WorksheetsComplexity theory and safe-to-fail
Total questions: 9
Worksheet time: 9mins
The complex domain is categorised by
emergence - new things emerging from the pattern that we might not have anticipated
irreducibility - when you zoom in or out on the system, it doesn't lose complexity
networks of interactions - individuals in the network are connected across multiple parts of the system
all of the above
COVID-19 with its exponential interactions and unpredictability is best represented by
the simple domain
the complicated domain
the complex domain
the chaotic domain
Leaders working in the complex domain are dealing with greater
unpredictability
stability
randomness
patterns and trends
Best practice is most suited to circumstances where
we know that things will happen again and again
there is a clear cause and effect relationship
everyone can agree on the cause and effect relationship
all of the above
Experimentation, prototyping and iteration is suited to complexity because it allows us to
Quickly learn from mistakes and successes in order to respond
Implement new initiatives
Attempt to control the situation
None of the above
Conducting a safe-to-fail experiment is most like
Poking a dog with a stick to see what happens
Dropping a water balloon from a 2m height
Kicking a stone
Spraying paint from a can in a closed room
What is the goal of a safe-to-fail experiment?
Learn from how the system responds to a nudge
Overhaul the whole system
Exercise a measure of control
Use it to plan a new initiative
Safe-to-fail experiments need
Permission
Risk
A roll out plan
To be scalable if successful
Safe-to-fail experiments work best when
There is only one experiment running at a time
They have clear action plans with multiple steps
You stick to your course of action
You adapt based on new learning
