IDEAS ECONOMY: FINDING VALUE IN BIG DATA A Summary of an Economist discussion on Big Data sponsored by Oracle
Big data is the electricity of the 21st century a new kind of power that changes everything it touches in business, government and private life. It s a phenomenon which Kenneth Cukier, data editor for The Economist, and his co-author, Viktor Mayer- Schönberger, call datafication in their excellent book, Big Data: A Revolution That Will Transform How We Live, Work And Think. Datafication is not just about capturing more data from daily activities. It is also about using more data in those daily activities to do and decide things better. In these pages you ll find stories of big data in everything from New York City s inspectional services to Intel s silicon manufacturing, from public policy implications to visual design innovations, and more. Despite their diversity, these stories share a common theme of making data useful. But the datafication of everything puts this familiar goal in a new, strange light. Making big data useful is not simply about organizing it to make it solve specific problems. It s also about taking the data as is to learn what it can do. The challenge of learning from data before it s fully organized is entirely different from the challenge of organizing data once you know what you want to do with it. For large organizations that have already invested in putting important data into neat rows and columns, this issue is even more pressing. These companies need technologies to cut the cost of forming and testing hypotheses on the new torrent of data coming at them, as well as technologies to cut the cost of standardizing and controlling processes that apply it. These two kinds of technology are more powerful together than either alone. Combining them is what we call Big Data At Work. Big data at work will speed up discoveries, like new ideas about the interactions between cancer types, therapies and patient genetics. It will make small predictions ever-present in daily activities like recommendations of parts to product designers, trouble spots to regulators, and diagnoses to doctors. It will create reservoirs of data for future use where, as Cukier and Mayer-Schönberger point out, the data s secondary value may be much bigger than that created when it was first collected. It will accelerate data-driven action to prevent fraud, improve cellular networks, and head off equipment failure in real time. And yet, this is only the beginning. Like the first incandescent light bulbs hung in a few Manhattan homes, today s big data bright spots only hint at the transformation to come. We look forward to building that new world with you. IDEAS ECONOMY: INFORMATION FORUM 2013 FINDING VALUE IN BIG DATA June 4th, 2013 Yerba Buena Center for the Arts, San Francisco Big data is not just a marketing slogan, explained Kenneth Cukier, author of Big Data: A Revolution That Will Transform How We Live, Work and Think, and data editor at The Economist. On these pages, you ll read about: 1. 2. 3. An exploration of companies and their use of big data to remake themselves and their industries A look at global economies with Google s Eric Schmidt and asking the question: What does a data rich universe mean? An analysis of data-based decision processes and telling stories through data visualization 4. Predictions for big data s future and what it means for society Paul Sonderegger Oracle Big Data Strategist @paulsonderegger #BigDataAtWork Companies are changing the way they operate, and even economies are shifting, because of the way information is used. Big data is a tool. It s about the wisdom of individuals to use [this tool] properly, said Cukier. 3
The next chapter: Big data and The future of The global economy The big data revolution will define the next era of business and government. Brad Peterson, chief information officer of NASDAQ OMX, Michael Flowers, analytics director for the Mayor s Office of Policy and Strategic Planning, NYC, and Bill Johnson, chief executive of Citi Retail Services, discuss how they are harnessing the power of data to change the realms of finance, banking and government to be smarter, more responsive and more ef ficient. KenneTh cukier AND Brad peterson, ChIEF INFORMATION OFFICER, NASDAQ OMX GOVERNMENT: Thanks to big data, local government can better deliver the essential services that it is supposed to including debris removal, public safety, street maintenance and education much more effectively. That delta has occurred really only in the last couple of years, said Flowers, and we have big data, essentially, to thank for that. For example, New York City has a limited number of building inspectors, and they use big data analysis to