FOR LEADERS OF CRITICAL PATHWAYS
Proof before you commit.
Boole provides external feasibility audits to establish whether your system can mathematically deliver the required standard, so leaders can commit with proof rather than trial and error.
Research consistently shows that fewer than one in four major improvement programmes deliver sustained results. [1] The issue is not effort or poor implementation — it is that the system’s constraint has not been correctly diagnosed.
The constraint standard instruments cannot find
Every standard management instrument deployed to diagnose operational pathway failure surfaces the same information: performance issues are due to capacity not meeting demand. The visible answer is always the same: add capacity or redesign the pathway to manage demand. But rarely are these interventions effective.
“Systems today are limited mainly by invisible policy constraints. We very rarely find organisations with a real capacity constraint, but rather, with devastating policy constraints.”
Eliyahu M. Goldratt, Theory of Constraints
When the root cause constraint is invisible, organisations deploy interventions to address the symptoms they can observe — more resource, improvement initiatives, service redesigns. Each response is rational, but when aimed at the wrong cause, the result is a Doom Loop:
When policies, or the combination of individually sound rules, make performance targets structurally unachievable, the result is what we call a Policy Knot: a configuration where no additional capacity or reduction in demand will close the gap.
Policy knots invisible to standard instruments operate in the Ultraviolet — the range of interaction complexity that no dashboard, KPI framework, or capacity model can detect. Boole exists to make Ultraviolet constraints visible and to establish the minimum intervention required to resolve the most complex knots.
What an assessment delivers
The specific constraint actually preventing performance
We determine whether the system is constrained by capacity, by policy interaction, or by a hybrid of the two. The answer changes what the decision should be.
A clear verdict: can this pathway meet its required standard
We establish whether the system can deliver the required standard under the current pathway design and policy configuration. A number, not a narrative.
The smallest change that resolves the constraint
If the system is infeasible, we identify the minimum necessary policy calibration, or resource increment, to ensure feasibility without compromising rules essential to governance and safety.
Evidence specifying the options for change and why
The decision shifts from “we have a plan” to “we have a verdict.” Every investment, regulatory, or governance decision that follows is made from a defensible, mathematically derived position.
A validated model of the system
Permanent access to the validated logic twin continues after the assessment, providing the capability to test how changes in policy would impact system performance.
Working with us
On technical rigour and sector insight
“The team’s skillset covers both data analytics and healthcare delivery, which is exceedingly rare. It is clear they know what the numbers actually mean in the healthcare context. They are not just making guesses.”
On creating an irrefutable evidence base
“By pulling together a solution that leverages the available data, it becomes an irrefutable source of truth. It provides great value by providing a context for our performance numbers which is otherwise very difficult to achieve.”
On clinical and operational credibility
“The solution takes some really quite complicated pathways and shows them in a variety of formats that make them easy to understand. It enables us to deepen our understanding and check the detail without being overwhelmed.”
How we work
Qualifying conversation.
No cost. No preparation required.A confidential discussion to establish whether a feasibility assessment is warranted. Boole works only where the method can genuinely help. If it can, we produce a proposal for Stage 2. If it cannot, we say so.
Observation study and baseline assessment.
Fixed fee, agreed in advance.An observation study maps the system under assessment. The physical pathway and its data are traced together and the resulting logic tree validated against thousands of cases. The study determines whether the pathway is capacity constrained, policy constrained, or both.
If the pathway is purely capacity constrained, the engagement closes here. You receive a robust, board-ready capacity and demand assessment specifying exactly what resource is required to meet the standard.
If the pathway is policy constrained — or if significant performance improvement is achievable through policy calibration — the study produces the evidence for this finding and the basis and costings for an optional Stage 3.
Option evaluation and decision support.
Value based fee agreed before work begins.The options for change are evaluated and costed. Boole works alongside the services until the chosen option is implemented and performance is within the expected range. Every investment, regulatory, or governance decision that follows is auditable and mathematically derived.
The fee for Stage 3 is calibrated against the expected value of the decisions it informs.
The value you can expect
The fee for full option evaluation and decision support stage is calibrated against the expected value of the decisions it informs. Enter the scale of the commitment under consideration.
Value of knowing before you commit
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Sensitivity (20% to 40% decision risk rate): — to —
Indicative fee range
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Our assessment fee is structured to deliver a minimum ten times return on its cost. The final price is established at scoping once the system parameters are confirmed.
Where the structure of a specific pathway warrants it, alternative fee arrangements can be discussed at the qualifying stage.
Before the next commitment is made, establish whether it can work.
- McKinsey Global Surveys on organisational transformation. The 26% figure is drawn from: Jacquemont D, Maor D, Reich A. How to beat the transformation odds. McKinsey Global Survey. April 2015 (survey data collected 2014; n= 1,946 executives): “just 26 percent of respondents say the transformations they’re most familiar with have been very or completely successful at both improving performance and equipping the organisation to sustain improvements over time.” The finding is consistent across multiple survey waves: Isern J, Meaney MC, Wilson S. Corporate transformation under pressure. McKinsey Quarterly. 2009 (origin of the consistent finding); Keller S, Meaney M, Pung C. What successful transformations share. McKinsey Global Survey. March 2010; and Bucy M, Schaninger B, VanAkin K, Weddle B. Losing from day one: why even successful transformations fall short. McKinsey Global Survey. December 2021: “the average success rate has remained persistently low… less than one-third.” All surveys available at: mckinsey.com/capabilities… ↑
- Goldratt EM. Theory of Constraints. Great Barrington (MA): North River Press; 1990. ↑
- Collins J. Good to Great: Why Some Companies Make the Leap… and Others Don’t. New York: HarperBusiness; 2001. The Doom Loop diagram on this page is adapted from the flywheel and doom loop concept in Chapter 8: The Flywheel and the Doom Loop. ↑
- Deloitte. Global Transformation Survey. Deloitte Insights; 2024. The figure of 7.5% of annual operating cost as a proxy for transformation programme expenditure is derived from the average transformation spend reported across sectors. ↑