Current technology trends are converging around four main technologies – Cloud Computing/Virtualisation, Social Media, Mobility and Big Data/Analytics. Each of these technologies is impacting both customers and service providers. For customers:Cloud is enabling a scalable, virtual computing environment via the internet that is leading to productivity improvements as it can be accessed from anywhere via practically any device. It is also offering an OPEX model with pay-per-use pricing – a feature many customers are leveraging to remain asset lightSocial media is emerging as the newest marketing tool. With a network on connections running into millions, it is becoming a communication tool for firms to reach their end user segments. Social media trends are also enabling firms respond to market changes faster and tailor their products/services to end user demandsSimilarly, Mobility is also another emerging productivity and communication tool. With most mobile devices being net-enabled, firms are using mobiles to stay connected to their extensive workforce Internet and social networking are driving exponential growth in the quantity of information being generated. Firms are leveraging Big Data/Analytics to gain strategic insights into business and customer trends and thereby improve decision making and minimise risks
Data Management comprises data storage infrastructure, and technologies for monitoring, coordination, administration and management of dataData Analytics includes the technologies and tools to analyze the data and generate insight from itData Consumption involves enabling the Big Data insights to work in BI and end-user applications Big Data ecosystem also includes the underlying data (structured and unstructured) and the IT infrastructure that supports itStructured data, i.e., data with named fields or row & column format resides in existing databases like RDBMS, Data Warehouse or an MPP system, vis-à-vis the unstructured data like weblogs, videos, social feeds, which is beyond the capabilities of traditional databasesWith emergence of Big Data, RDBMS, MPP and DW are transitioning to a new role of supporting Big Data management, by processing structured data sets as outputs of Hadoop or MapReduce technologies and then input for BI software and to applicationsOnce the Big Data is collected, processed and clustered, it becomes operational data, i.e., represents Big Data outcomes or serves as input data for analytics. After the data is analyzed, it becomes consumable for business users through various visualization techniques
Big Data analytics is the process of applying advanced analytic techniques to large data sets to uncover hidden patterns, unknown correlations and other useful information. Benefits of Big Data analytics have been explained in detail earlier in the report. But broadly, Big Data analytics assist companies in following ways:Take better business decisions: The most important objective of Big Data analytics is to help companies make better business decisions taking into account all the available information. This is achieved by analyzing large volumes of structured data as well as unstructured data from sources that are left unutilized by conventional business intelligence solutions. Predict and identify change: Big Data analytics helps companies closely monitor its ecosystem and discover what has changed and how should it react. It also gives the companies then ability to predict change which is crucial especially given the current uncertain macroeconomic environment.Identify new opportunities: Advanced Big Data analytics is an effective way to discover new opportunities such as new business segments, best suppliers, associate products of affinity, sales seasonality.Big Data analytics typically involves predictive analysis, data mining, statistical analysis, artificial intelligence, natural language processing, and database capabilities that support analytics (such as MapReduce, in-database analytics, in-memory databases, columnar data stores). It also involves highly skilled analytical talent, shortage of which is the biggest challenge facing the industry. In the Big Data analytics space, there are companies which provide Big Data analytics platforms and there are some which provide analytics services. Major Big Data analytics service providers are ThinkBig Analytics, Opera Solutions, MuSigma, AbsolutData, Wipro, Infosys, CSC etc. Increasing adoption of Big Data analytics across the industries presents substantial opportunities for these service providers as well as technology providers.
