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Discovery Kanban @ LKSE15

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Discovery Kanban @ LKSE15

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All knowledge work requires a delicate and continuously shifting balance between delivery – exploiting existing knowledge – and discovery – exploring new knowledge. This need to balance discovery and delivery can be found across the entire innovation cycle: from technology innovation over performance and sustaining innovation to disruptive innovation. It has been a driving concern for specific approaches such as Lean Product and Process Development as well as The Kanban Method, as exemplified in examples such as: developing a new product that requires novel features (discovery) while at the same time managing the overall risk that is involved in developing those features (delivery); improving agility and predictability of an organization that may require substantial change (discovery) while at the same time keeping resistance to change under control (delivery); a startup that requires an initial focus on finding problem/solution fit or product market fit (discovery) but then needs to develop the organization to delivery at scale (delivery); etc.

In each of the examples above, too much emphasis on discovery may result in a disconnection with the past leading to resistance to change, increasing delivery risk, and non-adoption of innovation. Too little emphasis on discovery (and consequently too much emphasis on delivery) may lead to not being prepared for the future resulting in stagnation and the risk of being disrupted. Discovery Kanban systems are Kanban systems that help to balance discovery and delivery while moving from a mindset of episodic (one-off) innovation and change towards a culture of continuous innovation and change. Discovery Kanban systems work across the entire discovery cycle starting from pre-hypothesis moving into hypothesis validation and ending in post-hypothesis. In this presentation, we will discuss the different elements of Discovery Kanban, examples and underlying principles.

All knowledge work requires a delicate and continuously shifting balance between delivery – exploiting existing knowledge – and discovery – exploring new knowledge. This need to balance discovery and delivery can be found across the entire innovation cycle: from technology innovation over performance and sustaining innovation to disruptive innovation. It has been a driving concern for specific approaches such as Lean Product and Process Development as well as The Kanban Method, as exemplified in examples such as: developing a new product that requires novel features (discovery) while at the same time managing the overall risk that is involved in developing those features (delivery); improving agility and predictability of an organization that may require substantial change (discovery) while at the same time keeping resistance to change under control (delivery); a startup that requires an initial focus on finding problem/solution fit or product market fit (discovery) but then needs to develop the organization to delivery at scale (delivery); etc.

In each of the examples above, too much emphasis on discovery may result in a disconnection with the past leading to resistance to change, increasing delivery risk, and non-adoption of innovation. Too little emphasis on discovery (and consequently too much emphasis on delivery) may lead to not being prepared for the future resulting in stagnation and the risk of being disrupted. Discovery Kanban systems are Kanban systems that help to balance discovery and delivery while moving from a mindset of episodic (one-off) innovation and change towards a culture of continuous innovation and change. Discovery Kanban systems work across the entire discovery cycle starting from pre-hypothesis moving into hypothesis validation and ending in post-hypothesis. In this presentation, we will discuss the different elements of Discovery Kanban, examples and underlying principles.

