www.wipro.com The Missing Data Scientists P. Srinivasa Rao, Vice President & Global Business Head Analytics and Information Management, Wipro Technologies
Table of Contents 1. Introduction...03 2. Why is Big Data taking on a larger-than-life role?...03 3. 6 Dimensions of the Big Data Scientist...04 4. Creating the analytical skill sets of tomorrow...04 5. Conclusion...05
The Missing Data Scientists Global business leaders acknowledge the importance of Big Data which holds the key to remain competitive and profitable in a consumer driven world that is evolving by the second. However, while companies are sourcing and storing these tremendous volumes of data they are at a loss when it comes to deriving real insights and business value from it. This paper examines the need for a new breed of professionals - The Data Scientists, who can decipher this data and turn it in to a valuable business asset. Why is Big Data taking on a larger-than-life role? As global, economic and physical walls disintegrate; hitherto strongly positioned companies are facing new sets of challenges associated with changing consumer behavior & business model innovation powered by disruptive SMAC technologies (Social, Mobility, Analytics and Cloud). While data analytics is not new, the disruptive SMAC technologies have enabled a consumer revolution which has pushed companies to find new ways of doing business. Caught in this customer centric economy, organizations are searching for ways to capitalize information assets and squeeze business results out of the same. Across varying roles, there are wide-ranging examples of how data is being used. The CFO of a Fortune 100 chemicals company says his function has been significantly increasing its use of data to improve its competitive intelligence and thus pricing structures. As we ve begun to learn more about data opportunities, it s allowed us to better analyze the competitive set that we play against in terms of pricing, cost structures, the ingredients of their products versus ours, cost positions, and market approaches, as he explains it. This is all analyzed in the pursuit of competitive gaps. Further downstream, it also drives other finance-led forecasting, such as how projected demand is affected by price shifts, the ability to supply that demand, and where excess capacity might lie. It gives us a better sense of our capacity to respond 1 he says. While data and analytics have always been utilized by organizations what we are witnessing now is a tectonic shift in the 5V s that capture the imperatives of Big Data - Volume, Velocity, Variety, Variability/Veracity and Value. For example, a decade ago a terabyte of data was considered as high volume, but now we are generating terabytes of data by the minute. The measurements have consistently moved up from PetaBytes, ExaBytes, ZettaBytes to YottaBytes. And soon we will have to come up with terms that can describe even higher volumes! There is also more variety. Earlier, Data Warehouses were built on static data. Now, with organizations needing real time insights, there is a need to analyze the data in motion. Hence, in-process analytics is becoming critical. Also, structured data available in databases is no longer the main and only source of data for all analytics. Data is available in varieties of structured, semi structured, unstructured, internal & external, text, voice/audio, pictures/video, human generated/machine generated etc. leading to better analytics driven insights and business value. Organizations are also looking to capture variability/veracity of data types such as weather, economic, social etc. that are thought to be inherently unpredictable, to thrive in this new economy. Big Data represents the ocean of unstructured, voluminous data out there. Whether social media sentiment, machine-generated data via sensors, staff emails, market data or otherwise, firms of all shapes and sizes are now 1.The Data Directive - An Economist Intelligence Unit survey, 2013, commissioned by Wipro Technologies 03
collecting more information than ever before. At least seven in ten companies collect syndicated third-party data, such as weather information (72%), or government data (70%), while many gather anything from internal staff data (66%) to some kind of location-based information (41%), among many other types. Two-thirds of business leaders say the range and types of data have expanded in the past two years, while about three-quarters expect this data stockpiling to expand yet further in the coming two years. Every day, Google alone processes about 24 petabytes (or 24,000 terabytes) of data. Yet very little of the information is formatted in the traditional rows and columns of conventional databases. Organizations are struggling to make sense of this data overload and most firms are yet to figure out what data is actually useful for them. The EIU report, commissioned by Wipro, confirms that only a small minority (12%) of executives think their organization has been highly effective at translating data into useful and insightful information so far. Access to data is no longer a challenge these days. We have a tremendous amount of access and we can measure just about anything, says Xerox s Ms Carone. To me, where we continue to have some challenges is how to translate this data into real, actionable results for the company, she says. Data should help drive revenue and sustainability in the long term for the organization. As you go higher up in the data value chain (figure 1), the value increases exponentially. Most organizations today operate at the Information level. Those who can move up to the Wisdom level leveraging insights from analytics will be able to fine tune their business strategy holistically and build a sustainable organization. Traditional analytical skill sets are falling miserably short on these expectations. As a result, most organizations have only been able to use this data for optimization purposes and are yet to employ it for strategic insights. To achieve Wisdom, organizations need to have suitable processes, technologies and human resources that help create these data driven insights. This paper will talk about the people aspect of an organization s data strategy. WISDOM APPLIED KNOWLEDGE KNOWLEDGE STRUCTURED INFORMATION INFORMATION LINKED UNITS DATA DISCRETE UNITS Figure 1: Data to Wisdom Pyramid 6 Dimensions of the Big Data Scientist Some of the key challenges in deriving insights from big data include underdeveloped tools, limited expertise and domain knowledge, and the challenges of dealing with IT itself. BI professionals who can summarize historical data and draw summaries may not be the answer any more. As leaders seek to make the evolution from optimization to strategic use of data they need to bring in advanced new skillsets matched with deep industry expertise. A data scientist weaves together the following 6 skillsets: Business Analysis Data Analysis Data Architecture Mathematics / Statistics Data Interpretation and Visualization ( BI ) Social / Behavioral Analysis Since data is complex, the role of a data scientist also assumes complexity. A data scientist while incorporating the traditional skill sets of the business analysts, data analysts and data architects must also have competency in statistical tools and techniques and human behavior. These are required for them to run statistical models such as probability