Concepts
The mental models behind StepChange: detect structural change, avoid tampering, and decide what to do next when outcomes don’t move.
Making the invisible visible
The symptom is visible. The cause is hidden. The constraint is structural. The contradiction is assumed away. Every great improvement framework is a different method for bridging that gap between what’s visible and what’s true.
Read the foundation concept →- Why nothing changes — the failure pattern behind repeated effort without structural improvement
- Types of measures — outcome vs process vs balancing; lead vs lag
- Understanding variation — patterns, signals and proportionate responses
- Joiner levels of fix — Level 1/2/3: the quickest predictor of whether an intervention will produce lasting change
- Necessary but not sufficient — why correct interventions still fail the sufficiency test
Use Interpreting your StepChange chart to check the result and choose a proportionate next step.
Three useful starting points
- Variation, demand and capacity — Can the system cope with the work? Include slack and flexibility when designing the change.
- Understanding variation — What is the pattern telling us? Common and special causes, tampering and misleading comparisons.
- Interpreting your StepChange chart — What might have changed, and what should we check next?
Why things fail
Why nothing changes
Failure patterns behind repeated effort without structural improvement.
The Joiner Triangle
Quality, Scientific Approach, All One Team — one interdependent system. Taken separately they are not as effective.
Joiner levels of fix
Level 1/2/3: the quickest predictor of lasting change.
Deming’s 14 Points
Operational prescriptions that follow from systems thinking and variation.
The compliance trap
Why measurement pressure often worsens the outcomes it measures.
The Innovator’s Dilemma
Why systems resist disruptive improvement from within.
Common traps
The don’t-do-this list, in one place.
Measurement & analysis
Types of measures
Outcome vs process vs balancing; lead vs lag indicators.
Understanding variation
Common and special causes, suitable charts, tampering and misleading comparisons.
Gaming the Measure
Deming’s Point 11 — why targets get gamed and the balancing measures defence. Goodhart’s Law in NHS practice.
Hawthorne Effect
Behaviour changes when people know they are being measured. Why observed improvement is not the same as structural improvement.
Behaviour over time
Patterns before data; archetypes and feedback loops.
Causal loop diagrams
Feedback structure behind persistent performance patterns.
Improvement method
Model for Improvement
Aim, measures, changes; PDSA as structured learning.
PDSA cycle
Prediction → test → study → adapt. Bootstrap CUSUM is the Study step.
Making the invisible visible
Why every improvement framework solves the same problem — and where Bootstrap CUSUM fits.
Constraints and bottlenecks
Follow the work, check four traps and test what is limiting the whole-system result.
Divergent and convergent thinking
The two-diamond approach, evaluation matrix, PICK, POWER — 3 hours to a testable plan.
Stratify, experiment, disaggregate
Joiner’s three strategies for improving a stable system. What to do instead of tampering.
Going to the Gemba
The visibility intervention — going to where the constraint lives with the authority to act on it immediately.
Visual Management
Making work visible vs making the constraint visible — the honest distinction that determines whether visual management produces change or records the problem.
Evaporating Cloud
Makes the structural contradiction keeping a constraint in place visible — then dissolves it by naming and questioning the assumption underneath.
Bright Spots
Positive deviance: find who is doing it better and understand why.
Root cause analysis
Fishbone diagrams and multi-factor cause mapping.
The 5 Whys
Linear causality tool for straightforward, single-chain problems.
The PICK model
Impact vs effort prioritisation before choosing what to work on.
Systems & constraints
Theory of Constraints
Five focusing steps for improving the whole system—not just local utilisation.
Necessary but not sufficient
Why correct interventions still fail the sufficiency test — and how Bootstrap CUSUM confirms it.
Systems thinking & silos
Why component optimisation harms the whole system.
Failure demand
Demand created by system failure and rework — the hidden load.
Focus & prioritisation
How to choose where to act when everything feels urgent.
Variation, demand and capacity
Queues, utilisation, slack and flexibility—with Ashby’s Law as optional background.
Run the analyser, then check the result and choose a proportionate response. The chart does not identify the cause or determine the action by itself.
Interpret your StepChange chart →