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Discovery Kanban @ LKSE15

  1. 1. Discovery Kanban Patrick Steyaert
  2. 2. Knowledge work 3 Exploiting existing knowledge Exploring new knowledge Finding out which problems to solve and creating solutions for problems that have not been solved before Using past experience and knowledge to create solutions for known problems and situations Solving hard problems, including the problem of finding out what problems to solve (or opportunities to capture) Delivery Discovery Balancing Discovery and Delivery - © Patrick Steyaert, 2015
  3. 3. Software development is knowledge work Ref.: Allistair Cockburn 4 Users &
 Sponsors Testers Business
 Analysts Programmers UI 
 Designers Detailed decisions
 about function
 and data Decisions 
 about program
 structure Detailed
 decisions about
 external
 appearance Decisions 
 about function 
 and style Decisions 
 about system
 correctness The knowledge discovery process
  4. 4. §  Features §  Change requests §  Fixes to production defects §  … Delivery 5 Balancing Discovery and Delivery - © Patrick Steyaert, 2015
  5. 5. Discovery Agile Business Requirements training - © Patrick Steyaert, 2015 Viability Desirability Feasibility 6
  6. 6. §  In the ideal world, work flows with little friction §  In the “messy” real world there are all kinds of friction: silos, specialists, communication, resistance to change, … § Kanban is a way of dealing with the present (friction in your current reality) and connecting with the future (flow in the ideal) Kanban helps to deal with the real world 7 Balancing Discovery and Delivery - © Patrick Steyaert, 2015
  7. 7. Continuous change and innovation 8 Future Present Dealing with the present & connecting with the future Digital Customer value Networked Pull Analog Shareholder value Hierarchical Push Balancing Discovery and Delivery - © Patrick Steyaert, 2015
  8. 8. Shared visual understanding 9 Balancing Discovery and Delivery - © Patrick Steyaert, 2015
  9. 9. Kanban principles and practices 10 Ideas Reday for Dev Development Testing Ready for UAT Done ongoing done 5 ∞ Abandoned 5 3 A user story A bug A user story A user story A user story A user story A user story A user story A user story A bugA user story A user story A user story A user story •  Visualize •  Limit WIP •  Manage Flow •  Make Process Policies Explicit •  Implement Feedback Loops •  Improve Collaboratively, Evolve Experimentally (using models/ scientific method) •  Start with what you do now •  Agree to pursue incremental, evolutionary change •  Initially, respect current roles, responsibilities & job titles Core practicesFoundational principles
  10. 10. Ideas Ready for Dev Development Testing Ready for UAT Done ongoing done 5 ∞ Abandoned 5 3 A user story A user story A user story A user story A user story A user story A user story A user story A user story A user story A user story A user story A user story A user story A user story A user story A user story Delivery kanban - focus on “work”? 11 A user story WORK items Limit WORK in progress
  11. 11. 12 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Knowledge work (at scale) information decisions options More than work alone! How does this affect flow? Delivery Discovery
  12. 12. ExampleDiscoveryKanban 13 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Idea (>15) Concept (>10) Specification (>6) Fragmented ideas Upstream (option) Kanban - discovery precedes delivery - Coherent specifications
  13. 13. Options, selection and commitment 14 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Options Selection Commitment Convergent process
  14. 14. Morethanjustvisualization 15 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Idea (>15) Concept (>10) Specification (>6) Minimum limits to ensure sufficient options to downstream process Upstream (option) Kanban - discovery precedes delivery - FLOW
  15. 15. Managerial approach Given goal Availablemeans M1 M2 M3 M4 M5 Selecting between given means to achieve a pre-determined goal Balancing Discovery and Delivery - © Patrick Steyaert, 2015 16 WHAT HOW WHY
  16. 16. 17 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 “Why”, “What” and “How” can be known upfront Discovery precedes delivery Post-Hypothesis (known known)
  17. 17. Not all knowledge work is alike 18 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Post-Hypothesis Known known “Why”, “What”, “How” can be known upfront Discovery precedes delivery Hypothesis Known unknown “Why” is defined “how” is discovered Discovery and delivery alternate Pre-hypothesis Unknown unknown “What” is known; “why” and “how” are discovered Delivery precedes discovery Hidden assumptions Unknown known Observation as a basis
  18. 18. Balancing Discovery and Delivery - © Patrick Steyaert, 2015 19 “why” is defined “how” is discovered Discovery and delivery alternate Hypothesis (known unknown)
  19. 19. Idealistic approach VisionNow Next target “How” is discovered “Why” is defined In the idealistic approach, the leaders of a project set out an ideal future state that they wish to achieve, identify the gap between the ideal and perception of the present, and seek to close it. Dave Snowden 20 Balancing Discovery and Delivery - © Patrick Steyaert, 2015
  20. 20. Applying the scientific method Design and run experiment (DO) Create hypothesis (PLAN) Study results (CHECK) Evolve model (ADJUST) Agile Business Requirements training - © Patrick Steyaert, 2015 21
  21. 21. ExampleDiscoveryKanban 22 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Backlog Plan Do Adjust 3 2 3 Experiment Kanban (1) - Discovery and delivery alternate - Check 2 FLOW Hypotheses Limit experiments in progress Explicit feedback loop (internal or external)