As organizations adjust to rapidly changing digital lifestyle of consumers worldwide, they are beginning to discover the importance of understanding and envisaging the impact of information generated from non-traditional sources such as blogs, Facebook posts, tweets, emails, smartphone applications, electronic sensors, images and YouTube videos. Big Data not only helps organizations gain a multidimensional view of their ecosystem, but also generates powerful insights that can help them execute their operations better and take meaningful decisions. Big Data is increasingly being leveraged through advanced data analytics tools and techniques, to provide organizations with a better understanding of their customers, competitors, operations, suppliers and partners. High-performance analytics that previously took days or weeks can be undertaken in seconds, minutes or hours through Big Data technologies. Private sector are adopting Big Data analytics at a large scale to generate strategic insights and improve products/services strategy, operational efficiency and gain deeper understanding of their customers, competitors and suppliers. Big Data analytics is enabling them to predict trends in near real time, make more accurate forecasts and adjust their operations quickly to changing demand or new business opportunities. Financial services: Big Data analytics can enable financial institutions to make better trading and risk decisions, protect them from frauds and security threats, and improve their products by better customer identification and marketing campaigns. Also, Big Data analytics is transitioning investment banks from relying on overnight batch data to make trading decisions. It has improved the risk decisions by leveraging real time analysis of current data rather than the risk management models based on historic data. For e.g., CITIC Bank Credit Card Center used Big Data technology to isolate customers unlikely to activate their credit card services, and direct marketing incentives to those most likely to activate, thereby, improving marketing campaign effectiveness by 65% and Westpac New Zealand used Big Data technology to analyze social media data to gain real-time insights into the bank's brand health and its product performance across different geographies by correlating specific branch performance to customer’s social data. Healthcare: The surge of large volumes of clinical data on medication, allergies, and procedures owing to implementation of electric health records have led healthcare companies to seek opportunities to predict and react more rapidly to critical clinical events, resulting in better care for patients and more effective cost management. Examples include several of the United States’ largest integrated delivery networks such as Cleveland Clinic, MedStar, University Hospitals, St. Joseph Health System, Catholic Health Partners and Summa Health System that use Big Data platform for real-time exploration, performance and predictive analytics of clinical data. Manufacturing: Companies are increasingly leveraging Big Data and finding new opportunities to predict maintenance problems, enhance manufacturing quality and reduce costs using Big Data. For e.g., Volvo leverages Big Data to analyze hoards of information being received from its vehicles, customer relationship management systems, product development and design systems, etc., to identify, in advance, potential issues such as manufacturing and mechanical problems and proactively resolve the problem by adjusting its manufacturing process. Telecommunications: Companies in the telecom industry are increasingly relying on real time analysis of data generated by mobile devices including phone calls, text messages, applications, and web browsing for better customer service and to build on retention and loyalty. For instance, while Nokia collects huge amount of unstructured data from phones in use, services, log files and other sources and uses it to gain insights and understand collective behaviors of consumers to improve the quality of its phones and their features, Cablecom deploys Big Data analytics to identify when a customer was most likely to make a decision to leave its network and offered special deals and incentives to retain the customer at the right time. Retail: With huge amount of data being generated from point of sale at stores, online transactions, social media posts, etc., Big Data offers numerous opportunities to retailers for improvement in marketing, merchandising, operations, supply chain and development of new business model. Retailers are deploying Big Data analytics to improve the accuracy of forecasts, anticipate changes in demand and then react accordingly. For e.g., active membership of Sears’ loyalty program showed a marked increase and crossed 80 million customers by using Big Data analytics. Other industries: Other than these verticals, benefits of Big Data can be applied to other industries as well. Data intensive verticals like utilities, oil & gas, and transportation, where data is generated through smart meters, GPS systems, satellites, etc. are also gradually using Big Data analytics to make real time predictions of their operations.
Game developers and brands have an opportunity to apply these Big Data analytics techniques to capture rich and varied behavioral and multi-structured game and player data
Surging demand for tools that can analyze massive volumes of structured and unstructured data has caught investor attention globally. In recent months, venture and growth capital firms have invested huge amount in Big Datacompanies, primarily to enable them to expand their operations. While Big Data firms across the globe have been receiving funding, Indian companies have also raised funding to boost their Big Data capabilities.Further, to capitalize on the growth momentum of Big Data industry, Indian service providers are leveraging partnerships and collaborations as well as acquisitions to expand their analytical capabilities beyond India. Also, players like MuSigma who are one of the early providers of data analytics are also expanding their overseas operations to cater to the surging demand of Big Data.