decide where to investigate, because city workers can correlate a tax lien on a building with a nine-fold likelihood for a catastrophic fire. In this way, data has become a tool for prioritization that makes government work bet ter. BANkING: Banks are on Brad peterson, ChIEF INFORMATION OFFICER, NASDAQ OMX, Bill Johnson, ChIEF EXECUTIVE, CITI RETAIL SERVICES, michael flowers, ANALYTICS DIRECTOR, MAYOR S OFFICE OF POLICY AND STRATEGIC PLANNING, NYC the receiving end of lots of unstructured data that before michael flowers, ANALYTICS DIRECTOR, MAYOR S OFFICE OF POLICY AND STRATEGIC PLANNING, NYC never had any real value. For example, the millions of customer service calls have millions of useful data points. Today, those calls are critical in helping banks implement new policies that can reduce the amount of customer complaints. As Johnson explains, all that unstructured call data can now be put through some computer queries to mathematically reveal the reasons for the call. The bank can take action, and completely eliminate calls for that reason in the future. Now efficiency and effectiveness become one in the same, said Johnson. At Citi, that opportunity has become an imperative, and investment in the right technology is necessary. Today, I need to act on data. I need to act on fact, he said. MARkETS: With the help of hard facts, market participants, market places and market regulators now have indisputable information to back their claims for the best set of rules. Business and regulators will have a fresh viewpoint on what s happening and not just use long held beliefs on what is good, said Peterson. 5
innovation rewired: corporate strategies 2.0 gerri martin-flickinger, ChIEF INFORMATION OFFICER, ADOBE HOW IS BIG DATA HELPING COMPANIES INNOVATE? One of the biggest ways big data technology is driving innovation is by shrinking the time it takes to answer key business questions, according to Paul Barth, managing par tner, NewVantage Partners. For example, a large bank s customer action analysis can now move from a six week process to just days, or a retailer can reduce monthly repor t calculation time from two days to 20 minutes per report, or a credit card company can change their accurate fraud detection process from an hourly micro-batch analysis into streaming analysis to predict patterns within seconds. Changing the compute scale of data speed has led to quantitative and qualitative changes in behavior, said Barth. That s because discovery and operations can now happen almost concurrently, so that product iteration can happen quicker in the market place. Joe spagnoletti, ChIEF INFORMATION OFFICER, CAMPBELL SOUP COMPANY HOW DOES BIG DATA AFFECT DECISION MAKING FROM THE BOTTOM-UP AND THE TOP-DOWN? An in-depth conversation with Gerri Martin-Flickinger, chief information of ficer, Adobe, Kim Stevenson, chief information officer, Intel, and Joe Spagnoletti, chief information of ficer, Campbell Soup Company. At Adobe, real-time data capabilities allowed the company to completely shift its business models. It can now offer consumers cloud-based products that give them immediate access to their software, and speedier service, while at the same time benefitting the company with realtime consumer data measurement. The company can now more accurately respond to user needs with regular updates, based on the data feeds it receives. Data mining has also helped Campbell focus on the customer. Data insights enabled the company to create new product offerings more quickly and based on buyer demand. Meanwhile, Intel has been driven into totally new areas, including mobile and tablets, by machine learning techniques that have reduced their product testing cycles by 25%. Growing corporate flexibility to respond to the insights that big data delivers is putting increasing pressure on information and technology offices. At Adobe, Intel and Campbell, information technology departments are overwhelmed with management requests for analyses to help make the big strategic decisions. 7
