Unlocking the Value of Big Data (Innovation Summit 2014)
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Unlocking the Value of Big Data (Innovation Summit 2014)

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Big Data is central to the strategic thinking of today’s innovators and business executives as companies are scrambling to figure out the secret to transforming Big Data to Big Insight and that......

Big Data is central to the strategic thinking of today’s innovators and business executives as companies are scrambling to figure out the secret to transforming Big Data to Big Insight and that Insight into Action. As many companies struggle with the emerging technologies and nascent capabilities to discover and curate massive quantities of highly dynamic data, new problems are emerging in the form of how to ask meaningful questions that leverage the “V’s” of large amounts of data (e.g. volume, variety, velocity, veracity). In the Business-to-Business space, these challenges are creating both significant opportunity and ominous new types of risk. This presentation discusses how companies are reacting to these changes and provide valuable insight into new ways of thinking in a world with overwhelming quantities of data.

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  • 1. Big Data Innovation Summit: Unlocking the Value of Big Data Anthony J. Scriffignano, Ph.D SVP Worldwide Data & Insight Dun & Bradstreet April 9, 2014 ダンアンドブラッドストリート Headquarters location: 40° 44' 30.0192'' N 74° 21' 35.8128'' W 斯格非亚诺 博士 (安东尼) 2014年4月9日
  • 2. 2 Clearly, Big Data is central to the strategic thinking of today’s innovators and business executives. Companies are scrambling to figure out the secret to transforming Big Data to Big Insight and that Insight into Action. As many companies struggle with the emerging technologies and nascent capabilities to discover and curate massive quantities of highly dynamic data, new problems are emerging in the form of how to ask meaningful questions that leverage the “V’s” of large amounts of data (e.g. volume, variety, velocity, veracity). In the Business-to-Business space, these challenges are creating both significant opportunity and ominous new types of risk. In this session, D&B’s SVP of Worldwide Data & Insight, Dr. Anthony Scriffignano, will discuss how companies are reacting to these changes and provide valuable insight into new ways of thinking in a world with overwhelming quantities of data. Session abstract…
  • 3. The imperative for transforming Big Data into Big Insight is central to B2B evolution, allowing us to turn insights into action 3
  • 4. Our customers continue to ask more difficult questions and expect innovation to outpace their need 4
  • 5. 5 1960 1970 1980 1990 2000 2010 Private fixed investment – IT equipment & software has become an increasingly important component Our response as an industry has been predictable, but incomplete
  • 6. Pope Benedict Inauguration Sometimes, a picture is worth a thousand words. Pope Francis Inauguration • What about the digital footprint of all of the smartphones? • What about the social networks the crowd? • What about the metadata in the photos? • What are the opportunity costs to other activities? • The largest corpus of data preceded the event • Most data created about the event had significant, and asymmetric latency • The rate of “data decay” attributable to the participants in the event is significant Lately, a thousand pictures are taken in the time it takes to speak a single word! The nature of Big Data itself is changing through human and digital “learning”
  • 7. 7 The fundamental problem of identifying and understanding a business is something we do well. That problem is made much more complex when the “crowd” is doubling and doubling in size. “There will be a shortage of talent necessary for organizations to take advantage of big data. By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know- how to use the analysis of big data to make effective decisions.” McKinsey & Global Institute Report “ Big data: The next frontier for innovation, competition, and productivity” June, 2011 Business problems such as credit decisioning are much more complex as the “crowd” is changing
  • 8. 30 years ago we were in search of basic tools 8 • Lack of transactional data resulted in surveys, surveys and more surveys • Human and Digital latency was an accepted part of the analytic landscape • Storage and computing power were severe limitations (remember the days of megabytes or sharing a PC with other team members?) • Analytic methods – descriptive at best • … fragmented views of the truth that lacked foresight in most cases
  • 9. 30 years later these issues have been addressed, giving rise to others • Transactional data overwhelming problem formulation, increased reliance on tools vs. methods • Storage and processing power – our head is now in the clouds • Analytic capabilities that can allow us to filter, determine casualty and be both prescriptive and proscriptive • New capabilities to understand the character and quality of data in ways that were never before possible • …. However we are still struggling to get to a complete view, determine causality and to transform our understanding into foresight and action 9
  • 10. • We all know that the world is changing • We are aware that the rate of change is increasing at an unprecedented rate • We see new types of data, technologies, and behaviors every day The Operating Environment • What has made us successful so far is insufficient • We now have the ability to succeed… or fail, much faster • The connectedness of information and the ways in which it is changing is impacting the risk and opportunity space in ways we are only beginning to understand The Case for Change The case for change is a compelling one
  • 11. We must learn to ask questions in new ways 11
  • 12. Data Data Data DATA!It’s not just about DATA! 12
  • 13. 13 Math Math Math MATH!It’s not just about MATH! It’s about making better business decisions Where to invest? How do to optimize sales & marketing investments? How to target better? How to minimize my risk? How to manage world class supply chain? 13
  • 14. 14 Relationships matter
  • 15. Put simply, there are three levels of insight required along a journey to informed perspective I See You Global Data Completeness I Know You Multi-Lingual Identity Resolution I Can Predict Your Behavior Predictive Analytics Transparent Relationships Insight for Decisions “I need integration of assets and transactional data.” “I need foundational business insight.” “I need predictive insights on-demand.” 15
