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The CDO Agenda: Competing with Data - Strategy and Organization

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Data are exerting themselves, more and more, promising great opportunity--fundamental new discovery, better products and service, and more informed, confident decisions. A data revolution is …

Data are exerting themselves, more and more, promising great opportunity--fundamental new discovery, better products and service, and more informed, confident decisions. A data revolution is unfolding! But few are ready. They’ve not set their strategies for competing with data. Worse, most organizations are remarkably “unfit for data.” In this webinar we’ll summarize the opportunity and the risk, lay out strategic options, and propose steps leaders can take to get in front of the data curve.

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  • 1. Competing with Data: Strategy and Organization Thomas C. Redman, Ph.D. “the Data Doc,” Navesink Consulting Group www.navesinkconsultinggroup.com Dataversity Webinar, March 2014 /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T.C. Redman, Page 1
  • 2. Data at Grandma’s We find some real nuggets—that lead to fundamental innovations and create new industries. We use them to Improve product and service People, top-to-bottom, bring more data to the decision-making table Good things follow: • The economy grows • Health care is better and less costly. • We’re freer and safer. FOUNDATION: The data are high-quality— we know we can trust them. /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 2
  • 3. Junior Executive VS /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 3
  • 4. Family Practitioner VS /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 4
  • 5. Rising Middle Manager VS /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 5
  • 6. CEO Capital Request Our future… I better get involved! /Redman-Competing-March2014 VS More tech b#@S%! © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 6
  • 7. “Data come up in every single conversation” POINT Individually, nothing more than tough social and organizational issues. COUNTERPOINT Collectively, something deeper. The successful have always Data, especially big data, sought and taken advantage are exploding everywhere. of superior data. Impressive “big data” successes, from all over. /Redman-Competing-March2014 Viewed through the “data lens,” the financial crisis is a colossal failure of data. © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 7
  • 8. Opinion: A full-strength data revolution is brewing!      It is not “big data,” it is all data. Revolutions are chaotic, messy and inherently unpredictable. No one will remain untouched. There are no roadmaps. By the time they appear it will be too late. The technological challenges are tall. These pale in comparison to the organizational challenges. /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 8
  • 9. The Four Most Common Things I Hear     “We’re data rich and information poor.” (e.g., “We’ve not thought through how we’ll compete with data “I’ve been in this industry twenty-five years. Trust me. These data are as good as they can possibly be.” “Tom, you’ve got to keep in mind that we are much more siloed than the other companies (industries, etc) you work with.” “If its in the computer, it must be IT’s responsibility.” /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 9
  • 10. Today’s organizations are unfit for data      Don’t know how to compete with data, nor gained enough experience to do so in a sensible fashion. Lack talent, up and down the organization chart. Silos impede data sharing. Quality is essentially unmanaged. Responsibility for data buried in the bowels of IT. Step one: Move it out! WORKING THROUGH THESE ISSUES IS THE MANAGEMENT CHALLENGE OF OUR GENERATION /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 10
  • 11. Bottom Line The leadership challenge in a nutshell:  A full-strength data revolution is brewing  Today’s organizations are stunningly unfit for data So… what to do?  Sort out how to compete with data  Build organizational capability:  Get responsibility for data out of IT  Quality is pre-requisite (and we know what to do!)  Think end-to-end.  Develop and exploit data that are uniquely your own.  Recognize this will take a lot of people spread throughout /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 11
  • 12. So far, I’ve identified eighteen distinct ways to “put data to work” Internally  Improve operational efficiency  360°-view  Data-Driven Culture • Provide (Sell) Content  New Content  Re-package  Informationalization  Unbundling  Exploiting Asymmetries  Closing Asymmetries *Working out “what’s right for us” is the key challenge for senior leadership! Facilitators  Own the Identifiers  Infomediation  Big Data/Advanced Analytics  Privacy and security  Training  New Marketplaces  Infrastructure technologies  Information appliances  Tools *Every organization must think through the four in bold /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 12
  • 13. Four Basic Strategies     Innovation (Big Data/Advanced Analytics): Find hidden nuggets in the data and,… Content: Provide or exploit content that others don’t have. Build a Data-Driven Culture: Make better decisions, bottom-to-top and across the company. Be the low-cost provider: Superior data quality keeps costs down! /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 13
