Quality ≠ Good

This article is the first in a series on transformation and is based on my experiences in my 20 years working with organisations to implement strategy and transformatibased on patterns I see across sectors, not commentary on any one institution.

It is difficult today to think of a sector which is not in disruption and undergoing transformation. Organisations who are lucky enough to have the resource to transform and innovate can avoid implementing cost reduction measures. Many are not so fortunate. Traditional approaches: workforce reductions, budget cuts, or “vertical cuts” (a term which I recently heard at a conference) may deliver short-term savings, but risk embedding inefficiencies that undermine long-term sustainability.

The temptation is understandable. Leaders under pressure often reach for visible, immediate measures. But these approaches carry risks that compound over time, because they misunderstand the nature of organisations themselves.

Underpinning many transformation programmes is an implicit but flawed assumption: that leaders sometimes retain resources out of comfort or inertia, and that transforming simply means reallocating resource after encouraging people to give it up. This assumption is flawed for two key reasons:

Taken together, these two realities make traditional cost cutting risky.⁴ Costs do not disappear; they shift. Dependencies remain hidden, duplication persists, and effort leaks into workarounds. Transformation is therefore not about removing people, but about surfacing and redesigning the work itself deliberately and at the system level.

A recent EY study¹ found that less than half of employees (c. 41%) understand and believe in their organisation’s transformation vision and strategy. This highlights a common mismatch between what is labelled transformational versus what actually delivers long-term, sustainable change. Many transformation initiatives add new tools, processes or ways of working, but that does not always equal rising quality in the way customers or stakeholders experience it.

At the heart of this mismatch is a confusion of terms. “Better” does not automatically mean “quality.” Something new or faster may seem like progress, but unless it aligns with what matters to those served, it may not deliver what “quality” is meant to convey.

Crosby in his seminal text ‘Quality is Free: The Art of Making Quality Certain’² defines quality as:

If you were to ask most people outside of technical fields what quality means, I suspect they would say "good". None of those words above say "good", they are the facets of what customers determine as being "good" (the semantic distinction is important here).

This difference sounds small, but foundational. “Good” is subjective. “Quality” is measurable. Customers determine “good” by how consistently, reliably, and fairly their needs are met.

But meeting standards is not the same as delivering quality. Organisations often mistake compliance for quality — allowing legacy policies, outdated standard operating procedures, or redundant requirements to masquerade as value. These consume energy, create friction, and in fact reduce quality. The task of transformation is to distinguish value-creating standards from redundant requirements.

Extending the thinking a bit further in this context. Operational efficiency is about how we meet current customer needs. Strategy is about how we meet future customers’ future needs. Transformation is therefore about how we adjust our system to meet both current and future customer needs, and importantly no other needs, using less resource, in aggregate, than we use today. This is how organisations achieve greater revenue, margin and impact.

Emerging technologies, particularly horizontal AI (tools and systems that cut across functions, not just embedded in one department), make this system-wide view more possible than before³. AI can cut across silos — connecting datasets, surfacing hidden dependencies, and exposing duplicated or redundant work. Instead of each department optimising in isolation, AI enables orchestration across the whole enterprise: work redesigned as part of a coherent system, not a patchwork of fixes.

Seen this way, transformation is not a euphemism for downsizing, nor a race to adopt shiny tools. It is a disciplined redesign of the organisation as a system, guided by properly defined quality: standards + customer expectations + removal of redundant requirements.