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Creating a Data-Driven Organization (Data Day Seattle 2015)

My slides about "Creating a Data-Driven Organization" from Data Day Seattle 2015

Creating a Data-Driven Organization (Data Day Seattle 2015)

  1. 1. Creating a Data-Driven Organization Carl Anderson 9:15am, Grand 2 @leapingllamas | www.p-value.info
  2. 2. Why data-driven?
  3. 3. 5%more productive Controlling for other factors, data-driven orgs are Brynjolfsson, et al 2011. Strength in numbers: how does data-driven decisonmaking affect firm performance? Social Science Research Network
  4. 4. $13/ $1 invested Analytics pays back http://nucleusresearch.com/research/single/analytics-pays-back-13-01-for-every-dollar-spent/
  5. 5. What is data-driven?
  6. 6. Having lots of reports does not make you data-driven.
  7. 7. Having lots of dashboards does not make you data-driven.
  8. 8. Having lots of alerts does not make you data-driven.
  9. 9. Figure from http://www.bwfhosting.com/we-got- your-back/
  10. 10. Data-driven: you must have analytics Not necessarily data-driven ! Reporting Analysis Descriptive Prescriptive What? Why? Backward-looking Forward-looking Raise questions Answer questions Data → Information Data + Information → insights Reports, dashboards, alerts Findings, Recommendation No context story telling
  11. 11. https://www.sas.com/news/sascom/analytics_levels.pdf Levels of Analytics
  12. 12. Analytics Value Chain Figure from http:// blogs.adobe.com/digitalmarketing/analytics/reporting-vs-analysis-whats-the- difference/
  13. 13. “Analytics is about impact…In our company [Zynga], if you have brilliant insight and you did great research and no one changes, you get zero credit.” Ken Rudin Facebook
  14. 14. Train analysts to be business savvy 2013 Strata+Hadoop talk: https://www.youtube.com/watch?v=RJFwsZwTBgg
  15. 15. Having a hadoop cluster does not make you data-driven.
  16. 16. Leverage data as a strategic asset.
  17. 17. Data-driven requires a data culture
  18. 18. Culture Testing Iterative, learning Open, sharing Self service Data leadership Broad data literacy Inquisitive, Questioning Goals first Data Driven Culture
  19. 19. a strong testing culture Being data-driven means having… Innovate through online and offline experimentation. Encourage hypothesis generation broadly across org.
  20. 20. “you get surprises more often, and surprises are a key source of innovation. You only get a surprise when you are trying something and the result is different than you expected, so the sooner you run the experiment, the sooner you are likely to find a surprise, and the surprise is the market speaking to you, telling you something you didn’t know.” Scott Cook Intuit Baer, D. 2013. Why Intuit founder Scott Cook want you to stop listening to your boss. Fast Company
  21. 21. Optimize for Right Thing
  22. 22. Iterate
  23. 23. an open, sharing culture Being data-driven means having… No data hoarding or silos. Bring data together to create rich contexts. Connect the dots.
  24. 24. Order #16478645 Belinda Smith Context is King
  25. 25. Order #16478645 Belinda Smith Context is King
  26. 26. Order #16478645 Belinda Smith Context is King
  27. 27. Order #16478645 Belinda Smith Context is King
  28. 28. Order #16478645 Address Belinda Smith Context is King
  29. 29. Order #16478645 Address Belinda Smith Context is King
  30. 30. Order #16478645 Address Belinda Smith Context is King
  31. 31. Order #16478645 Address Refer a friend Belinda Smith Context is King
  32. 32. 1/3 business leaders frequently make decisions with data that they cannot trust Business Analytics and Optimization for the Intelligent Enterprise. IBM Invest in data quality
  33. 33. a self service culture Being data-driven means having… Business units have necessary data access as well as within- team analytical skills to drive insights, actions, and impact.
  34. 34. Traits of great analysts • Numerate • Detail-oriented • Skeptical • Confident • Curious • Communicators • Data lovers • Business savvy Few, S. 2009. Now You See It. Analytics Press, Oakland has a good discussion of this topic, pp. 19–24.
  35. 35. Hiring not just as individuals but to complement team Nordstrom data lab (as of Strata 2013)
  36. 36. a broad data literacy Being data-driven means having… All decision-makers have appropriate skills to use and interpret data.
  37. 37. Analysts must sell, sell, sell their product
  38. 38. http://www.uglyresearch.com/UglyResearch_DataEasy_DecidingHard.pdf Tie actions to outcomes
  39. 39. a goals first approach. Being data-driven means having… Set out metrics before experiment. What does success mean? Have an analysis plan. Prevent gaming the system.
  40. 40. an objective, inquisitive culture Being data-driven means having… ‘“Do you have data to back that up?” should be a question that no one is afraid to ask and everyone is prepared to answer’—Julie Arsenault.
