Agile metrics at-pmi bangalore
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The document discusses metrics for agile teams. It begins by introducing agile principles like Scrum and Lean that emphasize eliminating waste, delivering value early, and responding quickly to change. It then explains that metrics are important for agile teams for several reasons: to provide transparency to stakeholders, enable data-driven decision making, get feedback to improve estimates, and change day-to-day behaviors. However, metrics must be simple, change behaviors in a positive way, and not demotivate teams. The document provides examples of common agile metrics like velocity, story completion rates, and defect rates and advocates for visual dashboards that are transparent and aim to continuously improve.
Agile metrics at-pmi bangalore
- 1. Understanding Metrics for Agile Teams Bimlesh Gundurao Sept 26 2013 1
- 2. Vision To become the most preferred business partner to our customers through leadership in our actions, values and social responsibility People Business Mission To be a world class organization in enabling clients to become Leaders in their industry Technology Values LEAD by Example Leadership, Empower, Agile, Decisive A Business, Technology and Talent Development Consulting Company with focus on Healthcare , Retail & IT 2
- 3. are you measuring your performances ? 3
- 4. Agile Manifesto & Scrum Framework Time box Commit No Changes Inspect Adapt 4
- 5. Lean Principles • Eliminate waste • Build quality in • Create knowledge • Defer commitment • Deliver fast • Respect people • Optimize the whole 5
- 6. different perspectives self-induced vs. enforced internal vs. external snapshot vs. forward looking 6
- 8. Why do Metrics matter? They provide true reflection 8
- 9. Enter Agile some Agile principles: Value for the customer as early as possible Eliminate Waste (WIP, YAGNI) Drive and Respond to Change, quickly Time/Capacity Boxing (see Scrum and Kanban) Provide Visibility into project progress Create 9
- 10. Why do Metrics matter REASONS #1 & #2 • We Have to! • Self Defense! Every stakeholder wants to know what’s going on through a quantified measure! 10
- 11. Why do Metrics Matter? Reason #3 To Make Business Decisions • Decision making frequency increases multi-fold • Such as - Should we start this effort - Which team needs the most help now - When do we stop doing this product backlog - Do we understand the customer better - Did it actually help to remove that - impediment 11
- 12. Why do Metrics Matter? Reason #4 • To get feedback, so that forward-looking guesses have a higher probability of being right • We make a guess (aka estimate), and then we check later how good the guess was • If it is off a lot...maybe: ”gee, we need to learn how to estimate better” 12
- 13. Why do Metrics Matter? Reasons #5 • To change behavior... – Not just the key business-decisions – But as close as possible to all the behavior on a day-to-day basis 13
- 14. What you can’t control you can’t manage! What you can’t manage you can’t measure! 14
- 16. Choosing the right Metrics 1. Goal Setting 2. Vital Few Vs Trivial Many 16
- 17. too many KPIs are useless 17
- 18. Goal Setting Answer 3 questions – What is its purpose? – How will you report? – How will you gather data? 18
- 19. Product Life Cycle Metrics Measured at different stages has different value 19
- 21. The product owner plans the product in layers Release Product or Project How can we release value incrementally? What business objectives will the product fulfill? What subset of business objectives will each release achieve? Product Charter Elevator Pitch What user constituencies will the release serve? What general capabilities (big stories) will the release offer? Release plan Iteration What specifically will we build? (user stories) Story (Backlog Item) How will this iteration move us toward release objectives? What user or stakeholder need will the story serve? Iteration Plan How will it specifically look and behave? How will I determine if it’s completed? Story Details © 2006-2007 Jeff Patton, All rights reserved, www.agileproductdesign.com Acceptance Tests 21