The most important thing is the ability to make sense and extract wisdom from the data. Leveraging the Big Data opportunity could face a talent and skills issue. The biggest effort for Indian service providers will be to develop a skilled workforce capable of generating value-adding insights from the data. This will call for huge investments and innovation in creating and grooming a new breed of talent. However, to solve problems such as these, it requires people with multifaceted skills: knowledge of advanced statistical techniques, modeling capabilities, strong understanding of the business context, customer insights, perhaps even some knowledge of regulations and programming.Today, there are not enough multifaceted people in the workforce; and the best education systems in the world are not designed to produce such industry-ready talent. While India produces huge number of graduates and software engineers every year, as well as has some graduates in statistics or other decision sciences MBAs, software engineers and statisticians are individuals with differing skill sets, but, Big Data analytics requires an individual to combine the capabilities of a statistician, a software engineer and an MBA - the pool of individuals, who combine such complementary skill sets. India is at an advantage vis-à-vis other geographies, as apart ample graduates each year, companies in India are also making huge investments in breeding and grooming such talent. Also, India retains advantages due to demographic factors, and the fact that the education system is producing a huge pool of analytical talent.
Rising demand for Big Data analytics is expected to lead to a global shortfall of professionals who can leverage Big Data to positively affect business results for organizations. According to a survey by EMC, two-third of organizations surveyed expect the demand for data scientists to outpace supply over the next five years, while one-third cite lack of employee skills as the biggest obstacle barrier to data science adoption.Recruitment and training are the main obstacles in growth of the Big Data industry, owing to heavy demand and limited capacity to train new talent. Companies have begun recruiting new talent from universities, and also collaborate with academic institutions to launch Big Data analytics courses. For Example, the Northwestern University recently launched a Master of Science degree in Predictive Analytics, in collaboration with IBM. However, Big Data analyticsas an integrated discipline has just emerged in academic curriculum, and it would be a while before academic institutions begin to serve as a robust supply source for Big Data professionals.Further, enterprises need to create organizational cultures that are conducive to data-driven decision making by:Effective recruitment: While recruiting new talent, focus should shift from business oriented degrees to other academic fields such as hard sciences, statistics, and mathematics. Further, candidates should be tested for intellectual curiosity and technical depth to addressBig Data challengesOn-the-job training: Companies should invest in providingon-the-job training in emerging technologies of Big Data, to eliminate skill gaps in their existing workforceIndian enterprises and academia have also begun to address the Big Data skills shortage. Technology firms such as EMC, Oracle, and IBM are planning to work with universities in India and overseas to introduce full-length electives or crash courses on various facets of Big Data. Training organizations such as NIITand Aptech are also exploring the Big Data space to design curricula for developing specialized skilled talent for theBig Data industry.
