Key Note - Path to Agility 2013 - Kanban - the alternative path to agility


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The Kanban Method represents the alternative path to agility. It is the "start with what you do now" approach that promotes evolutionary change to improve business agility rather than adopting a defined Agile method. This presentation explains the mechanics of virtual kanban systems and their implications. It defines the Kanban Method and explains how it creates an evolutionary capability in your organization

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Key Note - Path to Agility 2013 - Kanban - the alternative path to agility

  1. 1. Kanban An Alternative Path to Agility What is Kanban? How do you implement it? What are the benefits? Path to Agility Columbus, Ohio 2013, @djaa_dja
  2. 2. The Meaning of Agile, @djaa_dja
  3. 3. What Agile Methods Seek to Achieve Agile methods ask us to… Agile methods ask us Enable aMake trust (yet with Let’s not high to… culture boreProgress you Create slide showing & again) with craftsmanship a Feedback Loops imperfect information Create a work-in-progress enable a capability to Treat The trust dividend eliminates adapt the Manifesto! work ethic liability bureaucracy & encourages as Reworking & course correcting if it were a collaborative working & use of this was Withas new Agile methods tacit is 1st gen than an asset rather information arrives knowledge limited to adapting to changing Encourage high quality, well & faster better risk management requirements or “perfect” engineered code that is for scope than delaying easily Knowledge work as new adapted (refactored)is perishable. information Focus on finishing things quickly information arrives and requires before they go stale very little rework due to errors, @djaa_dja
  4. 4. The Kanban Method – an alternative path to agility!, @djaa_dja
  5. 5. Kanban Method A management & cultural approach to improvement View creative knowledge work as a set of services Encourages a management focus on demand, business risks and capability of each service to supply against that demand, @djaa_dja
  6. 6. The Kanban Method is not… A project management or software development lifecycle process Nor, does it encourage a processcentric approach to improvement!, @djaa_dja
  7. 7. Don’t do this!... Management Imposes Designs Or Defines Process Workers, @djaa_dja Follow Process Coaches
  8. 8. Kanban Method Uses visualization of invisible work and virtual kanban systems Installs evolutionary “DNA” in your organization Enables adaptability in your business processes to respond successfully to changes in your business environment, @djaa_dja
  9. 9. Kanban Method • “Kanbanize” your existing process • Provoke existing processes to change and service delivery to improve • Each workflow will evolve a uniquely tailored process solution, “fitter” for its context • Customer & employee satisfaction will improve, @djaa_dja
  10. 10. 6 Practices for Evolutionary DNA The Generalized Version Visualize Limit Work-in-progress Manage Flow Make Policies Explicit Implement Feedback Loops Improve Collaboratively, Evolve Experimentally (using models & the scientific method), @djaa_dja
  11. 11. What is a kanban system?, @djaa_dja
  12. 12. A Kanban Systems consists of “kanban” signal cards in circulation, @djaa_dja
  13. 13. Using a virtual kanban system, @djaa_dja
  14. 14. Kanban are virtual! Backlog Engineering Ready 5 Development Test Ready Testing UAT 3 5 3 ∞ Ongoing Done Change Requests Deployment Ready ∞ B Pull These are the virtual kanban F J G C F Pull Boards are not required to do F F Kanban! F I F The board D a visualization of the is F * The first system used database workflow process, the work-intriggers to signal pull. There was no progress and the kanban PTCs board! Pull I, @djaa_dja
  15. 15. Commitment is deferred Backlog Pool of Ideas Engineering Ready 5 Testing UAT 3 5 3 ∞ Ongoing Done Items in the backlog remain optional and unprioritized Change Requests Pull F F F F F F F Development Test Ready D G Wish to avoid discard after commitment PTCs Commitment point, @djaa_dja E We are committing to getting started. We are certain we want to take delivery. I Deployment Ready ∞
