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Secrets and surprises of high performance: What the data says

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Nicole Forsgren shares results and stories to uncover the secrets and surprises of what really makes high-performing technology-driven teams and organizations, helping you deliver quality software quickly and reliably. The insights include architecture, burnout, leadership, and employee engagement. You’ll leave with takeaways you can apply immediately to make your team more effective and warning signs to watch out for as you continue to push the envelope in your technology journey.

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Secrets and surprises of high performance: What the data says

  1. 1. @nicolefv Secrets and Surprises of High Performance: What the Data Says Nicole Forsgren, PhD
  2. 2. @nicolefv
  3. 3. @nicolefv
  4. 4. @nicolefv “IT doesn’t matter.” -- Nicholas Carr, 2003
  5. 5. @nicolefv “IT doesn’t matter.” -- Nicholas Carr, 2003
  6. 6. @nicolefv Technology matters
  7. 7. @nicolefv
  8. 8. @nicolefv You’re doing it wrong. There is no ”DevOps in a box”
  9. 9. @nicolefv 10 Deploys per day Dev & ops cooperation at Flickr John Allspaw & Paul Hammond Velocity 2009 @nicolefv
  10. 10. @nicolefv DevOps is Technical Practices and Lean Processes and Culture These drive performance outcomes @nicolefv https://www.flickr.com/photos/152950521@N07/37622864031
  11. 11. @nicolefv But intuition falls short So we need data @nicolefv https://www.flickr.com/photos/151876933@N04/38992268995/
  12. 12. @nicolefv@nicolefv https://www.flickr.com/photos/151876933@N04/38992268995/ DevOps is good for Technology Software delivery performance - Deploy frequency (when business demands) - Lead Time for Changes - Mean Time to Recover (MTTR) - Change Fail Rate
  13. 13. @nicolefv High Performing DevOps teams More agile More frequent Code deployments 46x That’s the difference between multiple times per day and once a week or less. Faster lead time from commit to deploy 440x That’s the difference between less than an hour and more than a week. @nicolefv https://www.flickr.com/photos/151876933@N04/38992268995/
  14. 14. @nicolefv High Performing DevOps teams More reliable Faster mean time to recover from downtime 96x That means high performers recover in less than an hour instead of several days As likely that changes will fail 1/5x That means high performer’s changes fail 0-15% of the time, compared to 31-45% of the time. @nicolefv https://www.flickr.com/photos/151876933@N04/38992268995/
  15. 15. @nicolefv DevOps is good for organizations @nicolefv https://www.flickr.com/photos/151876933@N04/38992268995/
  16. 16. @nicolefv High Performing tech organizations are twice as likely to meet or exceed Commercial Goals • Productivity • Profitability • Market Share • # of customers 2x @nicolefv https://www.flickr.com/photos/151876933@N04/38992268995/
  17. 17. @nicolefv High Performing tech organizations are twice as likely to meet or exceed Commercial Goals • Productivity • Profitability • Market Share • # of customers Non-commercial Goals • Quantity of products or services • Operating efficiency • Customer satisfaction • Quality of products or services • Achieving organizational or mission goals 2x @nicolefv https://www.flickr.com/photos/151876933@N04/38992268995/
  18. 18. @nicolefv High Performing tech organizations are twice as likely to meet or exceed Commercial Goals • Productivity • Profitability • Market Share • # of customers Non-commercial Goals • Quantity of products or services • Operating efficiency • Customer satisfaction • Quality of products or services • Achieving organizational or mission goals 50% Higher market cap growth over 3 years 2x @nicolefv https://www.flickr.com/photos/151876933@N04/38992268995/
  19. 19. @nicolefv Software Delivery Performance is comprised of throughput and stability, and both are possible without tradeoffs @nicolefv@nicolefv https://www.flickr.com/photos/151876933@N04/38992268995/
  20. 20. @nicolefv How do we get there? @nicolefv https://www.flickr.com/photos/fantascapes/4530372648
  21. 21. @nicolefv Maturity Models
  22. 22. @nicolefv Maturity Models don’t work
  23. 23. @nicolefv Maturity models are for CHUMPS @nicolefv
  24. 24. @nicolefv Maturity models are for CHUMPS @nicolefv
  25. 25. @nicolefv@nicolefv https://www.flickr.com/photos/nanpalmero/9313659376 Maturity models tell us we are done once we reach a certain destination… and then the world passes us by
  26. 26. @nicolefv Maturity models tell us (and leaders) to stop dedicating resources once we have arrived. @nicolefv https://www.flickr.com/photos/volvob12b/9988822123/
  27. 27. @nicolefv Maturity models tell us we all follow the same path to success @nicolefv https://www.flickr.com/photos/mortaupat/6410006785
  28. 28. @nicolefv Maturity models tell us technology is a checklist to be completed and not an exciting journey to continually explore and improve. @nicolefv https://www.flickr.com/photos/pebb/42467336382
  29. 29. @nicolefv Architecture matters… technology doesn’t
  30. 30. @nicolefv Technology stack doesn’t matter •Low performers are more likely to: • be working with outsourced software • be working on a mainframe system BUT • Working on a mainframe system was not correlated with performance. • Working on greenfield or brownfield (or any other system) was not correlated with performance, either. @nicolefv https://www.flickr.com/photos/serenasoftware/3288275568
  31. 31. @nicolefv Architectural outcomes matter Can my team •Change the design of its system •Test the system •Deploy the system ... without communication and coordination with people outside the team? @nicolefv https://commons.wikimedia.org/wiki/File:BalticServers_data_center.jpg
  32. 32. @nicolefv Conway’s Law “organizations which design systems … are constrained to produce designs which are copies of the communication structures of these organizations”
  33. 33. @nicolefv We can make work better
  34. 34. @nicolefv
  35. 35. @nicolefv Smart investments in tech and practices make our work better •The work? •Less deployment pain •Less burnout •Higher employee Net Promoter Score @nicolefv https://www.flickr.com/photos/151876933@N04/38992268995/
  36. 36. @nicolefv Microsoft Engineering Thiago Almeida -- DevOps Days London, 2016 Work/Life Scores Before CD: 38% After CD: 75% https://vimeo.com/165184757
  37. 37. @nicolefv Employees in high performing organizations are 2.2 times more likely to recommend their organization as a great place to work @nicolefv https://www.flickr.com/photos/thomashawk/17383831292
  38. 38. @nicolefv Some of my other favorite misconceptions Some of my other favorite data findings!
  39. 39. @nicolefv Some of my other favorite misconceptions Some of my other favorite data findings! • Change advisory boards are useless* • Integration times and branch lifetimes lasting hours are better than days
  40. 40. @nicolefv You can help
  41. 41. @nicolefv Some of my other favorite misconceptions Intuition is good, but we need to confirm with data & science bit.ly/DORA-ASODR
  42. 42. @nicolefv TL;DR •Technology matters •Maturity models don’t work •Architecture > technology •We can make work better •You can help! bit.ly/DORA-ASODR
  43. 43. @nicolefv Thank you! nicolefv@devops-research.com nicolefv.com @nicolefv

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