Big Data – The next big thing
Global uncertainty affecting IT spending Macro indicators look sluggish…. Near term IT spending outlook* Economic Growth - Global GDP Growth estimate for 2012 - 2.5% (2.8% in 2011); Euro area recession Employment & Households - Unemployment high, limited signs of recovery in US jobs, PMI and durables Financial Conditions – Developed markets – fiscal consolidation, credit stringency. Emerging Markets – Tight money, declining capital flows, currency volatility Corporates – Delayed decision making, uncertain earnings scenario * Includes hardware and telecomSource: IDC, NASSCOM
Indian IT-BPO industry sustained growthin FY2012 IT-BPO revenues* (USD billion) •India’s share in global sourcing - 14% 58 per cent in 2011 •Industry directly employs 2.77 million professionals; •Relative to India’s GDP: ~7.5 per cent •Relative to merchandise exports: ~23-25 per cent •Value add: 60-70 per cent9/17/2012Source: NASSCOM * Including Hardware 3
FY2013 - delayed decisionmaking, sluggish revenue growth Revenues Hiring • Revenue growth of only 1.3 per cent • 2 per cent QoQ increase for listed QoQ for listed IT-BPO companies public IT-BPO companies • Delayed decision making, pricing • Entry level hiring for current batch – pressure lower than FY 12 • Lack of discretionary spending, cross • Focus on hiring global workforce in currency volatility US, Europe • Banking sector – stagnant to some • Lower attrition decline • Higher bench, lower capacity • Crisis in Europe, sentiment based utilization downturn in US • Lower margins on increased • Emerging markets –potential SG&A, visa charges, wage hikes opportunity but long business cycles Markets Operational Metrics9/17/2012
Virtual infrastructure, data transforming ITlandscape of customers…creating new opportunities CLOUD COMPUTING SOCIAL MEDIA • Distributed pool of virtualized computing and • Scaleable – large audience storage • Enables crowdsourcing – innovation • Private cloud – focus area • Creats mobile office • Direct use of remote applications • Business communication / collaboration • Automatically scalable to demand SHARED tool • Shared utility computing model • Digital marketing tool • Pay-per-use model DECOUPLED DISTRIBUTED ANALYSED • Key basis of competition and growth • Better customer service, improved • Real-time micro-segmentation of customers employee collaboration & productivity for targeted promotions and advertising • Reduction in operating and • Improve decision making, minimize communication costs risks, unearth valuable insights • E-mail, Social networking, ERP, CRM - • Innovations in business on mobile applications models, products, services • Managed Services, Pay-per-use model BIG DATA/ANALYTICS MOBILITYSource: Accenture, Everest Research, McKinsey Global Institute, Zinnov, NASSCOM
Global Big Data market is estimated at ~USD 8.0 billion in 2012 Global Big Data market Global Big Data market by Key growth drivers include: opportunity, 2011 & 2012E, category, 2012E, Percent USD billion 100%= ~USD 8.0 billion Rapidly increasing sources of data, e.g., click 1 stream, mobile applications, social media, etc. 8.0-8.5 Exponential growth in speed of data 2 generation and complexity Software IT & IT 5.3-5.6 26%-28% enabled Services Need to store, analyze and consume 36%-38% 3 unstructured data for business insights 4 Enhanced prospects for Hardware innovation, improved agility, and increased 36%-38% profitability Need to analyze data in real time to 2011 2012E 5 achieve better competitive advantage Source: CRISIL GR&A analysis 2012: Big Data becomes mainstream 2012 expected to be dominated by pilot projects North America to provide the major opportunity 90% of Fortune underway by end of 2012have Big Data initiatives 500 companies likely to New BigofData companies attracting funding rounds over USD 50 million About 50 full-scale Big Dataworldwide in 2012 implementations expected projects Big Dataamarket opportunity in the next five years witness manifold increase is expected toSource: Deloitte; industry reporting; CRISIL GR&A analysis
