Proceed with greater confidence that the investment addresses the real constraint.
How I work
Start with the explanation.
Not the proposed
solution.
Most difficult health and care decisions arrive with a plausible explanation already attached.
More demand needs more capacity.
A delayed pathway needs another service.
A performance problem needs more activity.
A business case needs approval.
Sometimes that explanation is right.
Before recommending investment, redesign or additional capacity, I want to know whether it still holds up when the evidence across the whole system is brought together.
Before commitment
Good delivery cannot rescue
the wrong explanation.
A programme can open the beds, recruit the staff, launch the pathway and deliver the activity it promised.
The original pressure can still remain.
That is why I separate three questions:
- 01Did we correctly understand the cause?
- 02Will the proposed intervention actually change it?
- 03How will we know whether the system behaved differently afterwards?
Delivery tells us whether the intervention happened.
Evaluation tells us whether the system changed.
Questions I test
Six questions I test
before recommending change.
Every proposal arrives with a persuasive explanation.
Before recommending investment, redesign or additional capacity, I try to answer six questions.
If one remains unresolved, the intervention may still deliver activity without changing the pattern it was funded to improve.
Are we seeing the whole picture?+
Start with what is reported, then test what is missing.
Activity data reflects what the system has chosen, or managed, to measure. Reconcile definitions, pathways and operational evidence before treating the visible position as the whole problem.
Will more activity actually change the outcome?+
More assessments, clinics or visits prove that work increased.
They do not prove the system behaves differently.
Test the causal link between additional activity and the pressure the proposal is intended to improve.
What is really driving the pressure?+
Waiting lists, delayed discharge, workforce pressure and occupancy interact.
Test where the constraint sits and whether the proposed response will remove it or simply move pressure elsewhere.
How much capacity is actually usable?+
Commissioned, staffed and usable capacity are rarely the same thing.
Geography, workforce, dependency, access routes and pathway design determine whether theoretical provision can serve the people waiting today.
Which assumptions are carrying this business case?+
The arithmetic can be correct while the conclusion is wrong.
Identify the assumptions about demand, behaviour, productivity and flow that must hold, then stress-test the ones capable of changing the decision.
How will we know the system has genuinely changed?+
Delivery shows that beds opened, teams mobilised and milestones were achieved.
Define the evidence needed to show something harder: that the original pattern of pressure has genuinely changed.
When the answer feels plausible
Trust the hesitation.
Test the explanation.
Most executive teams do not lack information.
They already have dashboards, business cases, programme teams, recovery plans and preferred options.
The question is rarely whether enough work has been done.
It is whether the explanation behind the preferred option has been tested hard enough to justify committing scarce resources.
In practice
Independent challenge
should lead somewhere.
The aim is not to produce disagreement for its own sake.
It is to make the decision easier to defend by showing which assumptions are supported, which remain uncertain and what would need to change before proceeding.
What I may test
- demand and pathway evidence
- usable rather than theoretical capacity
- operating constraints
- workforce and productivity assumptions
- marginal benefit and opportunity cost
- business-case dependencies
- intended outcome and benefit measures
What leaders should leave with
- a clearer explanation of the problem
- the evidence supporting it
- explicit assumptions and trade-offs
- clarity on what should happen next
- a way to know whether the intervention worked
Before you fund the solution
Bring me the proposal
you're expected to approve.
The strongest investment decisions still make sense after someone has tried to prove them wrong.
We'll test whether the explanation is strong enough to justify the decision.
Discovering that before committing resources is almost always the less expensive outcome.