"Turn and face the strange." Over the last decade I have been part of some significant transformation programmes — from junior days frantically taking meeting notes, to more recent years leading large multi-million pound portfolios. Technology rolled out during Covid that kept clinicians connected to patients. Digital tools deployed across Justice estates to reduce reoffending rates. Cancer systems using prevention analytics to identify citizens at stage 1 or 2 before a terminal diagnosis hits a family.

And yet it is hard not to sit with a nagging question: why does it all take so long?

Humans Have Always Adapted — When They Had To

Adapting to change is not new. Consider our ancestors, around 40,000 years ago. Communities that survived were the ones that changed fast. There were no steering groups, stakeholder engagement plans, or six-month discovery phases. There was a problem and an immediate response.

Fast forward to early 2020. Within weeks of a novel virus bringing the world to a standstill, we had national testing infrastructure, repurposed manufacturing lines, and vaccine candidates in development at a speed the scientific community itself found difficult to believe. When survival is on the line, we act.

The problem is that most change initiatives today do not feel like survival. So we default to something far more comfortable: over-analysis, over-consulting, and a prolonged fear of what might happen if we say or do the wrong thing.

"Losses loom larger than gains." — Kahneman and Tversky

In a change context, the people hesitating are not necessarily being obstructive — they are being entirely human. Understanding that does not make slow change acceptable, but it does explain why the default setting in most organisations is to keep thinking rather than start doing.

Technical Problems vs. Adaptive Challenges

Ronald Heifetz at Harvard draws a useful distinction between technical problems and adaptive challenges — where people have to shift their behaviours, beliefs, and ways of working.

"The most common cause of failure in leadership is treating adaptive challenges as if they were technical problems." — Ronald Heifetz

Most transformation programmes do exactly that. They apply process and governance to something that fundamentally requires human change. The result is a programme that looks busy while real impact moves far too slowly.

Who to Involve and When

Not everyone needs to know everything. Announcing every potential shift before anything is confirmed breeds change fatigue and makes people switch off long before anything happens. But for those directly affected, presenting them with a finished answer is a fast track to failure. Building alongside rather than delivering at them is the difference between change that sticks and change that generates resentment.

Five Things That Actually Work

Find the informal leaders, not the formal ones. Every organisation has people who others actually listen to — rarely those with the biggest job titles. Get them in the room early and genuinely involve them. If they are with you, the rest tends to follow.

Name the thing nobody is saying. There is almost always an elephant in the room — a redundancy everyone speculates over, a leader who caused the problem, a system nobody believes will work. Naming it out loud before someone else does is an act of trust.

Find the single narrative that unites the room. Find the outcome so self-evidently positive that nobody can deny it, name it clearly, and make it the thing every decision gets measured against.

Protect the first small win ferociously. Early momentum is fragile. The first visible proof that something is working — however small — is worth more than any strategy document. People follow evidence far more readily than they follow plans.

Boredom is a warning sign. When a transformation programme stops generating disagreement, it has usually stopped generating progress. If everyone in the room is nodding, someone has stopped telling the truth.

What We Actually Need

We need organisations where people at every level feel equipped and empowered to spot what is not working, say so, and play their part in fixing it. Curious, adaptable, and willing to try, fail, and try again. That is not a recruited personality type — it is a psychologically safe culture you have to build deliberately.

Change does not have to be as complicated as we make it. Understand the problem clearly, build a view quickly, and go. Adjust as you learn, and keep people with you.

Remember the organisations that hesitated when the internet became mainstream? The ones that treated email as informal, websites as optional, and online commerce as a fad. Their caution sounded reasonable. The organisations that pulled ahead were not reckless — they simply recognised that new tools change the shape of what is possible and moved early enough to benefit.

A Real World Example: UPS and Early Adoption

Long before AI became a mainstream talking point, UPS invested heavily in advanced optimisation tools. In the early 2000s, UPS developed ORION (On-Road Integrated Optimisation and Navigation), a system using algorithms to optimise delivery routes. The results: millions of gallons of fuel saved annually, reduced emissions, faster delivery times, and lower operating costs. Importantly, ORION did not replace drivers. It gave them a better starting point.

Effective organisations have always had one thing in common: they adopt useful tools earlier than the rest. Not because they chase novelty, but because they understand leverage.

Going Further, Faster Is Not Cheating

Using AI tools does not remove thinking from the process — it reallocates it. Instead of spending time on blank-page paralysis, repetitive drafting, or manual synthesis, teams can focus on judgment, direction, creativity, and decision-making. The parts humans are actually best at.