  16. 16. Discard rates are often high Pool of Ideas Engineering Ready 5 Development Test Ready Testing UAT 3 5 3 ∞ Ongoing Done The discard rate with XIT was 48%. ~50% is commonly observed. Change Requests F F F F G Reject Deferring commitment and Options have value because the avoiding interrupting future is Dworkersuncertain for estimates E 0%makes rate implies there is discard sense when discard no uncertainty about the future rates are high! PTCs I Discarded I, @djaa_dja Deployment Ready ∞
  17. 17. Replenishment Frequency Pool of Ideas Engineering Ready 5 Replenishment Change Requests Pull F F F F F F F Development Test Ready Testing UAT 3 5 3 ∞ Ongoing Done Frequent replenishment is more agile. On-demand replenishment is D most agile! G PTCs Discarded I, @djaa_dja E The frequency of system replenishment should reflect arrival rate of new information and the transaction & coordination I costs of holding a meeting Deployment Ready ∞
  18. 18. Delivery Frequency Pool of Ideas Change Requests Pull F F F F F F F Engineering Ready Development Test Ready Testing UAT 3 5 3 ∞ Ongoing Done Frequent deployment is more agile. 5 Deployment buffer size can On-demand deployment reduce as frequency of D deliveryagile! most increases G PTCs Discarded I, @djaa_dja is E The frequency of delivery should reflect the transaction & coordination costs of deployment plus costs & toleranceI of customer to take delivery Deployment Ready ∞ Delivery
  19. 19. Specific delivery commitment may be deferred even later DeployEnginPool of Ideas eering Ready 5 Development Test Ready Testing UAT 3 5 3 ∞ Ongoing Done ment Ready ∞ Change Requests Pull F F F F F F F D G E PTCs We are now committing to a specific deployment and delivery date Discarded *This may happen earlier if I circumstances demand it I, @djaa_dja 2nd Commitment point*
  20. 20. Defining Kanban System Lead Time Pool of Ideas Engineering Ready 5 Deployment Ready ∞ The clockTest starts ticking when UAT we customers Ready Development accept the Testing is 5 ∞ 3 order, not when it 3 placed! Ongoing Done Until then customer orders are merely available options Change Requests Pull F F F F F F F D G E System Lead Time PTCs I Discarded I, @djaa_dja Lead time ends when the item reaches the first ∞ queue.
  21. 21. Little’s Law & Cumulative Flow Delivery Rate Pool of Ideas = Lead Time Avg. Lead Time WIP, @djaa_dja WIP Ready To Deploy Avg. Delivery Rate
  22. 22. Flow the Efficiency Flow efficiency measures Pool Enginpercentage of total lead time of spent actually adding value eering is Development Ideas Ready (or knowledge) versus waiting 3 Ongoing 2 Done Testing 3 Verification Acceptance Deployment Ready ∞ Until then customer orders are merely available options Flow efficiency = Work Time Multitasking means time spent E in working columns is often waiting time PB GY DE Waiting Working MN AB Waiting Working Waiting Lead Time * Zsolt Fabok, Lean Agile Scotland, Sep 2012, Lean Kanban France, Oct 2012, @djaa_dja x 100% Lead Time Flow efficiencies of 2% have been F reported*. 5% -> 15% D normal, P1 is > 40% is good! G I Done
  23. 23. Observe Lead Time Distribution as an enabler of a Probabilistic Approach to Management Lead Time Distribution 3.5 3 CRs & Bugs 2.5 2 1.5 1 0.5 1 4 7 0 3 6 8 14 14 13 12 12 11 10 99 92 85 78 71 64 57 50 43 36 29 22 8 15 1 0 Days This is multi-modal data! Mean of 31 days The workexpectation of SLA is of two types: Change Requests (new 105 and Production features);days with 98 % Defects SLA expectation of 44 days with 85% on-time, @djaa_dja on-time
  24. 24. Mean 5 days Change Requests Production Defects Filter Lead Time data by Type of Work (and Class of Service) to get Single Mode Distributions 98% at 25 days 85% at 10 days, @djaa_dja 98% at 150 days Mean 50 days 85% at 60 days
  25. 25. Allocate Capacity to Types of Work Pool of Ideas Engineering Ready Ongoing 2 Change Requests Development 4 3 Done Testing 3 Verification Acceptance Consistent capacity allocation E some consistency to should bring more consistency to MN delivery rate of work of each D AB type F Lead Time PB DE Productio n Defects I Deployment Ready 3 G P1 GY, @djaa_dja Separate understanding of Separate understanding of Lead Lead Time for each type of Time for each type of work work Lead Time ∞ Done
