Is Big Data Driving Product/Technology Innovation?


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Big Data market opporunity is expected to witness strong growth in the next 5 years touching $25bn globally. The big opporunity lies in Indian IT/ITES space which is likely to be $10-11billion market globally in 2015. Key risks include shortfall of data-savvy managers and data scientists in the US.

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Is Big Data Driving Product/Technology Innovation?

  1. 1. Sanjeev Sinha President, CRISIL Global Research & Analytics © 2013 CRISIL Ltd. All rights reserved.. Is Big Data Driving Product/ Technology Innovation? Oct 23, 2013 1
  2. 2. Key Takeaways  Big Data market opportunity is expected to witness strong growth in the next 5 years – Expected to touch US$25 billion globally; the ‘BIG’ opportunity for India lies in the IT & IT-enabled Services space, which is likely to be ~US$ 10-11 billion market globally in 2015 – India is likely to garner a ~10% share of the ~US$ 10-11 billion global Big Data IT Services Market by 2015  Driving product innovation through Big Data analytics is amongst the Top 10 business priorities  Organisations are leveraging Big Data analytics to embed customer sentiment in product innovation  Integrated approach to Big Data analytics is driving next-generation innovations in technology  New database architectures and innovative analytics tools & techniques to facilitate Big Data implementations  Emergence of niche Big Data start-ups to boost technological innovation  Key risk – potential shortfall of 1.5 million Data-Savvy Managers and 140,000-190,000 Data Scientists in the US by 2018 Source: CRISIL GR&A analysis 2
  3. 3. Big Data is Defined by Volume, Variety and Velocity What is Big Data ? Big Data relates to rapidly growing, Structured and Unstructured datasets with sizes beyond the ability of conventional database tools to store, manage, and analyze them. In addition to its size and complexity, it refers to Speed, Accuracy and Complexity of Intelligence its ability to help in “Evidence-Based” Decision-making, having a high impact on business operations 3Vs Small Data Sets Big Data Advanced analytics 1 Big Data analytics Volume 2 Variety Small Data Sets Big Data Traditional analytics Traditional analytics Large quantity of data which may be enterprisespecific or general and public or private Diverse set of data being created, such as social networking feeds, video and audio files, email, sensor data and other raw data Velocity 3 Gigabytes Terabytes Petabytes Size of Data Zetabytes Speed of data inflow as well as rate at which this fast-moving data needs to be stored Source: CRISIL GR&A analysis Source: CRISIL GR&A analysis 3
  4. 4. Big Data Analytics is Application of Advanced Techniques on Big Datasets; Answers Questions Previously Considered Beyond Reach Evolution of analytics Big Data analytics Behavioral analytics Level of Complexity Prescriptive analytics  Big Data analytics is where advanced analytic techniques are applied on Big Data sets Extreme SQL Visualization Predictive modeling Predictive analytics Forecast - ing Statistical analysis Adhoc reports Standard reports Late 1990s Social network analytics Semantic analytics Time series analysis Natural Language Processing Multivariate statistical analysis Online analytical processing (OLAP) Alerts Query drill down Analytic database functions Constraint based BI Optimization  The term came into play late 2011 – early 2012 Descriptive analytics Stochastic optimization Complex event processing Advanced analytics  Why did it happen?  When will it happen again?  What caused it to happen?  What can be done to avoid it? Data mining Basic analytics  What happened?  When did it happen?  What was the its impact ? 2000 onwards Time Analytics as a separate value chain function In-database analytics Source: CRISIL GR&A analysis 4
  5. 5. Global Big Data market to reach ~USD 25 billion by 2015,with a 45% share of IT & IT-enabled services  The global Big Data market is expected to grow by about a CAGR of 46% over 2012-2015  IT & ITES, including analytics, is expected to grow the fastest, at a rate of more than 60% – Its share in the total Big Data market is expected to increase to ~45% in 2015 from ~31% in 2011  The USD 25 billion opportunity represents the initial wave of the opportunity. This opportunity is set to expand even more rapidly after 2015 given the pace at which data is being generated. Global Big Data Market Size, 2011 – 2015E US$ billion Global Big Data Market Size, 2015F ~US$25 billion 25.0-26.0 Big Data analytics & US$ 10-11 IT & IT-enabled billion services Software Hardware 8.0-8.5 US$ 7-7.5 billion US$ 6-6.5 billion 5.3-5.6 2011E 2012E Opportunity for India lies in capturing the slice of IT services that includes Big Data analytics and IT & ITenabled services Lion’s share of the Big Data hardware and software market is expected to be occupied by IT giants like IBM, HP, Microsoft, SAP, SAS, Oracle, etc. 2015F 2015 Source: Industry reporting; CRISIL GR&A analysis 5
  6. 6. India’s ‘BIG’ opportunity is in IT and IT-enabled services India Big Data outsourcing opportunity, 2011 – 2015E US$ billions India Big Data outsourcing opportunity, by category, 2015F, Percent 100%= ~US$1.1 billion 1.1-1.2 24%-27% Pure-play Analytics firms Integrated IT/ BPO players ~0.2 ~0.1 2011E 2012E Source: CRISIL GR&A analysis 2015F 73%-76% Source: CRISIL GR&A analysis  India’s Big Data market is expected to grow at a 83% CAGR over 2011-2015 to reach ~US$ 1.1-1.2 billion  India’s share in the ~USD 10-11 billion global Big data IT and IT-enabled services market is expected to be ~10% in 2015 , where: – In 2015, integrated IT and BPO players will dominate the US$1.1 billion opportunity with close to 73-76% Source: Industry reporting; CRISIL GR&A analysis 6
