July 2014 Executive Roundtable - Culture of Analytics

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See the presentation Shash Hegde gave at our July 2014 Executive Roundtable. The deck begins to explain why a culture is important, how it's formed, how it affects an organization and the role that analytics can play.

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July 2014 Executive Roundtable - Culture of Analytics

  1. 1. © 2014 Culture of Analytics Shash.Hegde@mariner-usa.com @DataCzar
  2. 2. © 2014 Operation Cat Drop
  3. 3. © 2014 Value of solution = Completeness or Quality of solution. Value = Quality x Acceptance
  4. 4. © 2014 Agenda • Revisit what we spoke about last time • Industry View on culture • Discussion • Mental models • How to succeed • Discussion
  5. 5. © 2014 Digital Disruption
  6. 6. © 2014 • Amazon -> Books. Retail. Cloud. Logistics. Hardware. • Google -> Search. Mobile. Cars. Gadgets. Robots. • Netflix -> Movie rentals. Cable. • Tesla -> Cars. Batteries/Power Generation. • Uber -> Taxis. Parcel Delivery. • Airbnb -> Hotels. Restaurants. Industry lines are blurring
  7. 7. © 2014 Social Analytics Mobile Cloud SMAC Convergence into a stack – a digital platform
  8. 8. © 2014 Source: http://techcrunch.com/2013/12/14/as-software-eats-the-world-non-tech-corporations-are-eating-startups/
  9. 9. © 2014 Adopting the mindset & culture Source: http://www.forbes.com/sites/stevedenning/2014/04/11/why-software-is-eating-the-world/ Continuous Delivery & Agile
  10. 10. © 2014 • Google • Facebook • Amazon • P&G • Progressive Insurance • GE • Netflix Case studies
  11. 11. © 2014 Most data driven company on the planet?
  12. 12. © 2014 • Google File System (2003) • MapReduce (2004) • Google Big Table (2006) • Dremel (2010) “Google Big Query” • Pregel (2010) Large scale Graph processing • Percolator (2010) Incremental indexing • Spanner (2012) Globally distributed database, successor to Big Table They invented “big data”
  13. 13. © 2014 41 Shades of Blue
  14. 14. © 2014 41 Shades of Blue
  15. 15. © 2014 GE
  16. 16. © 2014 Microsoft
  17. 17. © 2014 Discussion
  18. 18. © 2014 • Culture = “How we do things around here” • Culture = Mental Model/Mindset • Culture = Shared set of beliefs, values, and practices • Culture = Operating system for people Definitions
  19. 19. © 2014 • Why have a culture of analytics? • What about culture of innovation, culture of learning, quality, customer centricity, excellence? • If you don’t define a culture, do you get one anyway? • How much effort do you put on “acceptance” of projects? Questions
  20. 20. © 2014 • Has anyone initiated a cultural shift? What happened? • Or has anyone witnessed a cultural shift initiated by somebody else? What happened? • How do you know you if have a culture of analytics? More questions
  21. 21. © 2014 • At your organization, is working with data somebody else’s job? Perhaps a data specialist or IT department. Is it treated similar to, say, IT security? Or is it everybody’s job? Litmus test
  22. 22. © 2014 • Is a “data democracy” a pre-cursor to a data driven culture? • Is culture primarily a leadership issue or can it happen bottom up? How does it start?
  23. 23. © 2014 Mental models
  24. 24. © 2014 All models are wrong, some are useful. -George E. P. Box
  25. 25. © 2014 Cause  Effect (Co)Producer  Product
  26. 26. © 2014
  27. 27. https://www.youtube.com/watch?v=mkJ-Uy5dt5g
  28. 28. © 2014 Different groups, different tactics Source: http://www.enablingchange.com.au/Summary_Diffusion_Theory.pdf • Social norms rather than product benefits. • Increase convenience, reduce cost. • Risk of being left behind. • Invite them to partner in designing new projects • Reward egos (e.g. media coverage) • Recruit for peer education
  29. 29. © 2014 Source: http://www.infoq.com/articles/organizational-culture-and-agile
  30. 30. © 2014 How to succeed
  31. 31. © 2014 Strategies that work • Top-down guidance and or mandates from executives • Promotion of data-sharing practices • Increased availability of training in data analytics • Communication of the benefits of data-driven decision making • Recruitment of additional data analysts Policy Marketing Training Communication Recruitment
  32. 32. © 2014 • Science of Persuasion • Science of Motivation • Feedback loops • Strength of weak ties Some additional arsenal
  33. 33. © 2014 • 6 Heuristics • Reciprocity • Scarcity • Authority • Consistency • Liking • Consensus Science of Persuasion (influence) Source: https://www.youtube.com/watch?v=cFdCzN7RYbw
  34. 34. © 2014 Motivation
  35. 35. © 2014 Science of Motivation Autonomy PurposeMastery Engagement Source: Author Dan Pink’s book - Drive: The Surprising Truth About What Motivates Us
  36. 36. © 2014 Source: http://marcin.floryan.pl/blog/2011/05/motivation-3-0
  37. 37. © 2014 How do you spread it? Close the loop!
  38. 38. © 2014 The strength of weak ties Source: Granovetter's paper "The Strength of Weak Ties“. Over 27,000 citations according to Google Scholar
  39. 39. © 2014 • What other strategies/techniques are you aware of? • Any closing comments? Discussion
  40. 40. © 2014 • Decision Management and Intelligent Business Operations • Modern Data Architectures • How to SMAC enable your enterprise • Internet of Things Additional topics in queue
  41. 41. © 2014 Thank You

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