  41. 41. a visible, clearly-articulated strategy Being data-driven means having… Commonly understood vision. Suite of well-designed, accessible KPIs. All staff understand how their work ties back to these metrics.
  42. 42. strong data leadership Being data-driven means having… A head of data to evangelize data as strategic asset with budget, team, and influence to drive cultural change.
  43. 43. Which strategies have proved successful in promoting a data-driven culture in your organization? Strategy % of respondents Top-down guidance and / or mandates from execs 49 Promotion of data-sharing practices 48 Increased availability of training in data analytics 40 Communication of the benefits of data-driven decision-making 40 Recruitment of additional data analysts 17 2013. Fostering a data-driven culture. Economist Intelligence Unit. Sample of 530 execs.
  44. 44. but bottom up too Change should not just be top-down Everyone in org has role and responsibility through “leveling up” their data skills, mutual mentoring, and embedding data into their processes.
  45. 45. 2013 O’Reilly Data Science Salary Survey Learn and you shall receive
  46. 46. blindly following data. Being data-driven doesn’t mean Augment decision makers with objective, trustworthy, and relevant data.
  47. 47. using data to effect impact and results Ultimately, data-driven means Push data through “analytics value chain” from collection, analysis, decisions, action, and finally to impact. Partway along chain doesn’t count.
  48. 48. Example actions • Analyst competency matrix • Raise bar for new analyst hires • Vision statement: data culture • Stats for managers class • Mentor / train analysts to improve skills such as stats, SQL • Mentoring staff in experimental design • Democratizing data access through BI tools • Push on ROI, tie back to strategic objectives
  49. 49. Don’t get complacent! “With the exception of, say, an Amazon, no global store chain was thought to have demonstrably keener data-driven insight into customer loyalty and behavior”
  50. 50. Tesco Today • Stock at 11 year low • Shedding 9000 jobs • Closing 43 stores • $9.6B loss for 2014 fiscal year • Dunhumby, their analytics gem, up for sale • Warren Buffett: “I made a mistake on Tesco”
  51. 51. Data Organization Decision Making People Data Leadership Culture Analytics org: composition, skills, training Data quality, data management Embedded, federated analytics Testing mindset, fact-based, anti-HiPPO Chief Data Officer / Chief Analytics Officer Collaborative, inclusive, open, inquisitive Summary
  52. 52. Bake in data-driven culture early!
  53. 53. Available now 1. What is Data-Driven? 2. Data Quality 3. Data Collection 4. Analyst Org 5. Data Analysis 6. Metric Design 7. Story Telling 8. A/B Testing 9. Decision Making 10. Data-Driven Culture 11. Data-Driven C-suite 12. Privacy, Ethics 13. Conclusions http://shop.oreilly.com/ Copyright © 2015 Carl Anderson
  54. 54. Available July 1. What is Data-Driven? 2. Data Quality 3. Data Collection 4. Analyst Org 5. Data Analysis 6. Metric Design 7. Story Telling 8. A/B Testing 9. Decision Making 10. Data-Driven Culture 11. Data-Driven C-suite 12. Privacy, Ethics 13. Conclusions http://shop.oreilly.com/ Copyright © 2015 Carl Anderson
  55. 55. Questions? @leapingllamas http://p-value.info carl.anderson@warbyparker.com
  56. 56. spares
  57. 57. Vision Statement: data culture STRONG DATA LEADERSHIP • Data leaders that actively evangelize data as a strategic asset, leveraged to its fullest to impact all parts of the business. • Strong data leadership that understands and support the needs of the business. It supports the analytics organization by providing them with a clear career path, enables them to perform their best, to be happy and productive, and to maximize their impact. • Managers that expect and rely on data insights to make informed decisions. More generally across organization, data and analytics are deeply embedded into our processes and decisions vision statement—an aspirational description of what an organization would like to accomplish in the mid-term or long-term future
  58. 58. Vision Statement: data culture OPEN, TRUSTING CULTURE • A centralized set of coherent data sources without any silos. • Business units have a sense of data ownership, proactively managing data quality of their sources. • Broad access to data — Everyone who needs access to data to perform their function, has access. — Everyone only has access to the data that they need to perform their function. Sensitive data, such as customer and Rx data, should be treated with extreme caution: highly restrict access, anonymize, and encrypt. — All staff can easily get a holistic view of the company through highly visible and accessible dashboards, reports, and analysis. Systems are instrumented and alerted as reliable early warning systems. • Analysts are highly collaborative, proactively reaching out (across departments) to help validate ideas and ensure objectivity.

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