The examples of what other countries (such as Singapore) are doing in new areas such as Big data
and using Big data, and much more. Megatrend 5: Industrial Clusters and Global Value Chains Global value chains (GVCS) are the defining feature of early 21st-century international trade.
and visualization (big data) to provide real-time information, interactive applications and other services to its citizens.
Clouds, Big data, and Smart Assets: Ten Tech-Enabled Business Trends to Watch. Mckinsey Quarterly, August.
The Global Information technology Report 2014 Rewards and Risks of Big data Beñat Bilbao-Osorio, Soumitra Dutta,
and Bruno Lanvin, Editors Insight Report 2014 World Economic Forum Insight Report The Global Information technology Report 2014 Rewards and Risks of Big data Beñat Bilbao
and Rewards and Risks of Big data 1. 1 The Networked Readiness Index 2014: 3 Benchmarking ICT Uptake in a World of Big data Beñat Bilbao-Osorio and Roberto Crotti (World Economic
How 35 the Network Unleashes the Benefits of Big data Robert Pepper and John Garrity (Cisco systems) 1. 3 Big data Maturity:
and Walid Tohme (Booz & Company) 1. 4 Big data: Balancing the Risks and 53 Rewards of Data-Driven Public Policy Alex Pentland (MIT) 1. 5 Managing the Risks and Rewards 61 of Big data Matt Quinn and Chris
Taylor (TIBCO) 1. 6 Rebalancing Socioeconomic 67 Asymmetry in a Data-Driven Economy Peter Haynes (Atlantic Council) and M-H. Carolyn Nguyen (Microsoft
The Role of 73 Regulation in Unlocking the Value of Big data Scott Beardsley, Luís Enríquez, Ferry Grijpink, Sergio Sandoval, Steven Spittaels,
and Malin Strandell-Jansson (Mckinsey & Company) 1. 8 From Big data to Big Social 81 and Economic Opportunities:
and Patrick Ryan (Public Policy Division, Google, Inc.)1. 9 Making Big data Something 87 More than The next Big Thing Anant Gupta (HCL Technologies
and risks accruing from big data, an unprecedented phenomenon in terms of the volume, velocity, and variety of sources of the creation of new data.
These include the emergence of cloud and mobile computing, the growth of big data and analytics,
The migration to IP networks and the ability to turn big data into valuable actionable information have demonstrable benefits both economic and social as well as positive financial impacts for firms.
big data. This is comprised of large datasets often gathered in unstructured forms from the behavior of people and groups.
In capable companies, big data is aligned with their strategies. They invest only in the data gathering that gives them privileged access to the customers they care about,
Without that discipline, companies can be overwhelmed by big data. They can collect a huge volume of information without any predetermined purpose,
EXTRACTING VALUE FROM BIG DATA Data have had always strategic value, but with the magnitude of data available today and our capability to process them they have become a new form of asset class.
and has attracted a great deal of business press in recent years This new asset class of big data is described commonly by what we call the three Vs.
Big data is high volume, high velocity, and includes a high variety of sources of information. Next to those traditional three Vs we could add a fourth:
and this is why big data today gets so much attention. In the quest for value, the challenge facing us is how to reduce the complexity
and unwieldiness of big data so that it becomes truly valuable. Big data can take the form of structured data such as financial transactions or unstructured data such as photographs or blog posts.
It can be crowd-sourced or obtained from proprietary data sources. Big data has been fueled by both technological advances (such as the spread of radio-frequency identification, or RFID
chips) and social trends (such as the widespread adoption of social media. Our collective discussions, comments, likes, dislikes,
and studied within the realm of big data. Big data has arrived. It is changing our lives and changing the way we do business.
But succeeding with big data requires more than just data. Data-based value creation requires the identification of patterns from
which predictions can be inferred and decisions made. Businesses need to decide which data to use.
This world of big data has also become a source of concern. The consequences of big data for issues of privacy and other areas of society are understood not yet fully.
Some prominent critics such as Jaron Lanier, 2 call on us to be cautious about readily believing any result created by the wisdom of the crowd.
Moreover, applications of big data in military intelligence have created a growing concern for privacy around the world.
Furthermore, a number of expert contributions inquiring into the role of big data and how to extract value from it are included also.
These contributions relate to (1) how the network unleashes the benefits of big data;(2) how and why policymakers and business executives need to develop action plans to extract value from big data;(
3) balancing the risks and rewards of big data from a public policy perspective;(4) managing these risks and rewards;(
5) rebalancing socioeconomic asymmetry in a data-driven economy;(6) the role of regulation and trust building in unlocking the value of big data;(
7) turning the potential of big data into socioeconomic results; and (8) defining organizational change to take full advantage of big data.
Insights from the NRI 2014 on the world's networked readiness Chapter 1. 1 provides an overview of the networked readiness landscape of the world as assessed by the NRI 2014.
It presents the results of the top 10 performers and selected countries by region, in the following order:
How the Network Unleashes the Benefits of Big data Chapter 1. 2, contributed by Robert Pepper and John Garrity from Cisco systems,
and explores how IP networks accelerate big data's transformational impact on individuals, businesses, and governments around the world.
facilitating the growth of big data, and networks are fast becoming the key link among data generation, analysis, processing, and utilization.
or encumber, the full impact of big data and the Ioe including standards and interoperability, privacy and security, spectrum and bandwidth constraints, crossborder data traffic, legacy regulatory models, reliability, scaling, and electrical power.
Big data Maturity: An Action Plan for Policymakers and Executives In Chapter 1. 3, Bahjat El-Darwiche, Volkmar Koch, David Meer, Ramez T. Shehadi,
and Walid Tohme of Booz & Company argue that big data has the potential to improve
Big data can pave the way for disruptive, entrepreneurial companies and allow new industries to emerge.
but technology alone is insufficient to allow big data to show its full potential and to prevent companies from feeling swamped by this information.
Organizations need to understand where they are in terms of big data maturity, an approach that allows them to assess progress
considering an organization's internal capabilities and how ready it is to implement big data initiatives;
and more complicated methods for using big data, which can mean simple efficiency gains or revamping a business model.
They should present citizens with a compelling case for the benefits of big data. This means addressing privacy concerns
Policymakers should establish an environment that facilitates the business viability of the big data sector (such as data
and they should take educational measures to address the shortage of big data specialists. As big data becomes ubiquitous in public and private organizations,
its use will become a source of national and corporate competitive advantage. Balancing the Risks
and Rewards of Data-Driven Public Policy Alex Sandy Pentland from the Massachusetts institute of technology (MIT) highlights in Chapter 1. 4 that we are entering a big data world,
while at the same time providing greater security for organizations that use xiv The Global Information technology Report 2014 Executive Summary 2014 World Economic Forum big data.
allowing us to safely reap the advantages of using big data to help set and monitor public policy.
Managing the Risks and Rewards of Big data In Chapter 1. 5, . Matt Quinn and Chris Taylor from TIBCO argue that expert handling of big data brings the reward of being able to react to world-changing events,
both big and small, at an unprecedented rate and scope. Epidemics can be tracked and miracle drugs developed, for example,
but at the same time, big data brings risks that require balancing those benefits against privacy concerns raised by the potentially unsettling correlation of personal information.
Big data leverages previously untapped data sources to liberate information from places where it was hidden previously.