disrupting The global economy: how information changes The way we live and work WHAT WILL BE THE IMPACT OF DATA ON THE FUTURE GLOBAL ECONOMY? eric schmidt, EXECUTIVE ChAIRMAN, GOOGLE Eric Schmidt, executive chairman, Google and co-author of The New Digital Age: Reshaping the Future of People, Nations and Business, and James Manyika, director, Mckinsey Global Institute answer. healthcare. From genomics (the meeting of data applications and biology) to a newly FDAapproved device that can see the inside of a patient s stomach, more medical improvements are on the way. But, if nothing is done to contain costs, Schmidt estimates that healthcare expenses will exceed the entire revenue of the United States in the next 30 years. TEChNOLOGY. Digital devices are all talking to each other, but technology on the back end hasn t caught up yet to make those conversations fully useful. This gap will be filled by new companies, which will be more accurate at identifying what users actually do in life versus just online. PRIVACY. Eric Schmidt said that smaller companies push the boundaries of what is appropriate on the use of individuals data, while larger companies are held to a higher standard and must maintain stronger policies for their users. He suggests more anonymized data policies, but believes individuals do have to fight for privacy. For instance, governments will violate individual privacy when there is an apparent threat. Still, policies should be open enough so digital footprints could be analyzed to find evil people. history. Once information hits the internet, it s there forever. This has both legal and social ramifications, especially data that others collect without our permission. Schmidt predicts that eventually there will be laws addressing picture-taking or using technology, such as Google glasses, in public spaces for this reason. James manyika, DIRECTOR, MCkINSEY GLOBAL INSTITUTE 9
KenneTh cukier, Tariq shaukat, ChIEF MARkETING OFFICER, CAESARS ENTERTAINMENT, sharmila mulligan, CO-FOUNDER AND ChIEF EXECUTIVE, CLEARSTORY DATA, george John, CO-FOUNDER AND ChIEF EXECUTIVE, ROCkET FUEL data emerges from The BacKroom: how To profit from finding new connections Machine learning is being used to sell more effectively because it can identify correlations that are not immediately apparent. George John, co-founder and chief executive of Rocket Fuel, uses it to track users for more accurate advertising sales and placements, incorporating new tools including word cloud analysis. Sharmila Mulligan, co-founder and chief executive, ClearStory Data, added that data is so critical now that it must expand into an open marketplace, so more companies can get access to good, clean data of a much higher value. The best way to sell through data is to focus on the value it adds for the consumer. Tariq Shaukat, chief marketing officer, Caesars Entertainment, said the company s data practices have greatly evolved from selling-centric to consumercentric. A group of 200 analysts at Caesars monitors the flow of information to predict what triggers sales events and how to best design a casino for the consumer. The analysts found that patrons who have bad luck at casinos might still be loyal, if they ve been given other consumer perks, such as tickets to shows. ThE human FACTOR. Staffs of human analysts are needed to look at data sets to combat the limitations of computeronly generated analyses, said Mulligan, Shaukat and John. Human checks and balances can still steer decisions in the right directions more effectively. riva richmond, ECONOMIST INTELLIGENCE UNIT EDITOR in search of insight and foresight How do successful companies use data? Riva Richmond, editor, Economist Intelligence Unit, presented an Oracle-sponsored global survey of 373 senior executives. 1. Set clear and specific business objectives 2. Test various hypotheses and ask better, new questions of data 3. Use data insights to set a plan WhY DOES IT MATTER? Successful companies, defined as those that outperform their peers in profitability, have leaders who support the use of data and also have open, collaborative cultures. When it comes to decisionmaking, strong performers lean more on data and fact, instead of gut instinct. ThE TAkEAWAY: A top down vision on how to use data is key Investment in data capabilities is critical Culture matters: if a company isn t open, the data results can t be implemented Hire and cultivate employees who understand both data and business Ensure that data efforts and business strategy are aligned Report can be downloaded at http://www.economistinsights.com/analysis/search-insight-and-foresight 11
right Brain: a BrighT future for data visualization The end of experts: Big data and The science of decision-making HOW DO WE MAKE BIG DATA DIGESTIBLE FOR HUMANS? A conversation with Peter Arvai, chief executive, Prezi, Andrew Crow, experience design director, GE, and Pete Flint, chief executive, Trulia. COMPUTERS CAN T TELL STORIES. Computers are now good enough to compute data, but they don t know how to tell stories about that data and that s the difference in effectively communicating with the end consumer. Data should be organized in a manner that engages the way human brains peter arvai, ChIEF EXECUTIVE, PREzI actually work; then we can process a larger amount of data. ThE FUTURE OF INSIGhTS IS VISUALIzATION DRIVEN. For example, Trulia, a real estate website, can use a single visualization to