score customer behavior analysis and create models around newly discovered buying patterns. Accurately predict likely next best action for the customer. Score product sentiment and create models that would predict cross-sell and up-sell opportunities and insight into product enhancement and development of future portfolio Actionable insight supporting applications & processes campaign execution, CRM, ecommerce, call center, etc. Next best action offer can be modeled and predicted in real-time based on customer interaction and transactions. Actionable insight for localized product promotions that can be executed for maximum impact. Insight is fed into product enhancement and portfolio decisions Ad effectiveness Collect and analyze social data to assess awareness, reach and reaction to on and offline ads Create predictive models to test and fine tune ad campaign to maximize effectiveness Real-time ad analysis drives fast reaction to optimize campaign strategy and maximize ROI 2011 IBM
What can you do with big data? Know Everything About your Customers Social media customer sentiment analysis Promotion optimization Segmentation Customer profitability Click-stream analysis CDR processing Multi-channel interaction analysis Loyalty program analytics Churn prediction Innovate new Products Speed and Scale Social Media - Product/brand Sentiment analysis Brand strategy Market analysis RFID tracking & analysis Transaction analysis to create insightbased product/service offerings Run Zero Latency Operations Smart Grid/meter management Distribution load forecasting Sales reporting Inventory & merchandising optimization Options trading ICU patient monitoring Disease surveillance Transportation network optimization Store performance Environmental analysis Experimental research Exploit Instrumented Assets Network analytics Asset management and predictive issue resolution Website analytics IT log analysis Instant Awareness of Risk and Fraud Multimodal surveillance Cyber security Fraud modeling & detection Risk modeling & management Regulatory reporting 2009 IBM Corporation
17 Practical uses
18 Ambient Energy Orb Display energy consumption http://www.ambientdevices.com
19 Erik Fischer The Geotaggers World Atlas: Copenhagen http://www.flickr.com/photos/walkingsf/sets/72157623971287575/
IBM Sensor Solutions IBM City-in-Motion analyses multi-modal-traffic in real-time 2011 IBM Corporation
IBM Mobile Solutions Vestas optimizes capital investments based on 2.5 Petabytes of information 21 2012 IBM Corporation
IBM Mobile Solutions Barnes & Noble helps suppliers track sales and inventory in real time Capabilities Utilized: Need Data Warehouse Appliance Publishers absorb the losses on returns when they print too many books, and have stockouts when they print too few To provide publishers with the ability to get real-time insight into sales and view inventory trends over time Benefits Decreased time to run queries from weeks to seconds and enabled an 80% reduction in time to run compared to its previous system Reduced inventory levels and inventory carrying costs 22 2012 IBM Corporation
Intelligent City Operations Center for Smart Cities IBM Mobile Solutions 23 2012 IBM Corporation
Watson: From Jeopardy winner to healthcare provider 24
25 The Opportunity
We are ushering in a new wave of innovation Innovation The Industrial Revolution 1 st Wave Age of Steam and Railways 2 nd Wave Age of Steel, Electricity and Heavy Engineering 3 rd Wave Age of Oil, Cars and Mass Production 4 th Wave Age of IT & Telecom 5 th Wave 6 th Wave Smarter Products Instrumented, interconnected, and intelligent Building blocks for a smarter planet Sustainability 1770 1830 1875 1920 1970 2010 Source: Next Generation Green: Tomorrow s Innovation Green Business Leaders, Business Week, Feb 4, 2008 and Nicolai Kontratiev: The Major Economic Cycles (1925)
Sixth Wave Thinking 6 th Wave 1.Waste = Opportunity 2.Sell the Service, not the Product 3.Digital and Natural Converge 4.Bits are Global, Atoms are Local 5.If in Doubt, Look to Nature 27 James Bradfield Moody & Bianca Nogrady: The Sixth Wave How to succeed in a ressource-limted world
28 Price
Biodynamic Organic Conventional Pesticides Production method Herpacides Price Production environment Chemicals Child labor Packaging Sustainability Profiled Positive Health consequences Track Environmental footprint Geosphere Biosphere Climate change GMO Negative Transport Sustainability Sociosphere Health impact 29 History/Origin
30 Real-world use
Findings from the research collaboration of IBM Institute for Business Value and Saïd Business School, University of Oxford Analytics: The real-world use of big data How innovative enterprises extract value from uncertain data 2012 IBM Corporation
Macro findings Nearly two out of three respondents reports realizing a competitive advantage from information and analytics Competitive advantage enabler A majority of respondents reported analytics and information (including big data) creates a competitive advantage within their market or industry Represents a 70% increase since 2010 Organizations already active in big data activities were 15% more likely to report a competitive advantage A higher-than-average percentage of respondents in Latin America, India/SE Asia and ANZ reported realizing a competitive advantage Realizing a competitive advantage 2012 2011 2010 37% Respondents were asked To what extent does the use of information (including big data) and analytics create a competitive advantage for your organization in your industry or market. Respondent percentages shown are for those who rated the extent a [4 ] or [5 Significant extent]. The same question has been asked each year. 2010 and 2011 datasets Massachusetts Institute of Technology 58% 63% 70% increase Total respondents n = 1144 32 2012 IBM Corporation Source: Analytics: The real-world use of big data, a collaborative research study by the IBM Institute for Business Value and the Saïd Business School at the University of Oxford. IBM 2012
Key findings Five key findings highlight how organizations are moving forward with big data 1 Customer analytics are driving big data initiatives 2 Big data is dependent upon a scalable and extensible information foundation 3 Initial big data efforts are focused on gaining insights from existing and new sources of internal data 4 Big data requires strong analytics capabilities 5 The emerging pattern of big data adoption is focused upon delivering measureable business value 33 2012 IBM Corporation Source: Analytics: The real-world use of big data, a collaborative research study by the IBM Institute for Business Value and the Saïd Business School at the University of Oxford. IBM 2012
Download the study and access additional resources www.ibm.com/2012bigdatastudy www.ibm.com/gbs/bigdata@work Other IBV analytics studies are available at: www.ibm.com/iibv 2012 IBM Corporation
Thank you Kim Escherich IBM Global Business Services escherich@dk.ibm.com +45 2880 4733 internetofthings.dk escherich.biz @kescherich /in/escherich /escherich kescherich@gmail.com 35