Big data management requires automation wherever possible, because volume and complexity eliminate the ability of humans to intervene
Big data forces us to create adaptable, less fragile data systems because the sheer variety of structured and unstructured data breaks the old computational and transactional ways of writing logic.
Big data holds unseen patterns, which need to be visualized using analytics tools and techniques. Insights gained must be used at the right time, in the right context,
These elements are the driving forces behind making use of big data in increasingly sophisticated ways. The chapter cites examples in healthcare, logistics,
and retail where big data is being tackled with a systems approach that takes into consideration information streaming constantly as well as
what is found in historical databases that cut through the mystique of The Global Information technology Report 2014 xv Executive Summary 2014 World Economic Forum big data
and get to the core of understanding big data's risks and rewards. Rebalancing Socioeconomic Asymmetry in a Data-Driven Economy Chapter 1. 6, contributed by Peter Haynes of the Atlantic Council
The Role of Regulation in Unlocking the Value of Big data In Chapter 1. 7, Scott Beardsley, Luís Enríquez, Ferry Grijpink, Sergio Sandoval, Steven Spittaels,
and Malin Strandell-Jansson from Mckinsey & Company highlight the expectation that big data will create great benefit for society, companies,
These issues might hamper public trust in big data applications and companies and hinder the development of big data to its full potential.
The issues of concern include how to define personal data, how to treat anonymous data, whether to allow the right to be forgotten,
From Big data to Big Social and Economic Opportunities: Which Policies Will Lead to Leveraging Data-Driven Innovation's Potential?
commentators have been driven to call this revolution the age of big data. However, what is commonly known as big data is not a new concept:
the use of data to build successful products and services, optimize business processes, and make more efficient data-based decisions already has established an history.
Moreover, the term big data is ambiguous: the main features of big data (quantity, speed, variety) are technical properties that depend not on the data themselves but on the evolution of computing, storage,
and processing technologies. What is important about big data is not its volume but how it may contribute to innovation
and therefore be used to create value. This is why this chapter uses data-driven innovation to frame the discussion.
Making Big data Something More than The next Big Thing In Chapter 1. 9.,Anant Gupta, Chief executive officer at HCL Technologies Ltd, argues that big data analytics is not a passing fad.
and Rewards and Risks of Big data 2014 World Economic Forum 2014 World Economic Forum The Global Information technology Report 2014 3 CHAPTER 1. 1 The Networked Readiness
Benchmarking ICT Uptake in a World of Big data BEÑAT BILBAO-OSORIO, World Economic Forum ROBERTO CROTTI, World Economic Forum SOUMITRA DUTTA, Cornell University BRUNO LANVIN,
EXTRACTING VALUE FROM BIG DATA Data have had always strategic value, but with the magnitude of data available today and our capability to process them they have become a new form of asset class.
this new asset class of big data is described commonly by what we call the three Vs.
Big data is high volume, high velocity, and includes a high variety of sources of information. Next to those three Vs we could add a fourth:
and this is why big data today gets so much attention. In the quest for value, the challenge facing us is how to reduce the complexity
and unwieldiness of big data so that it becomes truly valuable. Big data can take the form of structured data such as financial transactions or unstructured data such as photographs or blog posts.
It can be crowd-sourced or obtained from proprietary data sources. Big data has been fueled by both technological advances (such as the spread of radio-frequency identification, or RFID
chips) and social trends (such as the widespread adoption of social media. Our collective discussions, comments, likes, dislikes,
and studied within the realm of big data. Big data has arrived. It is changing our lives and changing the way we do business.
Some examples include the following: Google uses big data to predict the next wave of influenza. 2 IBM uses data to optimize traffic flow in the city of Stockholm,
3 and to get the best possible air quality. Dr. Jeffrey Brenner, a physician in New jersey, uses medical billing data to map out hot spots where you can find his city's most complex and costly healthcare cases as part of a program to lower healthcare
which courses. 5 But succeeding with big data requires more than just data. Data-based value creation requires the identification of patterns from
To a large extent, mastering big data can also be compared to irrigation. It is not enough to bring water to where it can create fertility and value.
The stakes are not dissimilar when applied to big data, but this is a resource that could benefit the entire planet instead of just one country.
The Economist Intelligence Unit released survey data showing that approximately two-thirds of executives feel that big data will help find new market opportunities
and make better decisions. 6 Nearly half of the surveyed respondents feel big data will increase competitiveness,
This world of big data has also become a source of concern. The consequences of big data for issues of privacy and other areas of society are understood not yet fully.
Some prominent critics, such as Jaron Lanier, 7 call on us to be cautious about readily believing any result created by the wisdom of the crowd.
applications of big data in military intelligence have created a growing concern for privacy around the world. Indeed, we are now living in a world where anything
Large amounts of data, often referred to as big data, are generated constantly both in a structured and non-structured manner.
However, success in extracting this value requires more than just the generation of or access to big data.
the potential of big data to be misused is also increasingly becoming a source of concern. Privacy issues,
and the rise of big data can yield in generating growth and high-quality employment in a rapidly changing context.
Getting More out of Big data. White paper, sponsored by Oracle and Intel. London, New york, Hong kong, and Geneva:
How the Network Unleashes the Benefits of Big data ROBERT PEPPER JOHN GARRITY Cisco systems Exabytes (1018) of new data are created every single day.
facilitating the growth of big data, and fast becoming the key link among data generation, processing, analysis, and utilization.
and can accelerate big data's transformational impact on individuals, businesses, and governments around the world.
either accelerate or encumber the full impact of big data and the Ioe. ACCELERATING DATA PRODUCTION AND DATA TRAFFIC Data growth is skyrocketing.
For governments, Ioe and big data applications are helping to monitor pandemics and environmental conditions, improve public safety and security,
The Ioe will not only fuel the expansion of big data and data transmission, but can also provide targeted, automatic, data-driven analysis for our day-to-day lives.
Big data: Huge and growing data volume from industrial applications Industrial applications of the Internet of Everything (Ioe) generate immense data flows,
At an industrial level, big data analysis can yield very large benefits. For example, the value of modernizing the US electricity grid to be driven data is estimated at US$210 billion.
The Internet of Everything 38 The Global Information technology Report 2014 2014 World Economic Forum EQUIPPING IP NETWORKS TO DELIVER BIG DATA INSIGHTS Moving up the knowledge pyramid from data to insights
TECHNICAL AND POLICY CHALLENGES Building a network that will maximize the impact of big data requires powerful and seamless interactions among sensors
But although IP networks are primed to support the expansion of big data and the Ioe, technical and policy challenges exist in the ability of current IP networks to fully exploit big data expansion (Figure3).
An approach that tackles these issues concurrently will help to create the right ecosystem. The discussion below highlights specific issues that will need to be addressed thoughtfully.
Policy and technical issues facing big data and the Ioe Standards & interoperability Privacy & security Spectrum & bandwidth constraints Reliability Scaling Electrical power Cross-border data traffic
The key security issues for big data include the reliable prevention of hacking and access by unauthorized and unwanted users to large databases and data flows.
and businesses feel safe in engaging in big data activities, network security is essential. Over the next five years, the growth of mobile data traffic will require greater radio spectrum to enable wireless M2m,
and the Ioe and the era of big data are transforming our lives. Data flows and the ability to capture value from data are changing industries,
if IP networks are able to facilitate the rise of big data and generate added positive impact for society.