  • 14. I’m Excited About Informationalization      Eisner: “Content is king” Basic idea: Make existing products and services more valuable by building in more data and information Ubiquity: e.g., The hospital gown. Available to all: Doesn’t require massive quantities of data, people with advanced degrees, or capital investment. Caution: Customers already in information overload. /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 14
  • 15. High Quality Data is Pre-requisite  Poor quality the norm.  Enormous, mostly hidden, costs.  Decision-makers discount data they don’t trust. And analyses based on them. Wisely so.  In advanced analytics, data are highly leveraged. Recall the the financial crisis. /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 15
  • 16. For Data, Only Two Moments Really Matter The moment of creation Note that they do not occur in IT The moment of use The whole point of data quality management is to connect the two! /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 16
  • 17. Data Quality Done Properly Fraction Perfect Records First-time, on-time results 1 0.9 0.8 0.7 0.6 0.5 0 5 10 Accuracy Rate mean 15 control limits Month 20 target Each error not made saves an average of $500. This amounts to millions quickly! /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 17
  • 18. It is so easy for accountability to shift downstream!!! Here’s how you do number 3! /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 18
  • 19. Where does analytics fit? Analytical “sophistication” Basic Process Improvement New, sophisticated algorithms “One-time” opportunity Series of Fundamental Discoveries In the line: Everyone involved Really close to, but not in the line Project team wo/line Permanent “lab” responsibilities “Home” for Analytics /Redman-IDQ-Nov2013 © Navesink Consulting Group LLC, 2000-2013 T. C. Redman, Page 19
  • 20. Think End-to-End Whatever strategy you select, you need a D4-Process: Data: High-quality, well-understood, potentiallyinteresting data is pre-requisite. Discovery: Finding something truly interesting in the data Delivery: Getting the results to a decision-maker, into an ongoing process, into a new product/service, etc. Dollars: Making money from the data, discovery and delivery Expect none to be easy! /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 20
  • 21. It helps to have something others don’t!  Your data are uniquely your own.  And you make more each day.  Subtle and nuanced.  Some, maybe most data become standardized to facilitate communications.  A small fraction offer opportunity for sustained advantage. These data merit special attention! /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 21
  • 22. Putting data to work requires new skills and talent, up the organization chart Everyone/Culture: So far, Information Technology has not delivered on its promise to make everyone smarter. Analysts: The truly great ones are in short supply. Managers:  For every good+ analyst, need dozens of good+ managers.  In every “clever analysis” that actually bears fruit, the “unsung hero” is a manager who took a chance! Executive Leadership:  Stone-cold, sober evaluation of “what we can actually pull off.”  Sooner or later, all change is top-down. /Redman-IDQ-Nov2013 © Navesink Consulting Group LLC, 2000-2013 T. C. Redman, Page 22
  • 23. Federated Structure for Managing Data People Management Data Assets Regular people and managers: Day-in, day-out people management. Regular people and managers: Create high-quality data. Put data to use in novel ways. Departmental HR: Help their units find and advance the talent they need Departmental DG: Facilitate DQ, analytics, delivery, day-in, day-out innovation. Corporate HR: Succession planning, pay scales, etc Corporate DG: “metadata, ” unique data Data Lab: innovation via big data, advanced analytics /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 23
  • 24. I hope I’ve excited, and scared, you! The leadership challenge in a nutshell:  A full-strength data revolution is brewing  Today’s organizations are stunningly unfit for data For most, it is too soon to set strategy. But it is time to get moving  Quality is pre-requisite. Move responsibility out of IT!  Experiment with ways of competing with data  Think end-to-end  Sort out which data are strategic.  Build organizational capability. And above all BE COURAGEOUS! /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 24
  • 25. Questions? Thomas C. Redman, Ph.D. “the Data Doc” +1 732-933-4669 tomredman@dataqualitysolutions.com www.navesinkconsultinggroup.com /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 25
  • 26. Thomas C. Redman, “the Data Doc”  Ph.D., Statistics, Florida State, 1980.  Conceived and led the Data Quality Lab at AT&T Bell Labs.  Formed Navesink Consulting Group in 1996.  Helped dozens of companies think through, define, and advance their data and data quality programs.  Led development of most of today’s best-practice data quality management methods & techniques.  Latest and greatest: “Data’s Credibility Problem,” Harvard Business Review, December, 2013.  Data Driven: Profiting from Your Most Important Business Asset, Harvard Business School Press, 2008.  Known bias: “Data are quite obviously the key asset of the Information Age. Yet today’s organizations are singularly ill-designed for data. This leads me to conclude that learning to compete with and organizing for data is THE management challenge of the 21st century.” /Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 NCG, Page 26

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