Big Data management, analytics, IT services and applications are the key constituents of Big Data ecosystem What does the Big Data Ecosystem Constitute ? Big Data ecosystem constitutes four elements: Components of Big Data Ecosystem End users 1. Big Data Management & storage comprises Big Data Analytics application and use Applications Data analytics & its (System integration, customization, consulting, system design) data storage (mobile, search, we infrastructure, Developer Environments Analytics b) and technologies for (Languages (Java), products Environments (Eclipse & BI & visualization monitoring, coordinatio (Avro, Apache NetBeans) tools n, administration and programming interfaces Thrift) management of data (Tag cloud, heat (MapReduce)) 2 maps) 2. Big Data Analytics Input data Business analysts includes the IT services technologies and tools to analyze the data and Data Sources generate insight from it Big Data Data management & Unstructured Operational Data 3. Big Data’s data Application & Use Data Architecture NoSQL (Text, web NoSQL involves enabling the MPP storage pages, social Hadoop/ Big Data Hadoop Big Data insights to technology framework RDBMS media content, based work in BI and end-user email, video, aud DW (MapReduce & HDFS) applications io, etc.) 4. IT services including system integration, Structured Data administration tools consulting, project data ETL & Data Workflow/ System management and (stored in integration scheduler tools custom design for Big MPP, RDBMS products products Data systems & DW*)*MPP – Massively parallel processing; RDBMS - Relational Data Base Management Systems; DW – Data warehouseSource: CRISIL GR&A analysis
Social media analytics, sentiment analysis and behavioral analysis are the upcoming Big Data analytics services What is Big Data Analytics? Features • Big Data analytics is the process of applying advanced analytic and visualization techniques to large data sets to uncover hidden patterns and Big Data Analytics is: unknown correlations for effective decision-making • As analysis of such large data sets may be challenging to 1 2 understand, applying data visualization techniques make interpretation of Self-service Visual results easier for business users 3 4 Social Media Analytics Sentiment Analysis Dimension-free Exploratory High Real-time dashboards (NLP*) Fraud Detection Behavioral Analysis 5 6 Stochastic optimization Mashup Contextual Predictive Modeling Genetic Algorithm Degree of Complexity Optimization (optimization) 7 Descriptive Modeling Predictive Statistical Analysis Video Analytics Micro Customer Text Mining/Analytics Segmentation Social Network Analysis Data Mining Automating decisions for real-time Time-series analysis (regression B processes Low technique) e Identifying current business state and Pattern Recognition n new opportunities e Mature Growing Nascent Reducing time-to-insight Market Adoption Status f i Visualization Techniques Identifying and predicting change t 1. Tag cloud 2. Clustergram 3. Heat Maps s Quantifying of current and potential risks 4. Dashboards 5. Spatial information flow 6. History Flows*Natural Language ProcessingSource: Industry reporting; CRISIL GR&A analysis
Big Data enables better customer segmentation, improved productivity and fraud detection across all industry sectors How are organizations leveraging Big Data analytics? • Target segment identification • Trade monitoring and analysis • Buying patterns identification • Adhering to stringent regulations and • Customer experience & loyalty compliances Consumers management • Improved risk decisions • Social media management • Real time fraud detection and prevention • Customer attrition management • Intelligence to Financial counter national services • Productivity improvement threats • Process improvement Benefits for private sector • Forecast economic • Real time analysis Operations • Streamlining operations events of purchase • Fraud detection / mitigation • Traffic Public behavior and Retail management Sector buying patterns • Innovative product/service • Environment • Enhanced Product development monitoring, energy/ customer Potential development • Existing product/service waste management segmentation and improvement opportunities customer loyalty of Big Data • Supply chain interventions Manufacturing Telecom Supply Chain • Customer inventory management • Demand • Supplier inventory management forecasting and • Network planning operational and optimization analytics Healthcare • Customer churn • Competitive pricing • Supply chain analysis Competition • Competitor insights responsiveness • Failure and fraud • Next-generation sequencing and mapping for • Open innovation genomics: gene expression detection through • Analysis of correlation between treatments & • Cross-selling and up-selling crowdsourcing • Innovative marketing outcomes Marketing • Real time data from medical devices for • Advertising effectiveness better patient care measurementSource: Industry reporting; CRISIL GR&A analysis