The Big Deal about Big data in Oil and Gas. Hitachi. Available at www. lnm. com. br/bah/downloads/Hitachi bert-Beals BAH2013. pptx.
Defining Big data report. September 27. Palo alto, Shanghai, Singapore, and Reading, UK: Canalys. Cisco. 2012. Cisco Global Cloud Index:
The Rise of Big data: How It's Changing the Way We Think about the World. Foreign affairs May/June.
Available at http://www. foreignaffairs. com/articles/139104/kenneth-neil-cukier-and-viktor-mayerschoenberger/the-rise-of-big data.
Big data and Decision making, June 12. Report commissioned by Capgemini. Available at http://www. managementthinking. eiu. com/sites/default/files/downloads/The%20deciding%20factor final. pdf. EMC2. 2013.
Big data, Bigger Digital Shadows, and Biggest Growth in the Far east. IDC iview, sponsored by EMC.
Big data. Available at http://www. ibm. com/bigdata/us/en/./IBM Software. 2012. Managing Big data for Smart Grids and Smart Meters.
IBM White paper. Somers, NY: IBM Corporation. Available at ftp://public. dhe. ibm. com/software/pdf/industry/IMW14628USEN. pdf. Leber, J. 2012.
Big Oil Goes Mining for Big data. MIT Technology Review, May 8. Available at http://www. technologyreview. com/news/427876/big-oil-goes-mining-for-big data/.
/Lopez, M. 2013. GE Speaks on the Business Value of the Internet of things. Forbes. com, May 10.
Big data: An Overview. Going deep on Big data. ZDNET special feature, October 1. Available at http://www. zdnet. com/big data-an-overview-7000020785/.
/Palmer, M. 2006. Data Is the New Oil. Blog Post, November 3. Available at http://ana. blogs. com/maestros/2006/11/data is the new. html. Taft, J.,with P. De Martini and L. von Prellwitz. 2012.
Utility Data Management and Intelligence. Cisco. http://www. cisco. com/web/strategy/docs/energy/managing utility data intelligence. pdf. Top500. org. 2013.
The Internet of Everything 42 The Global Information technology Report 2014 2014 World Economic Forum CHAPTER 1. 3 Big data Maturity:
90 percent of the total data stored today is less than two years old. 1 So-called big data has the potential to improve
THE BIG DATA IMPERATIVE If they are to capitalize on this potential, organizations should avoid a common misapprehension.
it is not sufficient to enable big data to be exploited fully. Organizations must instead remold their decisionmaking culture
We propose a Big data Maturity Framework that is based on the experiences of organizations that have undergone a big data transformation.
and (3) the various, steadily more sophisticated, ways to use big data that range from increased efficiency in existing operations to a complete change in an organization's business model.
WHAT IS BIG DATA? Big data represents the newest and most comprehensive version of organizations'long-term aspiration to establish
and improve their data-driven decision-making. It is characterized by what are known as the three Vs large data volumes, from a variety of sources, at high velocity (i e.,
which are kept typically in organizations'data warehouses, big data builds on unstructured data from sources such as social media, text and video messages,
For example, in 2012 Facebook reported that it was processing around 2. 5 billion new pieces of content daily. 2 Big data has the potential to infuse executive decisions with an unprecedented level of data-driven insights.
However, research indicates that many organizations are struggling to cope with the challenges of big data. For example
had increased by up to 25 percent during the previous year. 3 EVOLUTION, NOT REVOLUTION Despite the rapid growth of big data,
Although remarkable, the big data phenomenon is merely the continuation of a journey in which ever-moreelaborate data have influenced decision-making.
The latest development, big data, may appear all-enveloping and revolutionary. However, the essential principles for exploiting its commercial benefit remain exactly the same as they were in previous moves toward increased data-driven decision-making.
Degree of sophistication Volume/complexity of data BIG DATA Chapter 1. 3: Big data Maturity 44 The Global Information technology Report 2014 2014 World Economic Forum performance or allow them to gain access to new revenue pools.
This continuation of a trusted managerial approach does not, however, imply an endorsement of inertia.
Rather, organizations must foster a new decision-making culture to exploit the opportunities presented by big data
At the same time, they must encourage governments to nurture an environment conducive to the exploitation of big data.
THE BUSINESS IMPACT OF BIG DATA Many organizations are still in the early stages of reaping the benefits of big data.
Andrew Mcafee and Erik Brynjolfsson explored the impact of big data on corporate performance. The authors interviewed executives in 330 publicly traded companies in the United states. They then examined relevant performance data,
which corporate attitudes toward big data correlated with how the respective companies were faring. Mcafee and Brynjolfsson's conclusions were remarkable for establishing a connection between big data and performance:
The more companies characterized themselves as data-driven, the better they performed on objective measures of financial and operational results.
broad adoption of advanced big data practices has materialized not yet. A 2013 Gartner survey found that less than 8 percent of companies surveyed have deployed actually big data technology. 5 Investment in forthcoming projects is much more widespread;
the research firm IDC has forecasted that the market for big data technology and services will reach US$16. 9 billion by 2015, up from US$3. 2 billion in 2010.
This represents a 40 percent annual growth rate, seven times the rate for the overall ICT business. 6 This trend is affecting all regions.
For example, over 40 percent of chief information officers in the middle East, according to IDC, are considering big data technology investment in 2013.
Although few have undertaken actually large-scale big data or analytics programs to date, IDC forecasts investment in this area to grow at a compound annual growth rate of over 20 percent over the coming five years. 7 Both expenditure
and travel still tend to spend substantially more on big data projects than the energy sector,
and there is far more implementation of big data initiatives in the United states than in the Asia Pacific region.
Meanwhile, the Economist Intelligence Unit found that big data is enlisted most frequently to assist financial management and marketing/sales,
and deemed least valuable in human resources management. 8 How big data is used The big data maturity stages (Figure2) depict the various ways in which data can be used,
Depending on the maturity of an organization's big data capabilities, big data can significantly increase top-line revenues
and markedly reduce operational expenses. The path to business model transformation, the highest level of maturity, promises potential high returns but often involves major investment over many years.
Advances in operational efficiency through big data such as the efficient deployment of staff resources and the optimization of the supply chain, also reside within this maturity stage.
organizations start to monetize big data, positioning it as a value driver of the business that offers a new source of competitive advantage beyond the mere improvement of operations or services.
Big data Maturity 2014 World Economic Forum deriving insights from it. This may include innovations such as customized,
Big data maturity stages and related use cases Source: Booz & Company. Maturity stages Typical use cases/applications Stage 1:
, web search, web advertising) Quantitative management of investment funds Crowdsourcing to augment internal data Large-scale implementation Experimenting/selective adoption BIG DATA Chapter 1. 3:
Big data Maturity 46 The Global Information technology Report 2014 2014 World Economic Forum of parking space at all times.
big data permeates the whole organization. It becomes deeply embedded within the operation, determining the nature of the business and the mode of executive decision-making.
Omnicom and Publicis believe that their combined size will produce the desired volume of Data general Electric (GE) provides a prominent example of a product organization placing great faith in big data.
and analytics services across business functions and geographies. 11 Another showcase for the transformative potential of big data comes from the public sector. Regional and national-level policymakers around the world are launching open data initiatives,
the release of public data is an important environmental factor enabling organizations to use big data,
However, some organizations do not have to progress through all the big data maturity stages. A data-driven business model has been integral to companies such as Google, Facebook,
Obstacles to progress Despite widespread interest in data-driven decisionmaking in one form or another, companies face many potential pitfalls in extracting the maximum commercial benefit from big data usage.