theory, operations research etc. on structured data as well as make sense of the unstructured social data. These people must understand the psychology of the audience and tie in a social update with sentiment analysis and analyze sociological, demographical and psychological trends. Can we find individuals with all the above skills required to manage data? Not where we stand right now. Instead organizations are looking at multidisciplinary teams with data architects, visualizers, change agents, data engineers/operators, stewards and data virtualization / cloud specialists. However, teams come at a higher cost and the answer to finding the enigmatic and elusive big data scientist may lie in technology after all. Industry experts are optimistic that a few years down the line technology convergence will enable tools that will provide a single interface for all analytical needs of an organization. People trained on these tools will be able to perform the role of a data scientist with ease. However, a McKinsey's report states that by 2018 the US alone could face a shortage of 140,000-190,000 "deep analytical talent" and 1.5 million people capable of analyzing data in ways that enable business decisions. Creating the analytical skill sets of tomorrow According to The Data Directive, EIU report, 35% of BI professionals lack the necessary skills to take on the daunting task of unraveling and understanding big data. The same report also says that creating a leading data competency requires investment in both technology and skills, which lower-margin sectors will find more challenging. We see the need to st move into the 21 century and a much more advanced IT setup, which we know holds huge possibilities, explains the CFO of a major Spanish retailer, but the fact is that these are not the best times, which makes the investment into the technology, and the talent needed to exploit that, difficult to justify. 04
Creating the requisite analytical skills needs a three pronged approach: Get a leadership buy-in the top management must understand the importance of data driven insights and the need to invest significantly and strategically to harness this data potential. There must be an organization structure to bring in all data analytics efforts under one organization led by a CXO role that may evolve in to the Chief Data Scientist of the future. The charter of a Chief Data Scientist would be to provide data driven insights to senior management to shape the business strategy Bring in a data culture The organization structure needed to support data scientists is currently missing in most companies. And even a realization of this need is visible only in the high growth companies. Organizational silos, legacy and incompatible systems, bureaucratic procedures must be broken down to create a seamless information flow across the company. As analytics get embedded into data in motion and business processes, every single user in the organization needs to understand the importance of data and how it can be leveraged to meet operational, tactical and strategic business objectives. It should be institutionalized as a culture, rather than limiting it to a few data scientists Conclusion Data driven insights will shape the organizations of tomorrow. Organizations must bring in more strategic support and optimize the cost for data management and analysis. Additionally, data has to enable revenue growth, create competitive advantage, new pricing models, and foster innovation. This is only possible with an organization culture that thrives on data. And to build this culture, apart from 6 dimensions of core skills required for data scientists, they also need highly sophisticated soft skills around communication, collaboration, creativity, discipline and passion to drive business results by deriving value out of data analytics. Invest in people and technology Skill, re-skill and cross-skill people on tools and technologies that make data structuring and analysis smoother. Train these people to garner business insights from data and create meaningful reports that can be used in strategic decision making. 05
About the Author P. Srinivasa Rao (PSR) is the Vice President & Global Business Head for Analytics and Information Management (A & IM) focusing on Banking, Insurance, Securities, Retail, CPG, Transportation, and Government customers. A&IM helps customers derive valuable insights out of integrated information by bringing together the combined expertise of Analytics, Business Intelligence, Performance Management and Information Management. The group provides consulting, business centric and technology specific analytical solutions and data management frameworks developed through a complete ecosystem of partners, focusing on industry specific analytics, optimization and operations analytics, Enterprise Data Warehouse, MDM, Data quality and data life cycle management. PSR has 20+ years of experience in IT industry, and is one of the founding members of Business Intelligence and Data warehouse practice in Wipro. He has authored many white papers on Business Intelligence and received several recognitions for his contribution to business growth at Wipro such as CEO s letter of appreciation, difference in action, best people manager. He holds Post Graduate Diploma in Software Enterprise Management from Indian Institute of Management, Bangalore, M.Tech from the Indian Institute of Technology, Delhi, and Bachelor s in Electrical Engineering from Osmania University. About Wipro Council for Industry Research The Wipro Council for Industry Research, comprised of domain and technology experts from the organization, aims to address the needs of customers by specifically looking at innovative strategies that will help them gain competitive advantage in the market. The Council, in collaboration with leading academic institutions and industry bodies, studies market trends to equip organizations with insights that facilitate their IT and business strategies. For more information please visit www.wipro.com/insights/business-research/ About Wipro Analytics and Information Management Services Wipro is a leading provider of analytics and information management solutions, enabling customers to derive actionable business insights from data to drive growth, enhance cost management and strengthen risk management. Wipro works with customers to develop end-to-end analytics and information strategy leveraging process assets and solutions based on analytics, business intelligence, enterprise performance management, and information management. For more information, please visit www.wipro.com/aim About Wipro Technologies Wipro Technologies, the global IT business of Wipro Limited (NYSE:WIT) is a leading Information Technology, Consulting and Outsourcing company, that delivers solutions to enable its clients do business better. Wipro Technologies delivers winning business outcomes through its deep industry experience and a 360 degree view of "Business through Technology" helping clients create successful and adaptive businesses. A company recognized globally for its comprehensive portfolio of services, a practitioner s approach to delivering innovation and an organization-wide commitment to sustainability, Wipro Technologies has over 140,000 employees and clients across 54 countries. For more information, please visit www.wipro.com 07
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