  26. 26. Infinite Queues Decouple Systems Pool Enginof eering The infinite queue Development decouples Ideas Ready the systems. The deployment 3 Done Ongoing system uses batches and is 2 separate from the kanban system F The 2nd commitment is actually a commitment for PB the downstream deployment system DE Deployment Ready Testing 3 Verification Acceptance D ∞ MN G P1 E AB The Kanban System gives us confidence to make that I downstream commitment GY 2nd Commitment point, @djaa_dja Done
  27. 27. Identifying Buffers Pool of Ideas Engineering Ready Ongoing 2 F GY, @djaa_dja Done verification Acceptance P1 PB I 3 3 I am a buffer! D G Testing Development Deployment Ready DE The clue isis in my name “… The clue in my name – – E Ready” “… Ready” MN AB I am buffering non-instant availability or activity with a availability or an activity with acyclical cadence cyclical cadence ∞ Done
  28. 28. Visualizing Pull Signals Pool of Ideas Engineering Ready Ongoing 2 F D G GY, @djaa_dja 3 Done 3 verification Acceptance Done ∞ I indicate “pullable” P1 E I am not a separate queue PB I Testing Development Deployment Ready DE MN AB The WIP limit for development applies to on-going or completed “pullable” work
  29. 29. Defining Customer Lead Time Pool of Ideas Engineering Ready Development Test Ready Testing UAT 3 5 3 ∞ Ongoing 5 Change Requests Done The clock still starts ticking when we accept the customers order, not when it is placed! Deployment Ready ∞ Pull F F F F F F F D G E Customer Lead Time PTCs Discarded I, @djaa_dja The frequency of delivery cadence will affect customer I lead time in addition to system capability Done ∞
  30. 30. impact The Optimal Time to Start If we start too early, we forgo the option and opportunity to do something else that may provide value. If we start too late we risk Ideal Start incurring the cost of delay When we need it Here With a 6 in 7 chance of on-time delivery, we can always expedite to insure on-time delivery 85th percentile Commitment point, @djaa_dja
  31. 31. Metrics for Kanban Systems Cumulative flow integrates demand, WIP, approx. avg. lead time and delivery rate capabilities Lead time histograms show us actual lead time capability Flow efficiency, value versus failure demand (rework), initial quality, and impact of blocking issues are also useful, @djaa_dja
  32. 32. Implementing a Virtual Kanban System Do not copy an existing (virtual) kanban system! Each system must be designed from 1st principles using the system thinking approach to implementing kanban A study of demand including business risks & capability is essential to design an appropriate (virtual) kanban system for any given knowledge work service, @djaa_dja
  33. 33. Reminder… The Kanban Method is not…. A project management or software development lifecycle process Nor, does it encourage a processcentric approach to improvement! You must “kanbanize” your existing processes and workflows!, @djaa_dja
  34. 34. Kanban Kata, @djaa_dja
  35. 35. Feedback Loops The Kanban Kata Operations Review Improvement Kata Standup Meeting, @djaa_dja
  36. 36. Standup Meeting Disciplined conduct and acts of leadership lead to improvement opportunities Improvement discussions & process evolution happen at after meetings, @djaa_dja
  37. 37. Improvement Kata A mentor-mentee relationship Usually (but not always) between a superior and a sub-ordinate A focused discussion about system capability Definition of target conditions or desired outcomes Agreement upon counter-measures – actions taken to improve capability – resulting in process evolution, @djaa_dja
  38. 38. Operations Review Monthly meeting Disciplined review of demand and capability for each kanban system Provides system of systems view and understanding Kanban system design changes & process evolution suggested by attendees, @djaa_dja
  39. 39. 6 Practices for Evolutionary DNA The More Specific Version Visualize work, workflow & business risks (using large physical or electronic boards in communal spaces) Implement Virtual Kanban Systems Manage Flow Make Policies Explicit Implement Kanban Kata Educate your workforce to enable collaborative evolution of policies & ways of working, @djaa_dja