Embracing the potential of big data as a concept will take organizations only so far. First and foremost
As big data extends its reach, executive instinct is challenged by the facts of hard data. However, while data can be of great assistance in solving an actual problem
These details are collected all without that person's explicit consent, leading to significant public reservations about big data.
potentially limiting companies'ability to exploit big data opportunities or exposing them to threats of legal and regulatory intervention.
HOW TO REACH BIG DATA MATURITY Our big data maturity framework (Figure3) comprises three elements: the enablers of environment readiness, the organization's internal capabilities,
and the different stages of maturity and sophistication in which big data can be used. The framework enables organizations to view the extent of their success in overcoming obstacles,
and identifies what more can be done to promote big data maturity and reach the desired destination.
Big data Maturity 2014 World Economic Forum The environment readiness dimension considers how far the relevant governments have enabled organizations in their jurisdiction to use big data freely and productively.
The organization's internal capabilities dimension sheds light on a company's readiness to execute big data.
By building up these capabilities and integrating them effectively, organizations move further along the path of data-driven decision-making and position themselves to extract greater benefits from big data.
While environment readiness serves as an enabler for big data usage internal capabilities act as critical success factors for organizations seeking to progress through the maturity stages.
Priorities for policymakers Big data will soon become ubiquitous practice in both the public and private worlds.
enable a big data ecosystem by establishing policies to facilitate valid business models for third-party data, service,
and handle big data from both a business and an IT perspective, potentially in public-private partnerships (PPPS).
Big data maturity framework Source: Booz & Company. Enablers of environment readiness Success factors for internal capabilities Maturity stages in the usage of big data Traditional applications (getting more out of data you already have) New horizons of big data Technical capabilities/infrastructure
Regulatory framework for data privacy Dataavailability andgovernance ICT infrastructure Sponsorship Big data ecosystem Organizational capabilities and resources Public perception and awareness Data-driven decision-making culture
Education/training Stage 1: Performance management Stage 2: Functional area excellence Stage 3: Value proposition enhancement Stage 4:
Big data Maturity 48 The Global Information technology Report 2014 2014 World Economic Forum Priorities for policymakers will vary in different parts of the world.
and education programs to prepare for large-scale demand from organizations intent on using big data. In more developed countries,
and promoting a public-interest argument for big data. Policymakers must make the case for big data In particular,
policymakers should set clear rules regarding data privacy so that organizations know which personal data they can store and for how long,
skeptical citizens must first be persuaded that big data will work in their favor by paving the way for better products and services.
and inform this public debate about the benefits of big data. Indeed, Jules Polonetsky and Omer Tene, in their Stanford Law Review article (2013), argue that finding the right balance between individuals'legitimate privacy concerns
and the overall rewards offered by big data practices may be the greatest contemporary public policy challenge. 13 The outcome of this debate will vary depending on the country.
this lack of harmonization threatens the adoption of big data on an international scale. The prevailing patchwork situation accentuates the lack of clarity on lawful data usage especially the question
Priorities for executives There is no general rule dictating how organizations should navigate the stages of big data maturity.
develop a clear (big data strategy; prove the value of data in pilot schemes; identify the owner for big data in the organization
and formally establish a Chief Data Scientist position (where applicable); recruit/train talent to ask the right questions
position big data as an integral element of the operating model; and establish a data-driven decision culture
Quick wins Organizations should resist expensive upfront infrastructure investments for overly ambitious big data projects. Instead, they should select opportunities for high business impact
Big data Maturity 2014 World Economic Forum one such quick win. For example, a mobile phone operator can collect anonymized real-time travel patterns,
Social media platforms are demonstrated also to be great sources of relevant big data for example for sentiment analysis (to determine the voice
In addition to sourcing data from outside the organization, the selective use of external analytics service providers can also prove instrumental in establishing big data maturity quickly,
CONCLUSION We currently see big data as poised to have significant impact in public and business spaces alike.
Largescale investment is flowing into establishing big data capabilities in many organizations, despite the limited number of cases in which it has been used successfully in completed projects and initiatives.
organizations confront vast differences in their ability to utilize big data to good effect, as seen in their stages of big data maturity.
These differences range from adopting big data practices for operational improvement in selected functional areas or building or revamping an organization's value proposition to completely transforming their business model based on big data.
At the more advanced stages, organizations learn to monetize big data far beyond simply getting better at
what they are currently doing; learning this lesson is an accomplishment that can mean a fundamental shift for them.
Environment readiness plays a pivotal role in enabling such success, because its effect is far greater than the evolution of individual organizations'internal capabilities
and usage levels of big data. Nonetheless, policymakers and organizations in general still have much to do if they want to realize the full potential of big data.
For their part, governments throughout the world need to create a supportive environment for the usage of big data to attract business to their region.
Meanwhile, organizations must act in a timely manner to determine how they can most effectively deploy big data.
They will have to predict what the world of data-driven insights will look like in the medium term,
Within the next five years, big data will become the norm, enabling a new horizon of personalization for both products and services.
Wise leaders will soon embrace the game-changing opportunities that big data affords for their societies and organizations,
What Is Big data? 2 Constine 2012.3 Aberdeen Group 2013.4 Mcafee and Brynjolfsson 2012, p. 6. 5 Gartner 2013.6 The New york times 2012.7 ITP. net 2013.8 The Economist
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Constine, J. 2012. How Big Is Facebook's Data? 2. 5 Billion Pieces of Content and 500+Terabytes Ingested Every day.
Big data Adoption in 2013 Shows Substance Behind the Hype. Available at http://www. gartner. com/id=2589121.
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#Ukrz9oasiso. Mcafee, A. and E. Brynjolfsson. 2012. Big data: The Management Revolution. Harvard Business Review, October.
Available at http://hbr. org/2012/10/big data-the-management-revolution. Munford, M. 2013. Don't Follow the Leaders, Watch the Parking Meters.
The Daily telegraph, September 15. Available at http://www. telegraph. co. uk/technology/news/10307926/Dontfollow-leaders-watch-the-parking-meters. html. Chapter 1. 3:
Big data Maturity 50 The Global Information technology Report 2014 2014 World Economic Forum The New york times. 2012.
IDC Sizes Up the Big data Market, March 7. Available at http://bits. blogs. nytimes. com/2012/03/07/idcsizes-up-the-big data-market/?
/r=0. OECD (Organisation for Economic Co-operation and Development. 2013. OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal data.
Available at http://www. oecd. org/internet/ieconomy/oecdguidelinesonthe protectionofprivacyandtransborderflowsofpersonaldata. htm. Polonetsky, J. and O. Tene. 2013.
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Big data Maturity 2014 World Economic Forum 2014 World Economic Forum CHAPTER 1. 4 Big data: Balancing the Risks and Rewards of Data-Driven Public Policy ALEX PENTLAND MIT In June 2013,
This chapter will outline both the risks and the rewards of this new age of big data
A BIG DATA TAXONOMY It is probably hopeless to try to provide a detailed taxonomy of data types
because the strengths and weaknesses of big data analysis are very different from those obtained through standard information sources.