  • 16. Leveraging new data sources provides a complete transparency of a business relationship which enables actionable insight Complete Transparency in Business Relationship Propritary Business Activity Signals 3rd Party Business Activity Signals Logistic – Shipping & Delivery Spend & Purchasing Transaction Data Real Estate Transactions & Ownership Social Media 16 Innovating and expanding data collection will result in:  Linking together relationships between trading partners to see a complete supply chain  Identifying the “heartbeat” of a business, predicting its future health, and rapidly seeing changes  Deeper insight based on signal patterns to anticipate the future behavior of a business  Understanding the true size of a business in multiple dimensions, including social influence beyond its balance sheet
  • 17. Traditional Size Attributes Number of Employees Sales Revenue New Data Sources Proprietary Data Signals Untraditional Size ‘Proxies’ Data innovations are radically enhancing our predictive analytic power, such as new models for assessing size dimensions Multi-dimensional Size Assessment • Comprehensive • Multi-faceted • Contextual • Representative 17
  • 18. 0 1 2 3 4 5 6 7 8 9 10Marketing Composite Score Total Loss Viability Physical Delinquency Influential Financial MCS Illustration SIZE RISK 3 SIZE Measurements trending over time + 3 RISK Measurements = 1 POWERFUL Score New strategies exist for risk-reward tradeoffs such as multi-dimensional marketing attributions 18
  • 19. Commercial signals and proxy are now added to existing predictive attributes to provide deeper insights and even more predictive analytics. Signal & proxy sources add significant decisioning content on small businesses with limited or no traditional predictive data footprint
  • 20. Leveraging signals gives rise to the ability to predict the likelihood a material change in a company’s profile will occur in the next year 20 Advanced Analytics Activity Signals Behavioral Trends Event Frequencies Changes in Traditional Data Sources Anticipatory Analytics Risk Profile Change Opportunity Profile Change
  • 21. Advanced analytics can identify businesses that are poised for growth, and anticipate customers’ progression across the business lifecycle Businesses can be thought to have stages of ‘size’, like caterpillars growing into butterflies Starting up Going Public Growing Physically and Financially Going Global Foresight into future needs enables you to take the best action at the best time Egg Caterpillar Molting Larva Pupa Emerging Adult Adult Engage Here High probability of growth in near future Act Now Indication a major business transition lies ahead 21
  • 22. Virtuous Cycle Teach & Learn Inform Focus on Creating an Informed Perspective for Customers The winning hand is to incorporate science into workflows in a systematic way…. Develop foundational knowledge Integrate assets including Transactional Data Establish complete and intimate knowledge of customers and prospects Transform insights into action 22
  • 23. With vast amounts of data come great opportunity… and new types of risk 23
  • 24. As we continue this work, we are also mindful about how the nature of data is changing… It is easier than ever to start a new business – geographic location, existing infrastructure, and physical customer interaction are becoming irrelevant. …However, ALL OF THESE ATTRIBUTES HELP RESOLVE BUSINESS IDENTITY. As the ability to provide “helpful” information proliferates, the truth can get lost. As information is increasingly unstructured or imbedded in applications and private spaces, the lines between what is public and what is discernable are blurred. 24 Source: USA Today
  • 25. The Internet • Just because it’s on the Internet doesn’t make it true… • Significant effort exists to manipulate what we “find,” that capability can be exploited or simply used with negligence • Everything isn’t on the internet! Veracity • Repetition doesn’t necessarily mean truth • Repetition doesn’t necessarily mean truth • Bad news travels fast • Bad guys are often “smarter” than good guys • Truth can only be measured against a source of the “truth” Latency • Everything is not simultaneously true • Newer information isn’t always more true Relationship •Correlation is not causation 25 In the above use-case, with millions of payment experiences a week, we were able to quickly identify and analyze a suspicious pattern and take action Not only on all related cases but also the “three ring leaders” Some thoughts on veracity…
  • 26. 26 Some thoughts on volume… • There are multiple considerations for Volume • Moving from data in hand to discoverable data • Discovery leads to curation and synthesis • Multiple technologies are available from cloud to in-house, but must consider existing footprint • Consider the skillset of resources available • Volume is dynamic • Monotonicity • Persistence • Ubiquity • Security and access • Volume must also be considered as an opportunity cost • More data requires different approaches to processing • Big “O” considerations for prospecting and analytics
  • 27. 27 Some thoughts on variety… • There are multiple considerations for Variety • The myth of “unstructured” data • Disambiguation and entity extraction • Neural networks and other methods for inferring ontology and relationship • Deep learning, heuristics and automata • Variety is constantly evolving • New data types are being created out of necessity • The “hidden” web and other sources of data • The impact of language and orthography • Evolution of encryption and transformations • Variety leads to unique challenges for processing • Measuring and sampling • Bias introduced by different types of data • Unknown “met” needs
  • 28. Macro Regional Local Micro Global Association Entity People in Context Connected Supply/Value Chains Mal- feasance Disaster Remediation Material Changes Challenging the Status Quo: There are many frames to consider when delivering an answer
  • 29. “And now we welcome the new year, full of things that have never been” – Rainer Maria Rilke We must embrace information that is rich, varied, and full of opportunity and shift our focus from “hunting and gathering” to new opportunities beyond just “Big Data”
  • 30. The informed. future belongs to Follow the conversation at: @dnbUS @Scriffignano1 Visit us at: www.dnb.com 30