Social gaming, mobile applications, Internet search portals are key end-user applications, leveraging Big Data analytics What are end-user applications of Big Data analytics? Organizations are increasingly leveraging insights provided by Big Data by delivering “Big Data value” directly to consumers through data driven applications. These applications can reside on a PC, smartphones, tablets or other Web-enabled devices • In July 2012, Google launched Google now, an android application that enables users the option to see suggested results without typing anything in the search box, leveraging Big Data analytics on information like behavior of the user, location, search, calendar history, etc. Search • Amazon’s Price Check App bar-code portals • Shopkick, a mobile application, tracks scanning mobile application leverage Big customers by picking up inaudible Data analytics to provide users with sounds emitted by in-store devices on comparative intelligence on store prices the mobile phone’s microphone • Thrive.AI, an iPad Examples of • Path Intelligence tracks foot traffic Geo-location within malls by passively monitoring application, customized to individual Big Data tastes, leverages users’ data, from social E-commerce based signals sent by mobiles networking sites, to suggest products user services applications Social Enterprise Gaming applications • US Xpress Inc. integrated sensor information from • Players like Zynga, deploy Big Data analytics to trucks into its Big Data analytics program and design retention strategies by optimizing ad- saved ~USD 20 million on fuel by collecting data generated interaction or in-game virtual goods from trucks on speed, hard braking, gas sales on consumer-centric, social gaming consumption, etc. through mobile devices, and applications like CityVille, Zynga Poker, and sending the analyzed data to fleet managers FarmVille tablets or mobiles to enable on-the-go decisionsSource: Industry reporting; CRISIL GR&A analysis
Emergence of niche startups and technological developments fostering growth in the Big Data industry Market Trends and Developments Impact on Industry Converging technology trends in data storage, processing, and analytics are driving 1 adoption 2 Emergence of niche Big Data startups driving technological innovation Large IT players leveraging M&A’s to add Big Data capabilities to their service 3 portfolios 4 Cloud computing to combine best practices of virtualization, grid computing, and advanced analytics on large datasets 5 Talent shortage is one of the biggest challenges of the Big Data space 6 Lack of awareness about benefits of Big Data may limit enterprise adoption 7 Regulations driving the adoption in various industry verticals Positive Neutral/ Limited Negative impact impact impactSource: CRISIL GR&A analysis
5 Potential shortfall of 1.5 million Data-Savvy Managers and ~150,000 Data Scientists in the US in 2018 Demand-supply gap for data scientists* in US, 2018 Role in Requisite educational Other expertise 440K-490K Ecosystem qualifications • Big Data analytics • Advanced degree like • Expertise in data analytics 300K Data M.S. or Ph.D., in skills to extract data, use • Business intelligence 140K – 190K Scientists mathematics, statistics, ec of modeling & simulations • Visualization onomics, computer • Multi-disciplinary 50%-60% science or any decision knowledge of business to gap relative sciences find insights to supply • Knowledge of statistics • Project management • Advanced business and/or machine learning to Data-savvy across the Big Data degree such as MBA, M.S. or frame key questions and 2018E Supply 2018E Demand Managers ecosystem managerial diplomas analyze answers - Consulting services • Conceptual knowledge of Demand-supply gap for data-savvy - Implementation business to interpret and managers* in US, 2018 - Infrastructure challenge the insights management 4.0 million - Analytics • Ability to make decisions using Big Data insights 2.5 million • Technical support in • Having a degree in • Possessing data Technical hardware & software computer management knowledge 1.5 million Engineers across the Big Data science, information 60% gap ecosystem for: technology, systems • IT skills to relative to - Data architecture engineering. or related develop, implement, and supply - Data administration disciplines maintain hardware and software - Developer environment - Applications 2018E Supply 2018E Demand*Analysts with deep analytical training; **Managers to analyze Big Data and make decisions based on their findings; Source: McKinsey Global Institute; CRISIL GR&A analysis
