Mona Vernon - Using big data to crack B2B markets
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Mona Vernon - Using big data to crack B2B markets

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Startupfest 2014 - "Techcrunch's Alex Williams once said, ""While the enterprise can be as boring as hell, the whole goddamn thing is paved with gold."" But how should an aspiring young startup crack ...

Startupfest 2014 - "Techcrunch's Alex Williams once said, ""While the enterprise can be as boring as hell, the whole goddamn thing is paved with gold."" But how should an aspiring young startup crack open business-to-business markets that are insular, uncomfortable with experimentation, and intolerant of the kind of rapid iteration that fuels innovation?

As it turns out, there are plenty of ways for start ups to innovate in the business to business space, and many of them come from the world of Big Data. In this session, Thomson Reuters' Mona Vernon will look at how organizations of all sizes can leverage abundant data to transform markets. You'll learn:

- how big companies innovate
- why working with large corporations is different than selling directly to the consumers
- The advantages of working with large companies to solve their Big Data challenges

If you're a B2B-focused startup, you can't afford to miss this session."

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  • We are an information company. We provide intelligent information to professionals in a number of industries <br /> <br /> Historically we’ve been a portfolio company made up of a number of business units <br /> <br /> Each business focuses on a specific industry with specific products tailored to that industry <br /> <br /> Very acquisitive: many distinct products with sometimes overlapping audiences <br /> <br /> To point out all the acquisitions that we’re made, and how this perfectly mimics the big data challenge that most large organizations will face <br /> <br />

Mona Vernon - Using big data to crack B2B markets Mona Vernon - Using big data to crack B2B markets Presentation Transcript

  • THE B2B OPPORTUNITY WITH BIG DATA – MONA VERNON
  • About Thomson Reuters Comprehensive IP & scientific information, decision support tools & services to enable governments, academia, publishers, corporations & law firms. Tax & Accounting Financial & Risk Integrated tax compliance and accounting information, software & services for professionals in accounting firms, corporations, law firms and government. Intellectual Property & Science Legal Critical information, decision support tools, software & services to legal, investigation, business and government professionals. Critical news, information & analytics, enables transactions, and connects trading, investing, financial and corporate professionals. Key products include: Eikon, Thomson One, Reuters 3000 Xtra, Datastream, FXall Key products include: WestlawNext, FindLaw, Firm Central, Concourse, CLEAR Key products include: OneSource, Checkpoint, CS Professional Suite, Government Revenue Management Key products include: Web of Knowledge, Cortellis, ScholarOne, Thomson IP Manager, Mark Monitor Reuters News Powered by more than 2,800 journalists reporting in 20 languages from bureaus around the world, Reuters is the world’s largest international news organization
  • About The Data Innovation Lab • Partner with customers, third parties, and internal teams on new data-driven innovations such as revealing new relationships and data mining for new patterns, and deliver data visualization prototypes • Data sources: internal big data store, open data and social data • Experiment with mash-ups of internal and external data in novel ways • Small team of amazing intrapreneur - data scientists 3
  • WHAT IS THE ENTERPRISE OPPORTUNITY WITH BIG DATA ?
  • The Enterprise Big Data Pain Point Most large enterprises are generating a significantly wider variety of data every day and this variety challenge (more than volume or velocity – if your counting Big Data “V”s) is becoming the biggest bottleneck for enterprise analytics. Mark Schreiber, Novartis 5
  • 3 2 1 High quality diverse data is the fuel for analytics • Quant Research: Predictive and Performance Models – Quant and analytical models mimicking human judgment – Sentiment engines aggregating opinions • Data Science: Predictive and Actionable Algorithms – Predictive Machine Learning – Persistent Point-in-Time Historical Analytics – Point-in-Time Entity Mapping and Alignment • Text Analytics: Descriptive Algorithms – Tagging meta-data and parsing – Search algorithms 6 One spectrum of analytics arranged from most human- based to most machine-based “even the most sophisticated front end tools will merely be window dressing on a spoiled carcass of bad and disconnected data “– Andy Palmer, Tamr Inc.
  • Benefits of Big Data – View from one sector
  • Planned Future Investment in Big Data
  • HOW TO BREAK IN THE ENTERPRISE MARKET WITH BIG DATA?
  • Coporation innovation is changing Enterprise data management is changing: Traditional approach meets the bottom-up approach: Treat everything as unstructured, keep the top-down approach as a starting point, and then let the algorithms mine for value. • New tools, new attitudes: Leverage Open standards and Open Source • Rapid iteration – lean experiment as a way to manage uncertainty and keep up with the pace of change • Partner with innovators like start-ups and academics to keep up with technology change
  • Good news: Software Is Eating The World
  • Yes, Software Is Eating The World
  • Yes, Software Is Eating The World YOU ARE NOT GOING TO BE ALONE !
  • Find a champion, over deliver, repeat • Who is passionate vs. who can make it happen • Who will sign the first check • Who will define success metrics • Who will iterate with you on the lean evaluation • Who will champion you to become a vendor • Who are you competing against: Legacy, R&D, Big players, other start-ups? • When do you break-up and try again elsewhere
  • DATA INNOVATION LAB THOMSON REUTERS INNOVATION DISTRICT BOSTON USA @monavernon