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Unlocking Excellence with Agile Metrics

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Data driven continuous improvement

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Unlocking Excellence with Agile Metrics

  1. 1. Unlocking Excellence with Agile Metrics Data-Driven Continuous Improvement May 2016 – Lean Agile Glasgow @MartinBurnsSCO www.linkedin.com/in/MartinBurnsUK
  2. 2. Avoiding EEEEEVIL with Agile Metrics May 2016 – Lean Agile Glasgow @MartinBurnsSCO www.linkedin.com/in/MartinBurnsUK
  3. 3. 3 © 2015 CA. ALL RIGHTS RESERVED. Martin Burns Lives in Edinburgh but spends too much time on planes Improvement obsessive and caffeine addict Been doing incremental and iterative since the 90s. The usual certifications and many logos meant to impress you Lapsed Partick Thistle Fan.
  4. 4. 4 © 2015 CA. ALL RIGHTS RESERVED. In God we trust All others bring data W. Edwards Deming
  5. 5. 5 © 2015 CA. ALL RIGHTS RESERVED. Without data our decision-making process is corrupted Source: http://www.vectorfreebie.com/wp-content/uploads/2016/01/Heart-Sketch.png https://s-media-cache-ak0.pinimg.com/736x/40/05/a7/4005a76193de7788886ea0d0339284f8.jpg Canberra Sydney Perth Melbourne Brisbane London Adelaide Glasgow Hobart Auckland 546mm 557mm 569mm 597mm 603mm 725mm 1115mm 1158mm 1223mm1124mm
  6. 6. 6 © 2015 CA. ALL RIGHTS RESERVED. The first step is admitting you have a problem…
  7. 7. 7 © 2015 CA. ALL RIGHTS RESERVED. • We are a data-driven company • This is data • Therefore • We should be driven by it
  8. 8. 8 © 2015 CA. ALL RIGHTS RESERVED. Oh my!
  9. 9. 9 © 2015 CA. ALL RIGHTS RESERVED.
  10. 10. 10 © 2015 CA. ALL RIGHTS RESERVED. Why are we collecting Data? To make decisions
  11. 11. 11 © 2015 CA. ALL RIGHTS RESERVED. Question: What Metrics are Coveted/Abused/Over-used in Your Organisation?
  12. 12. 12 © 2015 CA. ALL RIGHTS RESERVED. Common Metrics Traps What will impede our outcomes?
  13. 13. 13 © 2015 CA. ALL RIGHTS RESERVED. Common Metrics Traps Manipulation Unbalanced metrics Availability bias Mechanical decision-making False positives/negatives Lagging vs Leading Indicators Mean, Median and Mode - 13 -
  14. 14. 14 © 2015 CA. ALL RIGHTS RESERVED. Summary Stats § The average x value is 9 for each dataset § The average y value is 7.50 for each dataset § The variance for x is 11 and the variance for y is 4.12 § The correlation between x and y is 0.816 for each dataset § A linear regression (line of best fit) for each dataset follows the equation y = 0.5x + 3 http://data.heapanalytics.com/anscombes-quartet-and-why-summary-statistics-dont-tell-the-whole-story
  15. 15. 15 © 2015 CA. ALL RIGHTS RESERVED. Summary Stats
  16. 16. 16 © 2015 CA. ALL RIGHTS RESERVED. Poor Data Integrity Image coursesy of Flickr
  17. 17. 17 © 2015 CA. ALL RIGHTS RESERVED. Beware the One-Metric to Solve Them All
  18. 18. 18 © 2015 CA. ALL RIGHTS RESERVED. Photo courtesy of Flickr : Creative Commons
  19. 19. 19 © 2015 CA. ALL RIGHTS RESERVED. if management sets quantitative targets and makes people’s job depend on meeting them, they will likely meet the targets – even if they have to destroy the enterprise to do it. W. Edwards Deming
  20. 20. 20 © 2015 CA. ALL RIGHTS RESERVED. Photo courtesy of Flickr : Creative Commons
  21. 21. 21 © 2015 CA. ALL RIGHTS RESERVED. How Do I Unravel This All What metrics help us achieve our desired outcomes?
  22. 22. 22 © 2015 CA. ALL RIGHTS RESERVED. First: You Need To Organize Based on Outcomes ••How Deep/Wide is our Agile? Adoption Outcomes ••Are We Delivering Value Faster? Operations Outcomes ••Are We Meeting Expectations? Business Outcomes
  23. 23. 23 © 2015 CA. ALL RIGHTS RESERVED. Second– You Need Context (2 dimensions) Q1: How Mature are the Agile Practices of Your Group (Team/Program/Department/Business Unit)? Just Getting Started We’re Doing It and ….. We’re Doing Our Best and We Can Improve