With the advent of big data, we can potentially develop many more types of data commons; these commons can be both accessible in real time and far more detailed than previous, hand-built data commons (e g.,
which would diminish the ability of such a data commons to enable significant public goods. To explore the viability of a big data commons,
what is perhaps the world's first true big data commons was unveiled on May 1, 2013. In this Data for Development (D4d) initiative, 90 research organizations from around the world reported hundreds of results from their analysis of data describing the mobility
Big data: Balancing the Risks and Rewards of Data-Driven Public Policy 54 The Global Information technology Report 2014 2014 World Economic Forum Box 1:
The future of big data and governance The Data for Development (D4d) data commons is only a small first step toward improving governance by using big data.
Big data gives us for the first time a chance to view society in all its complexity, composed of millions of networks of person-toperson exchanges.
computational social scientists have begun to discover how to leverage big data and have been using datasets from companies such as cell phone carriers and social media firms.
Big data: Balancing the Risks and Rewards of Data-Driven Public Policy 2014 World Economic Forum These selected results are just a small sample of the impressive work that is made possible by this rich and unique data commons.
Each of these D4d research projects has demonstrated the great potential of a big data commons for improving people's living conditions.
Big data: Balancing the Risks and Rewards of Data-Driven Public Policy 56 The Global Information technology Report 2014 2014 World Economic Forum themselves.
the government must organize big data resources in a distributed manner, with each different type of data separated
What does all this have to do with the danger that a big data government will trample individual freedoms?
Big data: Balancing the Risks and Rewards of Data-Driven Public Policy 2014 World Economic Forum the requested records) remains hidden.
and cyberattack are among the greatest dangers that companies face in the big data era. A distributed architecture of databases joined with a network that supports permissions, provenance,
SUMMARY We are entering a big data world, where governance is driven far more by data than it has been in the past.
This chapter has suggested one path that can limit potential abuses of power while at the same time providing greater security for organizations that use big data.
Big data: Balancing the Risks and Rewards of Data-Driven Public Policy 58 The Global Information technology Report 2014 2014 World Economic Forum found within modern computer databases and networks.
allowing us to safely reap the advantages of using big data to help set and monitor public policy.
Big data: Balancing the Risks and Rewards of Data-Driven Public Policy 2014 World Economic Forum 2014 World Economic Forum CHAPTER 1. 5 Managing the Risks and Rewards of Big data
MATT QUINN CHRIS TAYLOR TIBCO One of the biggest challenges of the term big data is deciding on a standard definition of what those words really mean.
For many companies that have worked in an environment of large datasets, fast-moving information, and data that lack traditional structure, working in an environment of big data is just business as usual.
In this chapter we will discuss how managing the growing challenge of data is not new for a regional healthcare organization in the Midwestern United states
the term big data itself is a way to express the sudden digitization of many things that have been with us forever
For most companies, big data represents a significant challenge to growth and competitive positioning. In some cases, it represents the survival of the business.
BIG DATA: RISKS AND REWARDS Digitization itself is not new, but the maturation and availability of the Internet;
The term big data represents the need for a new way of thinking but also implies new tools and new ways of managing data.
Big data in its outsized properties, amplifies those effects. It is in those extremes that the risks
and rewards of big data are decided. THREE KEY BIG DATA TRENDS As the world becomes more familiar with big data,
three key trends that have a significant impact on those risks and rewards are emerging.
First and foremost, big data leverages previously untapped data sources. Those sources are of several types. The first includes wearable devices that stream data about an individual
making big data even bigger than human-generated information. The third type of sensor provides constant reporting by machines that perform the work critical to our security, health, and lifestyle.
Big data's effectiveness is coupled tightly to an organization's ability to bring the right data together in the right moments that allow for the right response and outcome.
The desire to affect outcomes brings about the second trend of big data: the need for automation technologies.
The challenge of the decreasing value of data over time has become even more meaningful in the age of big data.
The value-time curve challenge makes big data management a function of creating automation wherever possible.
and big data follows the same path. Big data's growth in each of its dimensions eliminates the ability for humans to intervene
and reprogram processes in real time, opening the door for better and better tools that can manage data far more quickly
The big data conversation often centers on the use of machines as the best resource for the storage and analytic processing of vast amounts of data,
The third trend being driven by big data is the necessity for adaptable, less fragile systems. For big data to leverage previously untapped sources of information,
organizations need to quickly adapt to the opportunities and risks represented by these new sources.
Automated systems that manage big data ecosystems cannot be developed around rigid schemas that require redevelopment for each new stream of information.
and Rewards of Big data 62 The Global Information technology Report 2014 2014 World Economic Forum RESOLVING TWO PRIMARY CHALLENGES OF BIG DATA Most organizations need to overcome two primary challenges before becoming productive
with big data. The first is need the for powerful visualization that allows the business to explore data to find questions worth answering.
as the pre big data model began with the business asking a question and ended with information technology structuring data to answer those questions in a very repeatable way,
when people talk about big data they often use the term to compartmentalize it and give it boundaries.
Thinking of big data in those terms fails to take into account all of the data being created everywhere, every day.
and Rewards of Big data 2014 World Economic Forum data not with the goal of having a larger dataset,
ENSURING THAT HUMANS STAY IN THE LOOP For exactly this reason we need to take a very careful approach to how big data is being used
Many of the risks and rewards of big data are coupled tightly to the use of all of those data.
Personalization and healthcare offer two standout opportunities for big data to reward us. At the same time, big data comes with privacy concerns that are not simply related to technology
but are also about very human things such as privacy, all-knowing creepiness, and personal security. Given enough personal data
and Rewards of Big data 64 The Global Information technology Report 2014 2014 World Economic Forum stretching of the boundaries of individual expectations.
Throughout the evolution of big data, the capability to govern data appropriately has existed, but unless organizations make the choice themselves
SHOWING BIG DATA'S SOPHISTICATED SYSTEMS Gaining benefits from big data while mitigating risks is entirely a matter of data systems sophistication.
This section will explore three examples that demonstrate the successful use of big data. The first example of that sophistication is on display at a major network of hospitals in the Midwest to address the problem of sepsis the systemic infection of the body which is a constant threat to hospitalized patients.
Like healthcare, logistics is an age-old practice undergoing big data transformation. It has become far more complicated in recent years because of the explosion of data that connect the customer's customer and the supplier's supplier.
In retail, the management of big data supports a brand's ability to predict the best product offering
and greatly improves customer service execution. 4 Big data offers an enormous reward to retail because successful selling is ultimately about having an excellent understanding of customers and the circumstances in
and Rewards of Big data 2014 World Economic Forum ideal way to gain that access and avoid the creepiness factor.
and creating less fragile data systems are crucial parts of ensuring the benefits of big data while mitigating its risks.
Accomplishing these three objectives requires successfully meeting big data's two main challenges: the need to visualize by using analytics tools
Big data has a remarkable ability to change the world. Its benefits need to be considered as a function of how well its risks are managed.
Truly expert handling of big data brings the reward of being able to react to world-changing events, both big and small, at an unprecedented rate and scope.
big data should be working for the benefit of humans, not the other way around. Organizations that manage big data have an obligation to monitor security device, server,
and application logs, all of which generate machine data that provide insight into how, when, and why machines are communicating with other machines.
Organizations, both public and private, must balance the risks and rewards of big data especially as big data moves from low impact experiments to driving real-time operations and decision-making.