Strong organisations do not win by refusing tools that exist. They win by playing the cards available in their hand, and playing them well. The work still demands clarity of thought, conviction, and accountability. AI simply reduces the friction between intent and execution.

AI as a Force Multiplier, Not a Replacement

The most effective use of AI is not full automation — it is augmentation. AI can help turn rough notes into structured narratives, surface patterns humans might miss, accelerate research and ideation, and reduce friction in everyday workflows. What it cannot do is set intent, values, or direction. That responsibility still sits with people.

Introducing AI Without Chasing the Hype

The biggest mistake organisations make with AI is not resistance — it is uncritical enthusiasm. Smart organisations do not adopt tools because they are fashionable. AI should be approached the same way: not as a headline, but as an opportunity to remove friction and increase leverage.

That starts with the work, not the tool. Before asking which AI to use, it is worth asking where the organisation is slow, repetitive, or constrained today. The best early use cases are rarely flashy — they are the processes people quietly dread but accept as necessary.

Pilot tools in contained environments, let teams test and refine, and scale only once value is clear. Adoption sticks best when it is opt-in rather than imposed, when people feel supported rather than replaced. Humans must remain firmly in the loop. Decisions, accountability, and final judgment must remain human-led.

The Real Risk Is Standing Still

Years from now, no one will be asking whether organisations used AI tools. They will be asking whether they used them well. The difference will come down to intent, judgment, and how thoughtfully the tools were integrated into human-led work. Playing the cards available in your hand is not cheating. The real risk is standing still while everyone else learns.

The Flywheel Effect, introduced by Jim Collins, captures a truth about how organisations achieve lasting success. It is the idea that exceptional performance does not come from one hero-like action or bold initiative, but from the cumulative impact of consistent, disciplined effort. Like pushing a massive flywheel, each steady push builds momentum until it revolves under its own force.

At its core, the Flywheel Effect rejects the myth of a quick fix. Instead, it promotes the power of compounded progress: the steady rhythm of behaviours, rituals, and habits that create a self-reinforcing cycle of success. It resonates with both effective organisations and mission-driven public sector bodies — though the latter often face greater challenges in maintaining momentum amid constant change.

"Greatness is not a function of circumstance. Greatness, it turns out, is largely a matter of conscious choice and discipline." — Jim Collins, Good to Great

Turning the Flywheel

In Collins' research, companies that transitioned from good to great did not rely on one defining moment or a single strategy. Rather, they committed to a clear purpose, disciplined people, and consistent actions — even when the payoff was not immediate. Each disciplined act was a turn of the flywheel, adding energy and pace. Over time, those small, aligned actions produced exponential performance gains.

Applied to organisational culture, the Flywheel Effect reinforces that the right behaviours, repeated consistently, build cultural gravity. When everyone pushes in the same direction — leaders modelling desired behaviours, teams aligning around shared values, and systems reinforcing them — the culture begins to move forward almost naturally.

The Flywheel in Action

Consider Amazon. Jeff Bezos famously designed the "Amazon Flywheel" to show how the company's ecosystem worked: lower prices lead to more customer visits; more customers attract more sellers; more sellers expand selection; greater selection improves customer experience — which feeds back into growth. Each element strengthens the others, creating a virtuous cycle.

Across public sector organisations, similar patterns emerge where sustained, incremental improvement has been prioritised over one-off initiatives. Small, repeatable habits — regular team huddles, short reflection sessions, peer learning forums — steadily build trust, alignment, and performance. These micro-actions compound over time, shaping stronger collaboration, innovation, and service outcomes.

Practical Steps to Turn Your Flywheel

Define your flywheel. Identify four or five interconnected elements that drive your organisation's success. Make the cycle explicit and visible.

Start small, stay consistent. Choose a few non-negotiable habits and protect them: daily check-ins, monthly reflection sessions, consistent recognition of desired behaviours.

Measure progress, not perfection. Track momentum through small wins and early indicators. The goal is to show movement, not mastery.

Empower champions. Identify people who naturally model the desired culture. Give them autonomy and celebrate their impact.

Communicate relentlessly. Keep reinforcing the narrative of progress and use storytelling to make cultural momentum tangible.

Final Thought

The Flywheel Effect is less about speed and more about direction and discipline. Sustainable performance in complex, changing environments comes not from doing everything at once, but from doing the right things consistently. Start small. Stay consistent. Protect the habits that matter. Over time, those steady pushes will generate their own energy.

