Cost Out vs Efficiency and the Genesis of Work

In the previous article in this series, I put forward the distinction between “good” (an arbitrary internal perception) and “quality” (what customers actually want). A similar distinction can also be drawn between “cost out” and “efficiency” terms which are often used interchangeably.

I recently released Transformation Sandbox; a small, playable simulation of system-level trade-offs. The underlying premise of simulation was that transformation begins not with structure or headcount, but with visibility of how work actually flows.

The real challenge is that most organisations lack that visibility. As an organisation ages, work emerges organically: shaped by legacy structures, inherited habits, and invisible dependencies. Leaders see costs, but not the system that creates them. Decisions made in isolation can feel efficient, yet quietly degrade performance elsewhere.

This is what makes vertical cuts (removal of teams or even whole departments) so deceptive. They look simple, even rational, but they target visible cost rather than systemic cause.

The danger is that cuts remove visible cost but leave invisible interdependencies intact. Leaders assume they are reducing expense, when in fact they are redistributing it; usually in ways that make other units less efficient.

As Harvard Business Review notes, “while layoffs can lead to short-term financial benefits, research shows just how much of an impact they can have on employee engagement, morale, and loyalty — and how long that negative impact can last.” (HBR, 2024)

The complexity of modern organisations means that work is largely not formally designed. It is typically inherited from the person who did the job before you and, if the organisation has recently been restructured, inherited from many people who did the jobs before you.

This inheritance creates opacity. Whilst it can be clear where a task originated, or why it continues, few do this for a whole organisation. The result is fragile processes: cut the wrong task, and workflows elsewhere collapse. Continue the wrong task, and cost is carried indefinitely.

Asking why we do this work is far more nuanced and useful than asking why we have this role. The former is much harder to answer. It is easier to point at a box on an organisation chart and ask whether it’s needed. Harder, but far more valuable, is to interrogate the work itself. Only then can costs be truly removed rather than displaced.

Think of an efficient unit within an organisation. Now imagine other units around it are cut, displacing tasks downstream. Suddenly the efficient unit is swamped, performing work it was never designed for. Its metrics worsen, not because it changed, but because the system did.

This is the real cost of cost out. They make balance sheets look cleaner for a moment, but they erode effectiveness elsewhere. Transformation cannot succeed unless it treats work as systemic, not siloed.

The better question isn’t “How do we reduce?” but instead:

Only when leaders can answer these can they claim to be transforming, rather than just cutting.

Most organisations cannot answer those questions easily because they lack visibility of the system itself. Work origins, dependencies, and flows are rarely documented in full - this is very expensive to do and is even more expensive to keep up to date. Until now.

This is where systems thinking provides the right lens — and where emerging technologies can act as enablers rather than replacements.

As CEO Netweavers frames it, “systems thinking is all about seeing the bigger picture — instead of focusing on isolated events or problems, it encourages leaders to examine how individual elements interact within a larger system.” (CEO Netweavers, 2025)

As we move into an age of agentic AI this presents both an necessity and a possibility for leaders to be able to:

What once required manual mapping exercises can now be illuminated through data, patterns, and machine learning. But only if you are using the right tools.

Seen this way, AI is not about automating tasks away. It is about orchestrating the organisation as an open system, making the invisible visible so leaders can redesign work deliberately, not blindly.

In Article 1, I argued that transformation should be defined by quality, not “good.” In this article, the focus has been on the genesis of work and the risks of vertical cuts.

In Article 3, I’ll look at how system-level visibility can evolve into system-level learning and what adaptive transformation looks like when human and machine intelligence start to co-design the organisation itself.