Big data is a fast-moving technology space that will affect all aspects of our lives.
and challenges will shape the path forward for organizations that wish to be deliberate and wise about their use of big data.
Managing the Risks and Rewards of Big data 66 The Global Information technology Report 2014 2014 World Economic Forum CHAPTER 1. 6 Rebalancing Socioeconomic Asymmetry in a Data-Driven
The recent emergence of big data along with what is being called the data-driven economy, may finally make possible a true knowledge economy by
the majority of big data will be collected passively and automatically, via machineto-machine transactions, and users will not be involved actively in the majority of those transactions.
Big data, then, truly does promise to create new knowledge and indeed new kinds of knowledge on
Moreover, in the world of big data, it would be impractical, if not impossible, for individuals to give express consent for all the data that may be generated about them.
and analytics of big data is how little we actually know about it its potential risks and rewards,
or similar approaches that address these concerns, will be essential to establish the concept of fair value exchange in the world of big data.
Big data: The next Frontier for Innovation, Competition and Productivity. Mckinsey Global Institute Report, May. Available at http://www. mckinsey. com/insights/business technology/big data the next frontier for innovation.
The Role of Regulation in Unlocking the Value of Big data SCOTT BEARDSLEY LUIS ENRIQUEZ FERRY GRIJPINK SERGIO SANDOVAL STEVEN SPITTAELS MALIN STRANDELL-JANSSON Mckinsey
when speaking about the value of big data earlier in 2013. As Kroes noted, data comprise a fuel we have begun only just to tap.
Definitions of big data vary greatly. Rather than put a number on what qualifies as big,
big data is acknowledged widely to create value in four ways. It creates greater transparency by making more and better information available more quickly.
Big data can create significant value for the whole economy. Mckinsey research shows that companies that use big data can deliver productivity
and profit gains that are 5 to 6 percent higher than those of competitors. The private sector is not the only beneficiary, however.
Big data can also enhance productivity and effectiveness of the public sector and create economic surplus for consumers.
For example, the Mckinsey Global Institute estimates that US healthcare expenditure could be reduced by 8 percent by using big data to drive efficiency and quality.
No wonder, then, that governments and political institutions are promoting big data on their agendas and adopting initiatives such as the European union's open data directive,
The Role of Regulation in Unlocking the Value of Big data 74 The Global Information technology Report 2014 data.
Governments understand that big data's economic and social potential can grow only alongside continued innovation in the underlying technologies, platforms,
The uptake of big data will depend on the adoption of nextgeneration telecommunications infrastructure, which is still in its early development in many parts of the world.
Equally, big data uptake will hinge on whether ways can be found to protect information technology infrastructures and the data they carry from cyberattacks.
while not stifling the enormous potential of big data, and it outlines some actions companies can take themselves to promote consumer trust.
CONSUMER TRUST AS AN ENABLER OF BIG DATA Research reveals that consumers are concerned increasingly about how their personal data are used (Figure1
If big data is to deliver on its promise, companies will need both to create customer trust in big data applications
and their use and to help customers feel safe about the protection of their personal data and privacy.
At the same time, these policies must not stifle the innovation that big data can deliver, or its attendant economic and social benefits.
The Role of Regulation in Unlocking the Value of Big data used. They have a right to be informed
KEY REGULATORY AREAS FOR BIG DATA UPTAKE Whatever approach any single government or regulator chooses to adopt,
The Role of Regulation in Unlocking the Value of Big data 76 The Global Information technology Report 2014 Figure 2:
The Role of Regulation in Unlocking the Value of Big data data can drive, while maintaining customer trust and data protection.
tedious process for companies and consumers alike and can hinder big data development. Cookies on the Internet are a simple example.
In a big data world where a lot of data are interlinked, it can be difficult to know exactly
However, in a big data world where anonymized data can easily be linked up, it is not very hard to build a profile of a person without traditional means of identification such as a name or address.
The Role of Regulation in Unlocking the Value of Big data 78 The Global Information technology Report 2014 consumers alike.
In today's world, companies often cooperate to produce big data applications and solutions. One company orders software from another,
and clarified so that both consumers and companies using big data clearly know what the rules are
and companies to make the big data environment more certain. IMPLICATIONS FOR REGULATORS AND POLICYMAKERS Regulators will need to address all the above issues
An even a wider take on data protection issues in the big data environment would be beneficial for all parties.
in markets such as the United states and the United kingdom. An international industry standard specifically concerning the use of personal data protection in big data would certainly be beneficial to establish a higher level of trust among consumers
To maximize the benefits of big data and to build trust, a number of actions could be considered.
and determine the best way to leverage those strengths to develop their big data strategy. For example
The Role of Regulation in Unlocking the Value of Big data Companies should strive to make data protection part of the company culture.
and policymakers understand the business issues at hand and the benefits of big data for society. Furthermore
Providing transparent privacy policies or simply informing the customer of the scope of data handling as well as requesting clear consent declarations from customers also helps create customer trust without sacrificing big data business opportunities.
CONCLUSION Big data offers a wide range of opportunities not just for individual companies, but also for nations and society as a whole.
and policy concerns regarding big data development. They must enable fast network build-out. They must also ensure the education and training of a qualified workforce and safeguard Internet safety.
It is only by addressing customer concerns at different levels within the industry that the big data industry can eventually evolve to its full potential.
The Role of Regulation in Unlocking the Value of Big data 80 The Global Information technology Report 2014 Council of europe. 1981.
The Big data Revolution. Speech given by Neelie Kroes, Vice president of the European commission responsible for the Digital Agenda, March 26.
The Economic and Social Benefits of Big data. Speech given by Neelie Kroes, Vice president of the European commission responsible for the Digital Agenda, May 23.
Big data: The next Frontier for Innovation, Competition and Productivity. Mckinsey Global Institute Report, May. Available at http://www. mckinsey. com/insights/business technology/big data the next frontier for innovation.
Available at http://dornsife. usc. edu/usc-lat-poll-privacy-march-2012/.2014 World Economic Forum CHAPTER 1. 8 From Big data to Big
We will therefore talk about data driven-innovation instead of big data, and will provide case studies from different areas,
WHY SPEAK OF DATA-DRIVEN INNOVATION INSTEAD OF BIG DATA? It has become axiomatic that more data are produced every year,
and somehow this phenomenon has driven commentators to call this revolution the age of big data. However, what is commonly known as big data is not a new concept,
as the use of data to build successful products and services, optimize business processes, or make more efficient data-based decisions already has established an history.
the term big data is ambiguous, and it sets up data as a negative because of the implication that big is bad.
Indeed, many common definitions of big data usually focus not on size but instead on various characteristics, including the frequency of production, speed, volume, variety,
for example, describes big data as datasets whose size is beyond the ability of typical database tools to capture,
store, manage and analyze. 10 The implications of this definition are that the main features of big data (quantity, speed,
and processing technologies. 11 What may look like big data today will not likely be as big in the near future.
When big data is no longer a trendy concept, data will continue to drive innovation, and solutions for new problems will come from new ways of analyzing
From Big data to Big Social and Economic Opportunities 82 The Global Information technology Report 2014 2014 World Economic Forum to download and use.
From Big data to Big Social and Economic Opportunities 2014 World Economic Forum SETTING THE STAGE FOR A DATA-DRIVEN ECONOMY Apart from producing
From Big data to Big Social and Economic Opportunities 84 The Global Information technology Report 2014 2014 World Economic Forum data analysis, information science, metadata and data visualization.