Urgent and emergency care sits at the most visible and pressurised point of the NHS. When triage fails, the consequences are immediate and serious. When it works, the whole system breathes easier. This engagement was about making it work better, across multiple sites, under significant operational pressure.

The Challenge

Triage inconsistency across sites was creating unpredictable patient flow, extended waits and avoidable escalations. The challenge was not a lack of clinical expertise. It was a lack of shared process, clear accountability and a way of embedding change that would hold under the daily pressures of an emergency environment.

What We Did

We worked embedded within NHS England teams to redesign the triage pathway from the ground up, co-designing with clinical leads, operational managers and frontline staff. We built a programme architecture that could flex across different site contexts while maintaining a consistent core. We ran rapid pilots, used real-time data to test impact, and built the change management infrastructure needed to scale what worked.

Critically, we did not disappear after the design phase. We stayed through implementation, troubleshooting and embedding, until the new pathways were genuinely operating in practice rather than just on paper.

The Outcome

Measurable reduction in average triage-to-treatment times across pilot sites. Improved consistency in triage decision-making. A change model that the system could extend independently. And a team that owned the change, not just inherited it.

Scaling a digital health business is a different challenge to building one. The skills, structures and ways of working that got you to a certain size become the things holding you back. This engagement was about helping a high-growth healthtech company make the transition from early-stage startup to credible, scalable enterprise.

The Challenge

The business had strong clinical credibility, a growing customer base and a leadership team that had moved fast and built something genuinely valuable. What it lacked was the commercial infrastructure, strategic clarity and governance architecture needed to scale further, particularly into larger NHS contracts and international markets.

What We Did

We worked at board level and alongside the executive team to sharpen commercial strategy, clarify the business model and position the company for the next stage of investment. We supported investor readiness work, helped structure the commercial pipeline and advised on the organisational design changes needed to support scale without losing the culture that had made the business successful.

We also supported the leadership team through some of the harder conversations that come with rapid growth: how to evolve roles, how to build capability without losing agility, and how to maintain a clear sense of direction when everything is moving fast.

The Outcome

A clearer strategic narrative, a more structured commercial approach, and a leadership team better equipped to manage scale. The business went on to secure significant new contracts and a further funding round.

Digital transformation in large public sector organisations is not primarily a technology problem. It is a workforce problem. The technology can be procured, installed and switched on. What takes far longer, and fails far more often, is changing how thousands of people work, what they are expected to do, and how they are supported to do it differently.

The Challenge

A national public sector organisation was mid-way through a major digital change programme when it became clear that the workforce strategy had not kept pace with the technology deployment. Roles were unclear, capability gaps were widening and resistance was building in parts of the organisation that had not been adequately engaged in the design.

What We Did

We conducted a rapid but thorough diagnostic of the workforce change landscape: where capability genuinely existed, where it did not, what was driving resistance and what the organisation needed to do differently. We then designed and delivered a workforce change programme that ran in parallel with the technology deployment, rather than lagging behind it.

This included redesigning job roles to reflect new digital ways of working, rebuilding the capability framework, designing learning and development interventions that were practical rather than theoretical, and building a network of change champions across the organisation who could carry the programme into parts of the business we could not reach directly.

The Outcome

Significantly improved adoption rates for the new digital systems. Clearer role definitions across the organisation. A capability framework that was used beyond the immediate programme. And a workforce that felt more equipped for the digital environment they were now operating in.

The justice estate presents some of the most complex change management challenges in the public sector. Security requirements, physical constraints, a workforce with a specific culture and history, and the high stakes of operating in an environment where things going wrong has serious consequences. Technology deployment in this environment is categorically different from most other sectors.

The Challenge

A major technology programme was being rolled out across the prison estate to modernise infrastructure and introduce new digital tools for both operational and administrative functions. The technical components were being managed effectively. The change that needed to happen around the technology was not.

What We Did

We provided programme design and change management support, working closely with operational leads, security teams and frontline staff to understand the real-world constraints and design change approaches that would work within them. We built a deployment sequencing model that accounted for the different operating contexts across sites, developed tailored training and adoption support, and created the stakeholder engagement infrastructure needed to maintain momentum and manage resistance.

We also worked at a senior level to maintain strategic alignment across a programme with many moving parts, a complex governance landscape and significant external scrutiny.

The Outcome

Successful technology deployment across multiple sites on time and within programme parameters. Measurably higher adoption rates than comparable programmes had achieved in similar environments. A change methodology that was documented and made available for future phases of the programme.