Cynefin sensemaking framework and usage examples
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Transcript of Cynefin sensemaking framework and usage examples
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CYNEFIN SENSE-MAKING FRAMEWORK AND USAGE EXAMPLES
Agile Practice23.12.2015
www.luxoft.com
Maksim Gaponov – Agile/Lean Coach
Experience
10+ years in IT. Developer background and management experience as a team lead, project manager, product manager and CTO. Worked both in large companies and smaller start-ups. Over 7 years of Agile experience, Maksim is an seasoned coach, trainer and speaker at various conferences, including AgileDays.
Certificates
§ Member of Scrum Alliance, Certified Scrum Product Owner
§ Member of International Consortium for Agile (ICAgile), ICAgile Certified Professional, ICP-Business Value Analysis, ICP-Agile Coaching, ICAgileaccredited trainer
§ Member of Scrum.org, Professional Scrum Master (PSM I)
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CYNEFIN SENSE-MAKING FRAMEWORK
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What is sense-making?
“Sense-making is how do we make sense of the world so we can act in it.
If you can't draw a framework on the back off a table napkin from memory it has little utility for sense-making”
Dave Snowden
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Let’s describe the current state of things fistrly
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Complex Adaptive Systems
w Understanding through constraints:
- Order: fully constrained; predictable & repeatable outcomes
- Chaos: random, unconstrained, difficult to create or sustain
- Complex: system partially constrains behaviour, but behaviour modifies constraint
w The inherent uncertainty of a complex systems means we have to navigate a fitness landscape of possibilities
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Let’s take away and map ordered ones
w Understanding through constraints:
- Order: fully constrained; predictable & repeatable outcomes
- Chaos: random, unconstrained, difficult to create or sustain
- Complex: system partially constrains behaviour, but behaviour modifies constraint
w The inherent uncertainty of a complex systems means we have to navigate a fitness landscape of possibilities
www.luxoft.com
Now let’s take away the chaotic ones
w Understanding through constraints:
- Order: fully constrained; predictable & repeatable outcomes
- Chaos: random, unconstrained, difficult to create or sustain
- Complex: system partially constrains behaviour, but behaviour modifies constraint
w The inherent uncertainty of a complex systems means we have to navigate a fitness landscape of possibilities
www.luxoft.com
Finally let’s take away the ones falling into complex description
w Understanding through constraints:
- Order: fully constrained; predictable & repeatable outcomes
- Chaos: random, unconstrained, difficult to create or sustain
- Complex: system partially constrains behaviour, but behaviour modifies constraint
w The inherent uncertainty of a complex systems means we have to navigate a fitness landscape of possibilities
www.luxoft.com
We’re spending most of our time in Complex domain
w Highly sensitive to small changes (weak signals too easily dismissed)
w Granularity, gradient & enabling constraints
w Proximity & connectivity are key
w Shift from fail-safe design to multiple contradictory safe-to-fail experiments to avoid premature convergence
w Avoid confusing correlation with causation or simulation with prediction
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Obvious domain
Nature
Known knowns
Familiar, certain, well worn pathways
Constraints self-evident to all
Stable within universal constraints
Self evident solutions
Response
Sense-Categorize-Respond
Ensure sound process in place
Monitor for noncompliance & deviance
Test for complacency
Protect some pet mavericks
Preparation
Watch for outliers
Usable process
Right support people for key staff
Automate, but no automata
Anonymous appeal/whistle blowers
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Complicated domain
Nature
Known unknowns
Ordered, predictable, forecastable
Constraints evident and enforceable
Stable within constraints
Evidence susceptible of analysis
Response
Sense-Analyze-Respond
Determine experts or process to resolve
Manage & enforce process
Monitor effectiveness of constraints
Focus on exploitation not exploration
Preparation
Right people & process, right time
Process engineering with feedback
Diversity of experts in network
Sound Analytical practice
Stand aside but stay in touch
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Chaotic domain
Nature
Unknowable unknowns
Temporary state - no time
No evidence of any constraint
High turbulence no patterns
Old certainties no longer apply
Response
Act-Sense-Respond
Speed of authoritative response vital
Follow and enforce heuristics
Focus on constraints not solution
Use the opportunity to innovate
Preparation
Establish heuristics & Parables
Human sensor networks
Crews as crisis management teams
Simulation games for key managers
Multi-perspective dissent feedback
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Complex domain
Nature
Unknown unknowns
Messily coherent, patterns discernible
Partial changing constraints
Flux within stabilities
Evidence supports contradiction
Response
Probe-Sense-Respond
Monitor safe-to fail experiments
All contradiction within heuristics
Flex constraints to manage emergence
Agility key to amplification/dampening
Preparation
Create time and space for reflection
Human sensor networks operational
Social network stimulation & the like to create networks
Scenario planning (inc. micro)
Build and monitor ‘requisite diversity’
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Making sense of the world to act in it
There are three basic types of system: ordered, complex and chaotic.
Complex systems have propensities and dispositions but no linear material cause
In Cynefin order is divided into ‘obvious’ & complicated and the fifth domain) disorder.
The boundary between Obvious and Chaotic is shown as a cliff, or a catastrophic failure arising from complacency.
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SPLITTING USER STORIES
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Using Cynefin for User Story splitting
w Obvious – Just build it. Or, if it’s too big, find all the stories, and do the most valuable ones first.
w Complicated – Find all the stories, and do the most valuable and/or most risky ones first.
w Complex – Don’t try to find all the stories. Find one or two that will provide some value and teach you something about the problem and solution, build those and use what you learn to find the rest.
w Chaotic – Put out the fire; splitting stories probably isn’t important right now.
w Disordered – Figure out which domain you’re in before splitting so you don’t take the wrong approach. Richard Lawrence, http://www.agileforall.com/2014/08/cynefin-and-story-splitting/
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RETROSPECTIVES
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Using Cynefin on Retrospectives
w Obvious – just implement these improvements, add them to working agreements
w Complicated – find experts in your environment or internal/external consultants, ask them to help you
w Complex – brainstorm a set of small and time-bound experiments, find a way to measure outcomes, implement them
w Chaotic – distribute knowledge and wait some time until the issue transitions into a complex domain
w Disordered – brake these down until they start falling into one of domains
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COLLABORATION WITH COMPANY ENVIRONMENT
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Interventions in the complex domain
w Each intervention should be
- coherent
- safe-to-fail
- Finely grained, tangible
w Overall the portfolio should contain
- some that are oblique in nature
- include “naive” approaches
- a few high risk/high return options
w Contradictions are good!
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Upcoming Agile Practice webinars
Metrics that bring valueJanuary 14, 2016Svetlana Mukhina
User Story CanvasJanuary 26, 2016Maksim Gaponov
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