Talking about this phenomenon as big data, however, misses the true potential of data. Instead, we should focus our discussion on data-driven innovation,
It is by looking at the big picture surrounding big data that we can create the right environment for data-driven innovation,
History of the Farmer's Almanac. 8 Platzman 1979.9 Hemerly 2013.10 Manyika et al. 2011.11 OECD 2013.12 According to Hilbert (2013, p. 4), the crux of the‘Big data'paradigm is actually not the increasingly large
From Big data to Big Social and Economic Opportunities 2014 World Economic Forum REFERENCES Brynjolfsson, E.,L. M. Hitt,
Big data and Digitizing the Farm. Canadian Startup News, August 7. Available at http://www. betakit. com/semios-big data-and-digitizing-the-farm/.
/Hemerly, J. 2013. Public Policy Considerations for Data-driven Innovation. Computer (IEEE Computer Society) 46 (6): 25 31.
Big data for Development: From Information-to Knowledge Societies. January 15. Available at http://dx. doi. org/10.2139/ssrn. 2205145.
The IBM Big data Platform. New york: IBM Corporation. Available at http://public. dhe. ibm. com/common/ssi/ecm/en/imb14135usen/IMB14135USEN. PDF. Lu, X.,L. Bengtsson,
Big data: The next Frontier for Innovation, Competition, and Productivity. Mckinsey Global Institute Report, May. Available at http://www. mckinsey. com/insights/business technology/big data the next frontier for innovation.
Big data: A Revolution That Will Transform How We Live, Work, and Think. New york: Houghton Mifflin Harcourt.
Big data Approach Leads to More Accurate Hurricane Forecasting. News from Mccormick, September 25. Available at http://www. mccormick. northwestern. edu/news articles/2012/09/more-accurate-hurricane-forecastingusing-big data. html. OECD (Organisation for Economic Co-operation and Development.
2013. Exploring Data-Driven Innovation as a New Source of Growth: Mapping the Policy Issues Raised by‘Big data'.
'OECD Digital economy Papers 222, June 18. Available at http://dx. doi. org/10.1787/5k47zw3fcp43-en. The Old Farmer's Almanac.
Big data Thwarts Fraud. O'reilly Strata, February 8. Available at http://strata. oreilly. com/2011/02/big data-fraudprotection-payment. html. Talbot, D. 2013.
Big data from Cheap Phones. MIT Technology Review, April 23. Available at http://www. technologyreview. com/featuredstory/513721/big data-from-cheap-phones/.
/Tapscott, D. and A. Williams. 2007. Wikinomics: How Mass Collaboration Changes Everything. New york: Portfolio Trade books.
United nations. 2012. Big data for Development: Challenges & Opportunities. Global Pulse, May. Available at http://www. unglobalpulse. org/sites/default/files/Bigdatafordevelopment-UNGLOBALPULSEJUNE2012. pdf. 1. 8:
From Big data to Big Social and Economic Opportunities 86 The Global Information technology Report 2014 2014 World Economic Forum CHAPTER 1. 9 Making Big data Something
More than The next Big Thing ANANT GUPTA HCL Technologies Big data is the business buzzword du jour.
But how can you turn this hot topic into a real source of business value?
But despite the sometimes exaggerated hype surrounding big data, the fundamental assertion is true: data and the decisions driven by those data now represent the next frontier of innovation and productivity.
Estimates of the potential benefits of leveraging big data are indeed staggering: productivity-led savings worth US$300 billion a year for the US healthcare industry and €250 billion for the European public sector, a 60 percent potential increase in retailers'operating
2 Some large companies have used indeed emerging technologies to extract significant value from big data. Visa recently announced that increasing from 40 to 200 the number of attributes it analyzes in each credit card transaction has saved 6 cents in every $100 worth of transactions. 3 Wal-mart uses a self-teaching semantic search tool that,
the promise of big data is nowhere close to being fulfilled. For one thing spending on it is polarized. While the telecommunications, travel, retail, life sciences,
and financial services industries are making significant strides in big data technologies, other industries, such as manufacturing and government,
The lack of major big data initiatives across industries can be seen in the numbers from service providers.
In 2012, the global top 20 big data players made less than 1 percent of their total revenues from big data.
The total market for big data hardware, software, and services in 2012 was US$11. 5 billion,
whereas the combined overall revenue of those 20 big data players was more than US$1. 2 trillion.
The disparity between a few success stories and the lack of action elsewhere has created a high level of anxiety within firms that have not yet begun to explore big data.
An organization should make The Global Information technology Report 2014 87 2014 World Economic Forum a big data investment
We offer here nine steps that companies can take to begin turning big data talk into action, buzz into business benefits.
WHY IS EXTRACTING VALUE FROM BIG DATA SO HARD? First, though, we examine some of the barriers to realizing big data's promise.
Volume, velocity, and variety Big data is said often to be characterized by 3 Vs: its tremendous volume, the velocity at which it needs to be processed,
and the variety of data types it encompasses. The first two characteristics are fairly obvious: technology has made it possible to capture increasingly large amounts of information
But mining the value of big data also is difficult because it requires simultaneously analyzing various types of information transactions, log data, mail documents, social media interactions, machine data, geospatial data, video and audio data,
much of the value in big data exists in unstructured information for example, the transcript of a chat session between a retail customer and a customer service representative.
as well as 1. 5 million analysts and managers to analyze big data and make decisions based on those findings. 6 Another report predicts that only one-third of 4. 4 million big data jobs created by 2015 will be filled. 7 Unlike traditional analytics,
mining big data requires an extremely diverse set of skills deep business insights, data visualization, statistics, machine learning, and computer programming.
Policy should work to mitigate this talent shortage through forwardlooking education and immigration policies. Flawed data governance Big data is not a substitute for much less a solution for flawed information management practices.
If anything, it requires much more rigorous data governance structures. Without those improvements, information technology (IT) systems that have not been upgraded to handle large volumes of data are likely to collapse under the sheer weight of the data being processed.
Surveys suggest that business leaders are excited often more about the potential of big data Box 1: A user's glossary of key big data terms As an organization plans its big data strategy,
the following terms are likely to be used with increasing frequency. Hadoop: A batch-oriented programming framework that supports the processing of large data sets in a distributed computing environment.
Making Big data Something More than The next Big Thing 88 The Global Information technology Report 2014 2014 World Economic Forum than their IT counterparts.
It is virtually impossible for big data investments to deliver value if business leaders do not have driven a data mind-set that is,
Lack of technical know-how Big data represents a convergence of IT and data science. Technologies include Hadoop
Big data professionals are expected to be familiar with both disciplines, but this combination is rare, despite the training courses that are sprouting up globally.
For descriptions of some of the technologies that enable the analysis of big data, see Box1.)
NINE STEPS TO BIG DATA VALUE CREATION The barriers to extracting business value from big data can seem daunting.
and the Chief Procurement Officer should be responsible for identifying areas within their respective functions where big data could drive value.
especially if the team IT and analytics or a dedicated big data center of excellence reside outside of the business function.