  7. 7. Driving Product Innovation through Big Data Analytics is Amongst the Top 10 Business Priorities Why Big Data Analytics in Product Innovation? WHY BIG DATA ANALYTICS IN PRODUCT INNOVATION? Product innovation is a risky business: Majority of new products that enter the market fail Big Data Analytics shortens time to market, improves product adoption, and reduces costs Drivers of Big Data Analytics in Product Innovation Need for real time analysis of data Explosion of unstructured and semi-structured data Research required to adapt products, improve sales, and drive value is costly and time consuming Companies are turning to big data platforms like Hadoop to help provide faster insights Barries in Adoption of Big Data Analytics in Product Innovation Organisational and Cultural issues Paucity of budgetary allowances Demand for intelligence on product defects, improvements and usage Shortage of data scientists and analytics professionals Proactive assessment of customer behaviour Inadequacy of in-house technology infrastructure Source: Industry reporting; CRISIL GR&A analysis 7
  8. 8. Leveraging Big Data Analytics to Measure, Manage and Increase the value of Product Innovation Organisations are recognizing the value of ‘Big Data Analytics’ in mining customer needs and desires as well in devising a data management strategy that integrates big data into the front end of the innovation pipeline Strategic Portfolio Planning Unstuctured Data 3 Stuctured Data 2 Go-to-Market 1  Product Analytics New Product Development Predictive Analytics Behavioral Analytics Sentiment Analytics Use of Big Data Analytics Customer Analytics CRM Analytics Customer Lifetime Value Customer Sentiment Accelerate Innovation  R&D Analytics  Product Launch Analytics  Product Life Cycle Analytics  Customer Segmentation  Product Analytics  Sales/Demand Forecasting  Predictive Analytics  Price/ Promotion  Innovation Analytics  Assortment Planning  Product Analytics  Regulatory Analytics  Marketing Mix Modeling  Predictive Analytics  Portfolio Analytics  Competitor Analysis  Extreme Event Modeling Optimization  Acquisition Modeling Usage of Big Data Analytics to Embed Customer Sentiment in Product Innovation Innovation Data Management Source: Industry reporting; CRISIL GR&A analysis 8
  9. 9. Integrated approach to Big Data analytics is driving nextgeneration innovations in technology MARKET TRENDS AND DEVELOPMENTS Converging technology trends in data storage, processing, and analytics are driving adoption INTEGRATED APPROACH TO ADVANCED BIG DATA ANALYTICS PLATFORM Traditional Approach Structured, analytical, logical, and historical Transaction Data Increasing convergence between cloud and big data are becoming huge springboards to innovations in technology Emergence of niche Big Data start ups driving technological innovation Internal App Data ERP Data Mainframe Data OLTP System Data Data Warehouse Structured Repeatable Linear Traditional Sources Enterprise Integration Large IT players leveraging M&A’s to add Big Data capabilities to their service portfolios Unstructured New Exploratory Sources Iterative Text Data: Emails Social Data RFID Web Logs Hadoop Streams Open Source Big Data tools (Talend, Pentaho, etc.) and models are driving next-generation innovations in technology Talent shortage is one of the biggest challenges of the Big Data space Driver Inhibitor Neutral Sensor Data New Approach Creative, holistic thought, intuition, sense and respond Source: Industry reporting; CRISIL GR&A analysis 9
  10. 10. New database architectures and innovative analytics tools & techniques to facilitate Big Data implementations Store large quantities of unstructured data Area of advancement Data storage and management (Architectures) Examples Application areas* Database architectures: Need • Website click streams • Hadoop (MapReduce & HDFS) • Tweets and Facebook likes • NoSQL databases • MPP architecture like EMC’s Greenplum Faster data access, storage and analysis In-memory databases: Data storage and analytics • SAP HANA • Terracota BigMemory • Sensor Data • Emails • Real-time embedded systems • Algorithmic trading • E-commerce • Social networking Real time analysis of high volumes of data Advanced analytics and data processing In-memory analytics platforms like: • Kognitio analytics platform • SAP HANA analytics appliance • Risk management • Customer intelligence • Revenue optimization • Assortment • Merchandise planning Gain actionable insights from analytics and respond to issues instantly Source: Industry reporting; CRISIL GR&A analysis *Are indicative examples • Tag clouds Advanced Visualization • Energy management • Real time dashboards • SEO optimization • Heat maps • Real-time traffic congestion detection using GPS data • Spatial information flow
  11. 11. Emergence of niche Big Data start-ups to boost technological innovation A new class of companies, specializing in Big Data technologies have emerged, to capitalize on the opportunities in the Big Data domain Big Data start-ups – Key characteristics Specialized in niche Big Data technologies like Hadoop, 1 NoSQL systems, in-memory analytics, multiple parallel processing, and analytical platforms 2 Focus on two segments in big data—building pure technology infrastructure for managing the information, and analytical software that help enterprises in specific industries Technology Area Hadoop distributions Non Hadoop Big Data Platforms 3 Most start-ups raising funding by private ventures or being acquired by large IT players Majority of start-ups generate revenue less than USD 4 50 million and exhibit double digit revenue growth annually Analytic Platforms and Applications 5 Have created demand for data scientists, data savvy managers and large number of technical engineers Cloud-based Big Data Applications Source: Industry reporting; CRISIL GR&A analysis *Indicative list of players Players*