display multiple data sets, including crime maps, neighborhood prices and school districts. Thinking about data visually also helps GE reach its goals because it makes data comprehension easier, clearing the way for andrew crow, EXPERIENCE DESIGN DIRECTOR, GE innovation faster. That s why the role of designer and developer is merging. ADVICE FOR PRESENTING DATA. The secret in presentation is in the context. Design data in such a way that it enables individuals to see just the data they need in order to take action on that information quickly. After all, data is consumed by humans and should be tailored to how each individual thinks and learns. pete flint, ChIEF EXECUTIVE, TRULIA MAN VERSUS COMPUTER. Data requires both art and science, says Douglas Merrill, founder and chief executive, zestfinance. We need the science and the math done correctly to interpret the data, but we also need human intuition applied to those answers to avoid silly results. For example, a computer doesn t always know that someone cited in a credit report has died. Relationship Science, according to its chief executive, Neal Goldman, has drawn the douglas merrill, FOUNDER AND ChIEF EXECUTIVE, zestfinance same conclusions. The only way to ensure accurate data, he says, is for humans to physically evaluate the data. that too much human reliance makes the technology not scalable. MAN CAN T keep UP. Gurjeet Singh, co-founder and chief executive, Ayasdi adds that computers generate so much analysis, more than ever before, that people can t keep up with their job: framing the right questions for the computers to work on. Kenneth Cukier, data editor at The Economist, added neal goldman, FOUNDER AND ChIEF EXECUTIVE, RELATIONShIP SCIENCE gurjeet singh, CO-FOUNDER AND ChIEF EXECUTIVE, AYASDI 13
K.r. sanjiv, SENIOR VICE PRESIDENT OF ANALYTICS AND INFORMATION MANAGEMENT SERVICES, WIPRO, paul sonderegger, SENIOR DIRECTOR OF ANALYTICS, ORACLE data and discovery Finding unexpected value in the avalanche of available data with Paul Sonderegger, senior director of analytics at Oracle, K.R. Sanjiv, senior vice-president of analytics and information management services at Wipro, and Paul Bernard, vice-president of market development for INRIX. It s essential to have the ability to change the perspective on your business instantaneously, said Sonderegger, discussing examples of companies that have found success by being responsive. a big data technology that allowed information gleaned from customer service phone calls to turn into structured data automatically. The strategy provided data on details including the number of laptops in the caller s household and the ages of the household s consumers. This information was then passed on to a sales person. The total revenue out of leads generated from the call center was more than the cost of running the call center, said Sanjiv. But in order to succeed, a company has to have the processes in place to be able to respond to the findings discovered in the big data. For example, Sanjiv explained how one high-tech manufacturer that operated a call center in India harnessed the power of big data to At INRIX, the team applied this grow its business. It implemented strategy. The company collects data from public and private sources for traffic information. In the past, in order to report an incident, it had to wait for a formal announcement from the source. But, INRIX now can report an issue based on just a data anomaly. This change in process allows the end user to get information faster. This is harder to do for some industries. For example, when the auto industry thinks about launching a product, it is tested over and over again, and verified, whereas a company like Facebook experiments daily. We revisited core assumptions...and developed new insights in to how the data could be used, said Bernard. ralf dreischmeier, MANAGING DIRECTOR, BOSTON CONSULTING GROUP, cassidy shield, head OF GLOBAL SOLUTIONS MARkETING, ALCATEL-LUCENT, anthony goldbloom, ChIEF EXECUTIVE, kaggle The data inside Ralf Dreischmeier, managing director of the Boston Consulting Group, Anthony Goldbloom, chief executive of kaggle, and Cassidy Shield, head of global solutions marketing at Alcatel-Lucent address the age-old question of whether to grow a business organically or through acquisition. Panelists in this session agreed that it is important for organizations to build a basic internal network that works on big data, and understand how it can help a business. Big data is a business transformation. It requires a change in organizational structure, said Dreischmeier. You need to have some expertise in house to start with. Shield added that if a company doesn t, and only looks externally, it risks losing its identity. It s easy to lean on technology vendors to build the infrastructure, but what you re not going to find out there very often is people who know your business better than you, he said. Goldbloom suggests sprinkling data scientists across each unit of an organization, charging them with continuing to do what the company does, but better. And then, data science becomes part of the fabric, he said. Still, Dreischmeier warned, that as a business slowly develops these capabilities, it must look at the total ecosystem it works in and develop a longer-term model, which may require more external relationships. 15