In order to drive the big data program the team may want to appoint a big data program sponsor for each function
and work closely with him or her to discover and locate the types of information that would improve business outcomes.
and identify big data opportunities within the function. Step 2: Get the business functions to ask the right questions.
if they demonstrate how big data might be valuable to them. Simple questions such as What would you really like to know about your business,
The ability to ask the right questions is key to succeeding with big data. It also pays to keep in mind that big data is not about data themselves;
it is about using data to discover insights that can lead to valuable outcomes. Step 3:
Making Big data Something More than The next Big Thing 2014 World Economic Forum Step 4: Select the business functions best positioned to lead the way.
It is smart to launch big data initiatives in business functions that are most ready to collect
Match big data initiatives with compatible business functions. Some big data programs can be implemented in a variety of settings,
but most are suited to specific functions. For example: Customer functions (such as marketing, e-commerce, and customer service) can use big data for targeted advertising that provides personalized offers to consumers based on their socio-demographic characteristics,
and for loyalty management that extends channel reach from point of sale, web, and call center to include mobile and social capabilities.
and treasury) can use big data for intraday liquidity management, providing real-time monitoring of price movements in relation to positions,
and for improved credit risk assessment, through multiple big data supported credit risk assessments that factor in hundreds or even thousands of indicators.
Supply chain and procurement can use big data for dynamic route optimization because big data technologies that are faster than conventional systems allow more iterations and faster route planning in real-time.
Step 6: Determine whether big data will yield valuable information unavailable through traditional business analytics. Making the business case for a big data initiative clearly will be easier
if it can be shown that it creates new value. For instance, if a marketing department is currently segmenting customer profiles using standard demographic indicators,
would there be additional benefit in analyzing attitudes and preferences (at a granular level) through text and speech analysis?
In comparing views of data from a traditional business intelligence perspective versus a big data one, consider the following the questions:
Potential payback of big data initiatives Source: Gartner, 2013. Data systems most fit for purpose Easy pickings Overeager Invest here Not ready but who cares?
Making Big data Something More than The next Big Thing 90 The Global Information technology Report 2014 2014 World Economic Forum gained?
an organization should begin its big data experimentation with an initiative that is not too demanding. In assessing possibilities,
what is meant by big data is unstructured information data that traditionally have been impossible to break down and categorize as they are collected.
organizations need to consider a variety of methods to upgrade their infrastructure in support of or in anticipation of big data.
the idea that big data involves negligible cost because it is analyzed using open-source tools and platforms is a myth.
If the outcome of big data analysis is mission-critical for your business, it probably makes sense to use only purpose-built hardware.
Creating or upgrading to big data ready technology architecture is no small feat. Building everything from scratch takes time,
Big data initiatives require multidisciplinary teams of business and technology experts. Every team member business analyst, programmer, data scientist,
That said, the structure of most organizations would make it difficult for someone owning the big data portfolio to succeed.
Without clear line responsibilities, a CDO (whichever flavor, Data or Digital) or a CAO would have little leverage to execute the important tasks needed to increase the organization's big data capabilities
big data and business analytics expertise should fall within existing functions for example, finance, human resources, and marketing with the aim of furthering the strategic initiatives of those functions.
The efforts of the big data teams in these areas could be overseen and coordinated by a big data manager, reporting to the Chief Information Officer,
who would The Global Information technology Report 2014 91 1. 9: Making Big data Something More than The next Big Thing 2014 World Economic Forum ensure that best practices were adopted
and that initiatives were coordinated. Following the nine steps described above will help the IT function to assume such responsibilities.
CASE STUDIES Many global organizations have begun already embarking on deriving value out of big data initiatives. Almost all of them have defined step-by-step frameworks somewhat similar to the one outlined above.
RECOMMENDATIONS FOR GOVERNMENT ACTIONS AND POLICIES In order to take full advantage of the potential of big data in both the public and private sectors,
Organizations already using big data initiatives A few organizations that have followed frameworks for using big data include: A US-based mid-to upscale chain of department stores is gaining new insights from analyzing
An Indianapolis-based global pharmaceutical company is using big data to develop an integrated approach to optimizing how clinical trials are conducted
Australia-based telecommunications companies use big data to determine which of their customers are less likely to pay their bills,
A global corporation offering computer-assisted legal research services uses a big data technology platform it has developed in house both for its risk management business
It now also sells this big data platform through its newly established subsidiary. A US-based multinational consumer goods company has developed a decision-support environment used by more than 60,000 employees worldwide to see what is happening in the business
A California-based multinational energy corporation is using big data to transform the audit function. It runs audit tests on all of its accounts payable transactions instead of only on the small sample it used to analyze before.
Making Big data Something More than The next Big Thing 92 The Global Information technology Report 2014 2014 World Economic Forum Moreover, it is essential to develop
and execute a big data plan for all government services and activities. The plan should identify all government data worth analyzing,
and determine where big data technologies and analysis capabilities should be deployed first. Finally, each government should establish a big data center of excellence (BDCOE.
The BDCOE should be the focal point of expertise, long-range thinking and policy formulation, and training and development.
many organizations are struggling to know where to start in becoming competent in the realm of big data.
What's the Big Deal with Big data for Customer service? Webinar with Gareth Herschel, Research director, Gartner and Michael Maoz, VP Distinguished Analyst, Gartner.
Strategic intelligence Wing Research on Big data (the research arm of HCL Technologies..2013b. CIO Straight Talk Issue 3. Quincy, Mass, US and Noida, India:
Big data Strategy Components: IT Essentials. October 15, ID G00238944. Chicago: Gartner. Manyika, J.,M. Chui, B. Brown, J. Bughin, R, Dobbs, C. Roxburgh,
Big data: The next Frontier for Innovation, Competition, and Productivity. Mckinsey Global Institute Report. May. Available at http://www. mckinsey. com/insights/business technology/big data the next frontier for innovation.
Making Big data Something More than The next Big Thing 2014 World Economic Forum 2014 World Economic Forum Part 2 Country/Economy Profiles 2014
and policy in areas including cybersecurity, big data, the Internet of things, and the economic impact of digital technologies.
He leads the Big data/CRM Center of Excellence for Europe and the Middle east within Booz & Company.
and how to embrace opportunities from big data/advanced analytics. Bruno Lanvin Bruno Lanvin is the Executive director of INSEAD's European Competitiveness Initiative (IECI) and of Global Indices projects at INSEAD (Global Information technology, Global Innovation Index,
such as big data and the Internet of things, on existing social, economic, and policy frameworks. Prior to joining Microsoft, Dr Nguyen held positions with Research in motion, Avaya Communications, Lucent Technologies, and Bell laboratories.
Sandy Pentland Alex Sandy Pentlanddirects MIT's Human Dynamics Laboratory and the MIT Media Lab Entrepreneurship Program, co-leads the World Economic Forum's Big data and Personal data initiatives,
Mr Taylor leads TIBCO's industry and customer marketing, where he has the opportunity to dive into the solutions being created using TIBCO software to solve some of the most complex and rewarding global big data integration challenges.
Dr Tohme leads the big data efforts for Booz & Company in the middle East. 2014 World Economic Forum 2014 World Economic Forum The Global Information technology Report 2014 335 The World Economic Forum's Global Competitiveness
This year the Report focuses on the role that big data may play in this process and the conditions that leading organizations will need to adopt
dives deeper into the rewards and risks that derive from the advent of big data. In addition, the Report includes detailed profiles for the 148 economies covered this year together with data tables for each of the 54 indicators used in the computation of the NRI.
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