  22. 22. Validated learning 23 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Ideas Build Product Measure Data Learn
  23. 23. Hypothesis 24 We believe that <Building this feature> <for these people> Will achieve <this outcome> We will know we are successful when we see <this signal or measurable result> Balancing Discovery and Delivery - © Patrick Steyaert, 2015
  24. 24. ExampleDiscoveryKanban 25 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Backlog Build Measure Learn 4 3 2 3 Hypothesis to be validated Experiment Kanban (2) - Discovery and delivery alternate - Options that can be exercised Limit the number of un-validated assumptions
  25. 25. Creating options 26 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Exercised Option Hypothesis Option creation exercising Down paymentHouse price will go up House MVP (option to pivot or persevere) User need Full product development Divergent process
  26. 26. Balancing Discovery and Delivery - © Patrick Steyaert, 2015 27 “what” is known “why” and “how” are discovered Delivery precedes discovery Pre-Hypothesis (unknown unknown)
  27. 27. Entrepreneurial approach 28 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Given means Imagine possible new ends given available means E1 E2 E3 E4 Imagined ends M1 M2 M3 M4 M5 WHAT HOW WHY
  28. 28. § Focus on what you can do and do it, without worrying much about what you ought to do §  Begin with who you are, what you know, whom you know §  Immediately start taking action and interaction with other people § Goals and network concurrently converge §  People you interact with self-select into the process §  Each commitment results in new means and goals §  As resources accumulate in the growing network, constraints begin to accrete that reduce possible changes in future goals and restrict who may further join the network Effectuation 29 Balancing Discovery and Delivery - © Patrick Steyaert, 2015
  29. 29. ExampleDiscoveryKanban 30 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Backlog Plan Do Adjust 4 3 2 3 Actions Action Kanban - Delivery precedes discovery - Check 2 Limit the number of actions in progress Not really a feedback loop, just verification It looks like PDCA, but it is not really PDCA!
  30. 30. Balancing Discovery and Delivery - © Patrick Steyaert, 2015 31 Observations as a basis for discovery Hidden assumptions (unknown known)
  31. 31. Path dependence The set of decisions one faces for any given circumstance is limited by the decisions one has made in the past, even though past circumstances may no longer be relevant. 32 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Options Emerging path Lock in Varietyofoptions (managerialflexibility) Critical juncture Definition from Praeger, Dave. Our Love Of Sewers: A Lesson in Path Dependence Pre-hypothesis Hypothesis Post-hypothesis
  32. 32. Weak signals – ugly babies & invisible gorillas 33 Every movie the company makes starts out "ugly”; Ill-defined ideas need protection the most, lest they die too young. - Pixar president Ed Catmull Our minds don't work the way we think they do. We think we see ourselves and the world as they really are, but we're actually missing a whole lot. - Christopher Chabris and Daniel Simons Balancing Discovery and Delivery - © Patrick Steyaert, 2015
  33. 33. Observe-Orient-Decide-Act Boyd’s strategic decision making loop Observe Orient Decide Act
  34. 34. ExampleDiscoveryKanban 35 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Backlog Observe Orient Act 4 3 2 3 Orientation Kanban - Observation as a basis for discovery - Decide 2 Strategic decision cycle: Observe-Orient-Decide-Act FLOW Limit the number of decisions in progress Observations (decisions to be made)
  35. 35. All together now – the discovery cycle 36 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 Upstream (option) kanban Experiment kanban Experiment Vision Known unknown Constraints Trigger Unknown unknown Orientation kanban Action kanban Model Options Known known Commitment Weak signal Unknown known Orientation
  36. 36. All together now – Program Management Kanban Visualize “actions” and “experiments” Visualize “decisions to be made” Balancing Discovery and Delivery - © Patrick Steyaert, 2015 37
  37. 37. >4 5 4 >4 5 4 Visualize “commitments” Visualize “options” All together now – Product Management Kanban Balancing Discovery and Delivery - © Patrick Steyaert, 2015 38
  38. 38. Visualizing knowledge work 39 Balancing Discovery and Delivery - © Patrick Steyaert, 2015 *oobeya = project room Options Commitments Observations Actions Experiments
  39. 39. Not all Kanban is alike Delivery Kanban Discovery Kanban Visualize work Limit work in progress
 Manage flow of work Organize feedback loops
 Evolve experimentally Visualize decisions and options Limit unvalidated assumptions and decisions in progress Manage flow of decisions and options Explicit feedback loops, customer feedback loops Mixed change
  40. 40. Not all Kanban is alike Delivery kanban Discovery kanban Improving fitness for purpose of service delivery Improving the fitness for purpose of organizations in a continuously changing landscape Demand is established and there is more demand than capability Not just delivery against established demand but also dealing with uncertain demand
  41. 41. @PatrickSteyaert patrick.steyaert@okaloa.com
  42. 42. References 43 Balancing Discovery and Delivery - © Patrick Steyaert, 2015

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