India’s Big Data market opportunity estimated at ~USD 200 million in 2012 India Big Data outsourcing opportunity, India Big Data outsourcing break- Key Trends 2011- 2012, USD million down by service type, 2012, Percent 100%= ~USD 200 – 205 million Telecom and financial services verticals Pure-play Analytics, are early adopters of Big Data technologies 16%-18% 200 - 205 Indian IT and analytics players are ~90.0 gaining maturity to serve the Big Data opportunity 2011 2012E Integrated IT / BPO players, Source: CRISIL GR&A analysis 82%-84% 2012: Big Data market to grow manifold The opportunity for Indian service providers lies in offering services around Big Data implementation and analytics for global multinationals India’s business opportunity in Big Data outsourcing is estimated at ~USD 90.0 in 2011 expected to reach ~USD 200 - 205 million in 2012, showing a growth of over 110% IT services segment is expected to be the major contributor to the Big Data services market accounting for about 82% with analytics accounting for the remaining The domestic demand for Big Data implementation is still at an embryonic stage* 10 petabytes and aboveSource: Deloitte; industry reporting; CRISIL GR&A analysis
Service providers are leveraging partnerships, M&As and venture funding to capture the Big Data outsourcing opportunity in India Indian M&As to Increase in Partnership companies gain Big venture with foreign expanding Data funding players overseas capabilities presence • In Dec 2011, MuSigma • In June 2012, Capgemini • Big Data players like • In July 2012, MuSigma raised USD 108 million to partnered with SAS to AbsolutData and MuSigma announced plans to expand grow its Big Data analytics launch a campaign in UK expect M&As to be a key in new markets and grow its business focusing on Big Data and focus area in the industry, to employees to over 2,800, • In May 2012, Nuevora, a Big analytics build capabilities (Jun ’12) primarily analytics Data analytics firm that professionals, in the next operates an analytics CoE • In July 2011, HCL opened a • In July 2012, Alten Group, a year in India secured its first co-innovation lab in European provider of round of institutional funding Singapore, along with Eli technology consulting and • TCS opened a Silicon Valley from Fortisure Ventures Lilly to create innovative engineering announced plans Customer Collaboration - Nuevora plans to use applications using business to make strategic acquisitions Center to bring the benifits the proceeds to develop analytics and cloud in India in areas of Big Data of emerging technologies a suite of cloud-based computing in the healthcare analytics like Big Data, analytics and business-processes-as- space mobility to enterprises a-service (BPaaS) across all industries analytics applications Indian service providers undertake several growth avenuesSource: Industry reporting; CRISIL GR&A analysis
India has an early mover advantage vis-à-vis other geographies in creating a strong base of Big Data workforce India’s Big Data talent requirement*, 2011-2015 Annual potential talent pool available for Big Data in India IT Professionals 2,800,000 ~15,000 – 20,000 Graduates in Math/science 700,000 Engineers 500,000 While total talent Graduates in Economics 350,000 availability is Post graduates in high, ready to hire ~4,000 – 6,000 Math/science 300,000 talent for Big Data MBAs 250,000 would be just ~3%- 5% of the total ~1,000 -1,500 PhDs 14,000 2011E 2013F 2015F Graduates in statistics 5,000 Source: CRISIL GR&A analysis State of Big Data talent across key geographies • India is expected to be in the forefront of Big Data analytics and related IT Service provider services, fueling demand for data scientists and IT engineers estimated at Talent Ready to Overall relative about 15,000 – 20,000 by 2015 efforts to build availability hire talent ranking such talent • India follows closely behind the US in terms of Big Data talent availability and service providers initiatives to build such talent United I High High High • India is ahead of most outsourcing destinations like China, Poland and States Philippines, in terms of talent availability. It also enjoys an early mover India High Medium High II advantage from service providers in capitalizing the immense potential arising from Big Data Poland Medium High Medium III - IT companies like EMC, Oracle, IBM, Infosys, etc., are leveraging China their academic alliance programs, with universities in India and High Low Low IV overseas to introduce courses in various areas of Big Data Philippines Low Low Low V - Further, private IT training institutes like NIIT, Aptech are developing talent through courses specific to Big Data*Includes data scientists and technical engineers High Medium LowSource: Industry reporting; CRISIL GR&A analysis