- 22. The Planning Onion can grow to include product portfolios and business strategy Product or Project What business objectives will the product fulfill? Product Charter Elevator Pitch Release How can we release value incrementally? Product or Project What subset of business objectives will each release achieve? Release What user constituencies will the release serve? Iteration Iteration What general capabilities (big stories) will the release offer? Release plan Story What specifically will we build? (user stories) Story (Backlog Item) How will this iteration move us toward release objectives? What user or stakeholder need will the story serve? Iteration Plan How will it specifically look and behave? How will I determine if it’s completed? Story Details © 2006-2007 Jeff Patton, All rights reserved, www.agileproductdesign.com Acceptance Tests 22
- 23. The Planning Onion can grow to include product portfolios and business strategy Product or Project Release Iteration Story © 2006-2007 Jeff Patton, All rights reserved, www.agileproductdesign.com 23
- 24. The Planning Onion can grow to include product portfolios and business strategy Business Strategy Yearly by PO Product Portfolio Product or Project Release Iteration Story © 2006-2007 Jeff Patton, All rights reserved, www.agileproductdesign.com Bi Yearly by PO Quarterly by PO and Team Bi-weekly by team Daily by team member 24
- 25. The Planning Onion can grow to include product portfolios and business strategy Business Strategy Profitability ROI Product Portfolio Product or Project NPS Release Business Value Iteration Velocity Story DOD © 2006-2007 Jeff Patton, All rights reserved, www.agileproductdesign.com 25
- 26. Measuring Agile Team Maturity Storming Performing Its all about Conversations and Behaviors Forming Norming Disperse 26
- 28. The Team wants metrics. Why? • To help them see their work • To plan with • To determine when successful • To push back on magical-thinking managers • To challenge themselves 28
- 29. Some key attitudes • We accept that things always were and always will be imperfect • We relentlessly pursue perfection 29
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- 32. The Agile approach • Truth and transparency are essential • The metrics are first for the Team • Typically, we trust the Team 32
- 33. The Agile approach - 2 • Managers can visit a team at any time to see the meaning of any numbers • Managers have the patience and respect to observe the Gemba 33
- 34. keep it simple, one step at a time 34
- 35. Good Metrics 1. Be accurate enough to enable better decision making 2. Enable better actions and serious Measure Results not Output improvement Vital Few 3. Not be seriously gamed (inaccurate); ideally - “gaming” is actually better behavior Measure Trends Easy to Collect 4. Change the behavior of all members of team and related managers Reinforce Desired Behavior 5. Motivate the team (or at least not deAmplify Learning motivate) 6. Simple enough that they are done, and used well 7. Enable optimizing the whole 35
- 36. Metrics & Myths Metrics get stale over time, Objective is lost! 36
- 37. Metrics Perspectives from the Trenches “I once worked for a team that started doing TDD, and we decided to measure the number of unit tests written during a sprint. The metric reminded us of the fact that we wanted to write tests, and it provided opportunities for celebrating as a team that we were implementing our decision. We weren't judged by outside the team on the metric, though, we didn't try to maximize it, and as soon as writing tests became an integral part of our work, we abandoned the metric, because it wasn't useful anymore” 37
- 38. Metrics should not scare or threaten people Enforced metrics are often cheated or ignored 38
- 39. Agile Metrics • Velocity • % Change in Velocity since (inception, last year) • Stories Completed (done, done) • Number of Passing Unit and Functional Tests (today or with growth trend) • Number of story points completed to date; % of total. • Bugs that escaped the Sprint • Bugs open today • • % BV completed (if use BV points or similar) Oldest bug open (with Sev level) • Sprints with stories incomplete • Sprints with added stories • Unplanned tasks (in the X Sprint); related hours • • Full Product Backlog (remaining stories) Impediments Open Vs Resolved 39
- 40. Agile Metrics – More • Stories added to / subtracted from the Release • Age of each story to done, done; average age • Impediments removed to date • Defects identified after done, done • If start with big bug list – – – Builds that passed/failed initially, to date • • Defects identified after release • Bugs added (old features) (per time) Old Bugs resolved / closed (per time) Old Bugs remaining (over time) If starting with minimal automated tests – – – Number of automated tests (unit, functional, etc) Number of manual tests (that could be automated) Effort on manual testing • Metrics around quality of builds and regression tests • Metrics around quality of code (eg, cyclomatic complexity) • Code coverage by automated tests (unit, functional, etc.) 40