  24. 24. 24 © 2015 CA. ALL RIGHTS RESERVED. Q2: Which Layer of the Business System are we focused on? Second– You Need Context (2 dimensions)
  25. 25. Activity Q. What Metrics are you Using to Track Agile Adoption?
  26. 26. 26 © 2015 CA. ALL RIGHTS RESERVED. Now Let’s Zero in on Operational Metrics Steering not Aiming
  27. 27. 27 © 2015 CA. ALL RIGHTS RESERVED. numerical goals set for other people, without a road map to reach the goal, have effects opposite to the effects sought. W. Edwards Deming Out of the Crisis, p69
  28. 28. 28 © 2015 CA. ALL RIGHTS RESERVED. not aiming … … but steering Photo courtesy of Flickr : Creative Commons
  29. 29. 29 © 2015 CA. ALL RIGHTS RESERVED. Focus at the right level 0 500 1000 1500 2000 2500 3000 3500 07/04/2015 14/04/2015 21/04/2015 28/04/2015 05/05/2015 12/05/2015 19/05/2015 26/05/2015 02/06/2015 09/06/2015 16/06/2015 23/06/2015 30/06/2015 All Trains - Story Count CFD – Release 3 Done Ready To Validate In Progress To Do Blocked 0 50 100 150 200 250 300 350 400 14/04/2015 21/04/2015 28/04/2015 05/05/2015 12/05/2015 19/05/2015 26/05/2015 02/06/2015 09/06/2015 16/06/2015 23/06/2015 30/06/2015 07/07/2015 All Trains - Features CFD – Release 3 Done In Progress To Do
  30. 30. 30 © 2015 CA. ALL RIGHTS RESERVED.
  31. 31. 31 © 2015 CA. ALL RIGHTS RESERVED. Some of My Favorites: Do It Fast Responsiveness: Feature Cycle Time Velocity (Planned and Actual) / Work Capacity e.g., In Planning we average 6 stories planned per human per sprint. We finish about 2 stories per human per sprint Productivity: Focus Factor * http://www.scruminc.com/wp-content/uploads/2014/05/Hyper-Productive-Metircs.pdf
  32. 32. 32 © 2015 CA. ALL RIGHTS RESERVED. Some of My Favorites: Do It On Time: Sprint Predictability Ranges Keep Doing It: Employee NPS Score
  33. 33. 33 © 2015 CA. ALL RIGHTS RESERVED. Some of My Favorites: Trade Me talk at Agile ANZ and nod to Dan Pink (include you Tube video) Keep Doing It: Autonomy, Mastery and Purpose
  34. 34. 34 © 2015 CA. ALL RIGHTS RESERVED. Some of My Favorites: Keep Doing It: Simple Mood
  35. 35. 35 © 2015 CA. ALL RIGHTS RESERVED. Metrics Mantra #1: Teams Execute Will we complete our work in a sprint (stories, tasks, defects, etc.)?
  36. 36. 36 © 2015 CA. ALL RIGHTS RESERVED. Teams Execute - 36 -
  37. 37. 37 © 2015 CA. ALL RIGHTS RESERVED. Teams: Consistency over Throughput
  38. 38. 38 © 2015 CA. ALL RIGHTS RESERVED. Metrics Mantra #2: Programs Deliver Value Will we meet our plan objectives (features, milestones, quality, etc.)?
  39. 39. 39 © 2015 CA. ALL RIGHTS RESERVED. Programs Deliver Value – Dashboard
  40. 40. 40 © 2015 CA. ALL RIGHTS RESERVED. Programs Deliver Value – Feature Progress
  41. 41. 41 © 2015 CA. ALL RIGHTS RESERVED. Programs Deliver Value – Timeline View
  42. 42. 42 © 2015 CA. ALL RIGHTS RESERVED. Metrics Mantra #3: Portfolios Steer
  43. 43. 43 © 2015 CA. ALL RIGHTS RESERVED. Portfolios Steer – Capacity Modeling
  44. 44. 44 © 2015 CA. ALL RIGHTS RESERVED. Metrics Mantra #4: Occasionally Glance Backward
  45. 45. 45 © 2015 CA. ALL RIGHTS RESERVED. Variance not Average
  46. 46. 46 © 2015 CA. ALL RIGHTS RESERVED. One final thought Photo courtesy of Flickr : Creative Commons http://cultivatingthought.com/author/aziz-ansari/
  47. 47. 47 © 2015 CA. ALL RIGHTS RESERVED. ROTI – return on time invested (this session) Source: http://blogs.adobe.com/agile/files/2013/12/hands-counting.jpg https://s-media-cache-ak0.pinimg.com/736x/4e/5c/f7/4e5cf7d4ccb9c59b6620a9c71944d51e.jpg https://dq9ucdqjq6nrk.cloudfront.net/wp-content/uploads/2014/02/01_sad_emoticon-300x269.jpg https://s-media-cache-ak0.pinimg.com/736x/e9/9b/54/e99b541789969921ebd0110309a35f63.jpg
  48. 48. Senior Principal Transformation Consultant Martin.burns@ca.com Martin Burns MartinBurnsSCO Suzanne Nottage

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