Global Big Data market to reach ~USD 25 billion by 2015 Global Big Data Market Size, 2011 – 2015E Global Big Data market by category, 2015F USD billion Percent 100%= ~USD 25.0 billion 24.0-26.0 29%-31% 44%-46% IT & IT enabled Services Hardware 8.0-8.5 5.3-5.6 Software 24%-26% 2011E 2012E 2015F Source: CRISIL GR&A analysis Source: CRISIL GR&A analysis • Rising need to focus on leveraging multiple data • Shortage of analytical and managerial talent sources, to maintain competitive advantage • Continued investments from service providers in • Regulations about data privacy and security Big Data technologies and tools, particularly in Drivers Big Data analytics Restraints • Roadblocks in managing change during transition to data driven organizations • Companies to define Big Data implementation strategy for taking more informed decisions • Restrained adoption in new geographies such • Big Data deployments to become mainstream in as the Middle East verticals like utilities, transportation, energy, etc.Source: Industry reporting; CRISIL GR&A analysis
India Big Data outsourcing opportunity to manifold over 2012- 2015 to lie between USD 1.1-1.2 billion India Big Data outsourcing opportunity, 2011 – 2015E India Big Data outsourcing opportunity, by USD billion category, 2015F, Percent 100%= ~USD 1.1 billion 1.1-1.2 24%-27% Pure-play Analytics firms Integrated IT/ ~0.2 73%-76% BPO players ~0.1 2011E 2012E 2015F Source: CRISIL GR&A analysis Source: CRISIL GR&A analysis Key growth drivers include: 1 Aggressive efforts for Big Data specific talent development Increasing domain expertise and breadth of services offered by 2 Indian service providers Effective strategies of Indian service providers through synergies of 3 international partnerships 4 Rising domestic demand for Big Data implementations across industry verticalsSource: Industry reporting; CRISIL GR&A analysis
Global Big Data market to evolve, India can emerge as a preferred destination for analytics and IT services Big Data technologies Service providers landscape Supply trends and applications • Significant M&A activity, particularly in analytics and front-end enablers • India to become a hub for • Big Data ecosystem will continue to evolve over analytics and IT services 2012 -2013 • Big Data technology distributors (Cloudera, Greenplum, etc.) to grow • Aggressive efforts to - Continued investments through partnerships with leading IT players or analytics providers develop talent specializing to strengthen existing in Big Data technologies and tools • IT/BPO service providers to expand their services to capitalize on Big - Emergence of in- Data opportunity memory processing for Hadoop Demand trends • Educate enterprises through Big Data conferences, seminars, white - Implementations to learn papers, and articles from pilots and early • US continues to dominate as adopters the major source of revenue - Growth in cloud based Big Data deployments Big Data customers • Demand from APAC and Europe to gain traction - Rise in business • Become more aware about benefits of Big Data in for competitive intelligence solutions on advantage mobile platforms • Big Data deployment to expand beyond - Tools for enhancements • Companies to define roadmaps for Big Data implementations telecom, manufacturing, he around data althcare, retail, Internet, and storage, security, and financial services reporting • Fortune 500 to remain the key segment; SME adoption to gain footing • Transportation, oil & gas, and utilities hold potentialSource: Industry reporting; CRISIL GR&A analysis
Concerted efforts by the service providers and academia to improve talent employability Academia & corporates building fresh talent Service providers introducing for Big Data, both in India and overseas cross-training to existing talent • Introduced Master of Science (M.S.) degrees in Analytics in 2012 • Launched an open data science and Big Data analytics training and • Also, offers an online degree in certification program in 2012 Predictive Analytics • Offers M.S. degree in Analytics since 2007 through its Institute of • Provides training to its analysts Advanced Analytics via its Mu Sigma University Analytics On-the-job program for core analytical skills as a part of training academic • Indian Institute of Science introduced curriculum a masters degree course on business analytics in 2012 • Launched Infosys Big Data Certification Program (IBCP) to validate and build knowledge of • Has partnerships with over 850 Big Data amongst its employees colleges globally including ~200 in India to offer courses on cloud Effective computing and Big Data recruitment practices Focus on hiring the right fit for data scientist roles during recruitments • HP Global Analytics hires people with expertise in decision sciences and applied mathematics, and professionals with strong data analytical skills • Amex hires candidates with PhD or MS in computer science, statistics, mathematics, or engineering, and prior experience in working with Big Data tools and leveraging sophisticated analytical techniques • Oracle India hires data scientists with strong foundation in statistics, strong programming skills, and experience in developing predictive modelsSource: Industry reporting; CRISIL GR&A analysis