  40. 40. Scaling out across an organization, @djaa_dja
  41. 41. Treat each service separately Demand Observed Capability Demand Observed Capability Demand Observed Capability, @djaa_dja
  42. 42. Some systems have dependencies on others Demand Observed Capability Demand Observed Capability Demand Observed Capability, @djaa_dja
  43. 43. Organizational Improvements Emerge, @djaa_dja
  44. 44. Scaling Kanban Each Kanban System is designed from first principles around a specific service Scale out in a service-oriented fashion Do not attempt to design a grand solution at enterprise scale The Kanban Kata are essential! Allow a better system of systems to emerge over time. Let evolution work!, @djaa_dja
  45. 45. Scaling up and down (big projects, portfolios & personal work), @djaa_dja
  46. 46. Summary of Benefits, @djaa_dja
  47. 47. Collaboration Benefits Shared language for improved collaboration Shared understanding of dynamics of flow Emotional engagement through visualization and tactile nature of boards Greater empowerment (without loss of control), @djaa_dja
  48. 48. Tangible Business Benefits Improved predictability of lead time and delivery rate Reduced rework Improved risk management Improved agility Improved governance, @djaa_dja
  49. 49. Organizational Benefits Improved trust and organizational social capital Improved organizational maturity Emergence of systems thinking Management focused on system capability through policy definition Organizational Adaptability (to shifts in demand and business risks under management), @djaa_dja
  50. 50. Change Management Benefits Significantly reduced resistance to change Processes uniquely tailored to business environment and risk under management Evolutionary changes reduce impact during change and lower risk of failure Change led from the middle and enacted by the workforce. Reduced need for coaching and process specialists, @djaa_dja
  51. 51. Kanban Improves Agility • Lead times gradually reduce • Predictability of delivery gradually improves • Organizational social capital improves • Governance, risk management are improved • Empowerment without loss of control • Improves are often dramatic! • 700% increase in delivery rate at BBC • On-time delivery often greater than 90% • Delivery times often reduced by up to 90%, @djaa_dja
  52. 52. Learn More • For best results, work with an accredited trainer (AKT) or credentialed Kanban Coaching Professional (KCP) • Part of a global conference series promoting Kanban and related concepts for improved business performance, @djaa_dja
  53. 53. Thank you!, @djaa_dja
  54. 54. About David Anderson is a thought leader in managing effective software teams. He leads a consulting, training and publishing and event planning business dedicated to developing, promoting and implementing sustainable evolutionary approaches for management of knowledge workers. He has 30 years experience in the high technology industry starting with computer games in the early 1980’s. He has led software teams delivering superior productivity and quality using innovative agile methods at large companies such as Sprint and Motorola. David is the pioneer of the Kanban Method an agile and evolutionary approach to change. His latest book, published in June 2012, is, Lessons in Agile Management – On the Road to Kanban. David is a founder of the Lean-Kanban University Inc., a business dedicated to assuring quality of training in Lean and Kanban for knowledge workers throughout the world., @djaa_dja
  55. 55. Acknowledgements Hakan Forss of Avega Group in Stockholm has been instrumental in defining the Kanban Kata and evangelizing its importance as part of a Kaizen culture. Real options & the optimal exercise point as an improvement over “last responsible moment” emerged from discussions with Chris Matts, Olav Maassen and Julian Everett around 2009. The inherent need for evolutionary capability that enables organizational adaptation was inspired by the work of Dave Snowden., @djaa_dja
  56. 56. David J Anderson & Associates, Inc., @djaa_dja
  57. 57. Appendix, @djaa_dja
  58. 58., @djaa_dja Fixed Date Intangible Standard Expedite Example Distributions
  59. 59., @djaa_dja