- 41. Some Kanban Specific Metrics lead time cycle time 40 60 25 ouch! ouch! Cycle Time = Number of Things in Process/ Average Completion Rate Little’s Law time spent in each lane ? bottlenecks ? Flow = Speed * Density, Density Speed => Traffic Jam 41
- 42. What metrics are these organizations using? 42
- 43. What Metrics works for you is important! Case Study 1 • Rework Ratio • Defects closed v/s resource capacity • New defects injected (open + closed – monthly iterations) • Defect per dev per week (Injected) • Review Yield = (Defects captured in Review)/(Total defects captured in review + testing) • RCA (for client defects and returnrework defects from iterations) and corrective actions • Avg. Story points (expected v/s actual) 43
- 44. What Metrics works for you is important! Case Study 2 • At completion of sprint, sprint status(g/y/r) and overall project health(g/y/r) – The above measure is dependent on the # of US planned versus done; if US not ‘done’, its not accounted in the completed US – Project health depends not only on US done, but on cross functional dependencies(internal + external) and risks status. If any of those aren’t Green, project health is Y or R. • Bug status reported at sprint completion • Stories Progress - Hours completed vs remaining • Stories Progress - how much work remains on each story, whats the progress towards completing the work on each story 44
- 45. What Metrics works for you is important! Case Study 3 • Project: – Burn-downs for Sprints – Burn-ups for Releases (it provides greater visibility into the value that can be derived at a certain point in time) – Defect Arrival and Kill Rates – Team velocity (with an eye on variance over time. Reducing variance are signs of a stabilizing system) • Program/Portfolio: – Cycle times – Lead times – Throughput – Wait times and more.. 45
- 46. What Metrics works for you is important! Case Study 4 Sprint Level • Velocity • Wastage in hours/Sprint • Service Test Automation Pass rate (Program) • Regression Pass Rate (Team wise & Program) • User Story - DOD Completeness • Code Coverage Program Level • Business Value Delivered vs Business Value Backlog 46
- 47. What Metrics works for you is important! Case Study 5 • % Progress. Acceptance Criteria Data. User Acceptance Test : Accepted Data. Rework data After UAT. Test cases Executed. Test Cases returned. Velocity of sprint. Actual Acceptance Planned Vs final accepted. The above which in turn will get the quality of the sprints. Program Plan levels: – – – Number of Stories Mapped to each release/Sprint. Number of Stories for total release. Probable cost per sprint based on a Projected Acceptance criteria. Line Management perspective. – – Release/ Sprint Level: – – – – – – – – – • • – – – • From Customer Validation: – – – – – • Either use Effort in Time for each Story. In depth Sub task level effort. Team Level: – • CSI. % of Progress in each release. Cost per sprint / Cost per Release. Cost Burn down. Value Burn up Estimations – – • No: of Sprints Planned. Total no: of Team members in reach release. FTE’s & Consultants. Total no: of Cross functional Team Members. Future Forecast of Team members. Ramp up data across sprints. Happiness Factor Large Scale Integration Projects: – Integration Hand-offs 47
- 49. Basic Metrics Value Customer Surveys Predictability Velocity Burn Up/ Burn Down Story Cycle Time Technical Debt Collaboration Quality 49
- 50. Extended Metrics Value Customer Surveys NPS Burn Up/ Burn Down NPV/ ROI Continuous Improvement Work-inProgress Collaboration Cost per Sprint/ Point Velocity Real Value Delivered Team Surveys Story Cycle Time Predictability Technical Debt RTF/ Automated Tests Defects Quality 50
- 51. TO SUMMARIZE 51
- 52. build a simple but effective dashboard 52
- 54. @you: are you getting this ? communicate clearly 54
- 56. use simple tools (but use them!) 56
- 57. transparency: Metrics visible to everyone 57
- 58. aim higher 58
- 59. Q & A 59
- 60. Bimlesh Gundurao +91-988 024 4406 bimlesh@aguaisolutions.com www.aguaisolutions.com Twitter - @bimleshgundurao Thank You 60