mind The gap: resolving The skills gap in data analytics stories from The front lines: why TrusT is more important Than ever A conversation between Anindya Ghose, co-director of the Center for Business Analytics, NYU Stern School of Business, Annika Jimenez, global head of data science services, Pivotal, and Sam Hamilton, vice president of data management, PayPal. An interview with John Rose, senior par tner, The Boston Consulting Group TRY FINDING A DATA SCIENTIST Academic programs are only now catching up to the needs in data science. That s why many recruiters can t find exactly the skill set they need, but work with universities to identify a capability among students who might become data scientists. New York University recently launched a degree program in computer science and data analytics, and is one of the few schools that have identified this opportunity. Students study statistics, including econometrics and predicative analytics, the collection and harnessing of data, and data visualization. The students could be training for some of the most lucrative careers of their generation. Companies are also retraining their own annika Jimenez, GLOBAL head OF DATA SCIENCE SERVICES, PIVOTAL employees. For instance, PayPal has a step-up program that is an internal roadmap to develop data science skills for current employees. how DO YOU GAIN TRUST? Real trust is established when companies only use data in manners that consumers expect it to be used. Internal and TRUST IS A COMPETITIVE WEAPON. Those organizations external policies must be set. Policies should be in a language that effectively manage trust will perform fundamentally better than consumers understand. And, when a company has consumer those who don t. trust, consumers are much more likely to let those companies use that data in new ways when asked. martin giles, John rose, SENIOR PARTNER, ThE BOSTON CONSULTING GROUP 17
Beyond Big data: The next frontiers of Business and Technology A conversation between Daniel Kaufman, information innovation office director, DARPA, Erik Swan, co-founder and chief technology of ficer, Splunk, and Ankur Jain, founder and chief executive, humin. WHAT ARE SOME RADICAL BIG DATA PREDIC TIONS? DATA ANALYSIS WILL BE COMMON. Swan predicts that the biggest shift in big data will be the attitudes people have around it. Using lots of data will be normal for everyone, from farmers to electricians. Everyone is going to default to using data to analyze everything in the next 10 years. of thought to build memory prosthesis for soldiers, currently in testing on rats. CONTEXT WILL MATTER MORE. Because data will be all APPLICATION ShIFT. Per around us, context will become more important, said Jain. We will start routing data into real world objects and it will help us process it bet ter. BIOLOGY TURNS INTO DATA. Kaufman would like the definition of data to include biological information, so that the information can be interpreted to provide life advice. For example, should you eat one more pizza slice? DARPA is using this line Swan, big data insights will no longer focus on selling to individuals. Instead, they will address real problems and answer essential human needs. humans DO LESS. People will stop asking all the questions for data to answer. What if computers can just tell you what is interesting? asked Kaufman. Swan is cautious about this. I want smarter people by giving them a tool that lets them be smar ter, he said. conclusion In the end, the use of big data by companies to sell better, work faster, and expand into new markets is just the beginning. The widespread use of insights from big data analysis is a societal tipping point. What s around the corner? We start doing things more effectively. What s the upshot? Progress in how we work, how we make money, how we live, how we tackle problems, and how we think. Technologies pushing big data forward are ultimately pushing societ y for ward. daniel Kaufman, INFORMATION INNOVATION OFFICE DIRECTOR, DARPA, ankur Jain, FOUNDER AND ChIEF EXECUTIVE, humin, erik swan, CO-FOUNDER AND ChIEF TEChNOLOGY OFFICER, SPLUNk 19