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To Be Option A
To be Option B
SECTION 7
To-Be Process Models Options A&B
Option A Operational Quick Wins & Waste Elimination
Option A focuses on fixing the obvious first, removing friction, eliminating duplicate effort and giving
staff the information they already need but currently can’t access in a timely manner. Most interventions
require minimal new infrastructure and can be delivered within 618 months using existing vendor
ecosystems.
Guiding principle: Stop doing things badly before trying to do new things intelligently.
This guidance is designed to support – not prescribe – your process modelling work. Each set of points gives
you a way of thinking about your To-Be design and a set of critical questions your model must be capable of
answering. The answers themselves are for you to work out.
Option A
Quick wins & waste elimination
Your To-Be model should show how fixing the obvious friction points – without rebuilding the
whole system – produces measurable improvements for patients and staff. Think: same
actors, better tools and better information.
PROCESS DESIGN GUIDANCE
1 Start with the handover chain
Every time information moves from one actor to another in the As-Is model, ask: is that
handover currently manual, verbal or paper-based? For each one that is, your To-Be model
should show what replaces it and what the receiving actor now has available that they did
not have before.
What does the triage nurse know the moment the patient arrives, versus what they know
now?
2 Target duplicate effort first
Look for every place in the As-Is model where the same information is entered, recorded or
communicated more than once. Your To-Be model should eliminate each instance of
duplication – and show clearly which actor is freed from that task and what they do with the
recovered time.
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Where does data exist in one place but get manually re-created somewhere else?
3 Make waiting visible and time-bounded
Every waiting step in the As-Is model is currently invisible – no one is automatically alerted
when a threshold is breached. In your To-Be model, identify which waits can be eliminated
entirely and which must remain but should trigger an automatic notification when they
exceed an acceptable limit.
Who needs to know what, and by when, to stop a wait from becoming a crisis?
4 Keep existing swim lane actors but change what they see
Option A does not restructure roles or introduce new organisational actors. The same
people do the same jobs – but with better information at the right moment. Your model
should reflect this: same swim lanes, but with improved data flows and eliminated manual
steps within each lane.
What information would each actor need at each step to make a faster, better decision?
5 Show the cascade effect of each change
Many improvements in Option A have knock-on effects upstream and downstream. Fixing
one bottleneck relieves pressure elsewhere. Your model and written analysis should
explicitly trace these cascades showing how an improvement in one swim lane reduces
waste in another.
If the bed status update delay is eliminated, what else improves as a result?
MODELLING REMINDERS
Annotate each changed process step with what specifically has changed and why.
Where a manual step is replaced by a digital one, show the new data flow explicitly.
Where a step is eliminated entirely, document it – removed steps are as important as new ones.
Use consistent notation to distinguish new steps from retained steps from eliminated steps.
Every claim about time or quality improvement must be traceable to a specific process change
in your model.
QUESTIONS YOUR MODEL MUST BE ABLE TO ANSWER
Which of the identifies issues in the Issue Register does this option address – and which
does it leave unresolved?
Be systematic. Work through the register item by item.
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For each improvement, what is the minimum technology or process change required to
deliver it?
Simpler solutions are more credible. Avoid over-engineering.
What does a shift handover look like in your To-Be model compared to the As-Is?
Trace it step by step. What information is transferred, how, and by whom?
How does the ramp wait time reduce – trace the causal chain step by step.
The answer must be traceable through your process model, not asserted.
Option B
Strategic AI adoption targeting root causes
Your To-Be model should show how AI changes the fundamental information architecture of
the system not just how individual tasks are done better, but how the system as a whole
becomes capable of seeing, anticipating and coordinating in ways that are structurally
impossible today.
PROCESS DESIGN GUIDANCE
1 Identify the root causes first
Before designing any process change, clearly articulate what the root causes of the current
crisis are, not its symptoms. Your To-Be model should be designed around resolving those
root causes. Every AI intervention you include should map directly to at least one of them.
What structural conditions make the current crisis unavoidable, regardless of how hard
individuals work?
2 Distinguish AI-assisted from AI-automated
Not every step in your To-Be model should be automated. For each AI intervention, be
explicit about whether a human remains in the decision loop and why. Some decisions carry
clinical or ethical risk that makes full automation inappropriate. Your model should show
where the boundary is and how it is enforced.
For each AI-supported decision, who retains authority and what happens if they override the
AI recommendation?
3 Redesign the information architecture, not just the tasks
Option B is not Option A with more technology. The fundamental change is that information
flows across the system in real time and reaches decision-makers before they need to ask
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for it. Your model should show new data flows that do not exist in the As-Is model and
explain what decisions become possible as a result.
What decisions are currently impossible because information does not exist, is not shared, or
arrives too late?
4 Model the system across its full-time horizon
The scope of option B’s could operate ahead of real time, predicting demand, anticipating
bottlenecks, triggering actions before problems materialise. Your model could show how the
system behaves across different time horizons: 48 hours ahead, 4 hours ahead, and in the
moment. This temporal dimension is what separates strategic AI from operational
automation.
Which process steps in your model are reactive and which are proactive? What is the ratio,
and is it better than the As-Is?
5 Address the patient record problem explicitly
One of the most significant root causes in the As-Is model is that patient information does
not follow the patient across sites. Your To-Be model must show a specific solution to this
and be honest about its constraints. A full EPR replacement is a decade-long project. What
is a realistic, staged approach that delivers meaningful clinical benefit within your
implementation horizon?
What is the minimum viable patient record capability that would eliminate the most critical
information gaps in the As-Is model?
MODELLING REMINDERS
Option B may introduce new swim lane actors, AI platforms, centralised operations, community
care coordinators. Justify each new actor: what role do they play and why does the current
system have no equivalent?
Show where AI generates an output and a human acts on it, these are two distinct process
steps and must be modelled as such.
Do not assume the AI is always right. Your model should include exception handling: what
happens when AI output is wrong or unavailable?
Clearly distinguish which parts of Option B build on Option A foundations and which require
entirely new infrastructure.
QUESTIONS YOUR MODEL MUST BE ABLE TO ANSWER
Which root causes does this option resolve and which does it only partially address?
Be honest about limitations. No option resolves everything.
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Where does AI create new risks that did not exist in the As-Is model? How are they
mitigated?
Consider: algorithmic bias, system failure, data privacy, deskilling.
How does the system respond to a 30% surge in demand under Option B trace the
process from prediction to resource deployment.
This tests whether your model is genuinely predictive or just reactive with better tools.
What does Option B require that Option A does not – in terms of data, infrastructure,
governance and culture?
Honest assessment of requirements is more persuasive to executives than optimism.
Guidance that applies to both options
Anchor every claim in the
As-Is
Your As-Is model is your
baseline. Every improvement
claim in your To-Be must
reference a specific problem
identified in the As-Is not a
generic aspiration about what
technology can do.
Separate process from
technology
Be precise about which
changes are process redesign,
which are technology
enablement, and which require
both. Conflating the two
produces models that are hard
to evaluate and harder to
implement.
Account for the resistant
stakeholder
Consider the stakeholder most
likely to resist each change.
How does your model account
for their concerns? A model
that ignores implementation
reality is not a credible model.
