Some organisations are systemically more change-receptive than others, and so are some teams within any given organisation. There are evolutionary explanations for both patterns, decent empirical support for both, and practical consequences for how we assess change readiness and run change impact assessments.
I should say up front that none of this means some organisations or functions are broken. They’ve adapted to different evolutionary pressures, and what looks like dysfunction from where you’re standing often looks like sensible adaptation within their context. These aren’t fixed rules, obviously – organisations and teams do break the mould, though perhaps less often than the people inside them like to think.
Factors that influence change receptiveness
Pick two organisations at random and they’ll almost certainly react to change differently. Some of that comes down to the people within them, some to the leadership, and some to the particular change being asked of them. But there are patterns you can predict. I’ve identified six factors, all reasonably well evidenced in the literature, that set this baseline.
- Age is the most reliably documented. It’s mostly about complexity piling up over time: procedures, roles, technologies and relationships (including external ones) accumulate. Each addition will be chosen because it fits with the others, so changing any one of them now means changing a dozen more. Le Mens, Hannan and Pólos showed that age by itself plays a part too1. Sørensen and Stuart added a useful nuance: older companies handle small, incremental innovation well, but struggle with the radical change that anything other than a very stable market eventually demands. The research is consistent – older organisations are slower to change, even once you control for size, sector and past performance.2
- Size compounds the problem. Bigger organisations have more layers of bureaucracy, more committees, more dependencies between functions and more formal procedures. The evidence on size isn’t as linear as that for age but most of it says scale alone slows change down. A small minority manage to keep innovative cultures at scale (see point 6 on Competition), but for most, that bureaucracy is precisely how they coordinate reliably, and nobody’s found a way to keep the benefits of scale without paying something in agility.
- Sector matters too. There’s a substantial literature comparing public and private sector workforces on risk, and it’s reasonably consistent. One group3 used a clever revealed-preference design, offering their survey respondents a choice of reward: a gift certificate, a lottery ticket or a charitable donation. Public sector employees came out significantly more risk-averse than their private sector counterparts – in what they actually chose, not just what they said.
- Regulation is another. Heavily regulated industries such as transport, finance or pharma, develop risk-averse cultures because that’s what the regulatory environment selects for and rewards. A bank that gambles on a novel process and gets it wrong faces consequences a software company simply doesn’t. In safety-critical industries, even moderate risk can cost lives. Over time, the environment selects only those organisations that embed low risk tolerance into their cultures, which is entirely as it should be. It makes change harder, but usually for very good reason.
- Crisis or scandal can ‘flip’ a culture. Banking is the clearest recent example. It had been an overly risk-tolerant industry, and the 2008 financial crisis set off a deeply traumatic cultural and regulatory shift across global banking that’s still with us nearly 20 years on. Srinivasan, Li, Rajgopal and Wong looked at board-level control mechanisms either side of the crisis and found banks used more risk-focused language in their annual reports, brought more technical risk expertise onto their boards, and tightened formal risk governance. None of this happened to anything like the same degree in non-bank firms.4 The Financial Stability Board’s 2014 framework on bank risk culture, the EU’s capital regulations and the Bank of England’s Senior Managers Regime all reinforce the lesson.5 A serious crisis is one of the few things that shifts a culture dramatically in a short space of time, and it almost always pushes it towards the change-averse end. Banks have become risk-averse with good reason!
- Competition and market dynamism cuts the other way. Industries facing fast technological or market change – such as media, retail and some professional services – develop more change-oriented cultures, because being nimble is vital to such organisations. In dynamic environments, selection favours the adaptable and kills off everyone else. In slower-moving ones, the less adaptive survive and pile up, getting slower as they grow and age. 6
This factor also pulls against age and size. There are large, older companies, like Amazon, 3M and Pixar, that have kept their agility. But doing so takes sustained effort and rigidly enforced ‘rules’ about how work gets done. There’s a whole other article in this topic, but for now let’s just say they’re the exception, and they all operate in fiercely competitive, disruptive industries where constant adaptation is the price of survival.
Let’s return to banking to illustrate how these factors compound. A typical heavyweight UK retail bank will be long-established – often at least 150 years old;, large, with tens of thousands of employees; heavily regulated; working in an industry with moderate rather than extreme dynamism; and still shaped by traumatic memory. Every factor pushes the same way. The baseline change receptiveness ends up low, and anyone importing practices built in younger, smaller, less regulated, more dynamic organisations is in for a frustrating time, I can tell you that first hand. The same logic applies, with different specifics, to large public-sector bodies, utilities, defence contractors and the big professional services firms. They aren’t broken; they’ve just adapted to a different environment.
To make this useful in practice, I’ve built a simple Receptiveness Baseline Estimator that takes these six factors as inputs and returns an indicative baseline score. The results show what each factor contributed and document the literature behind the weighting for each factor. The Estimator generates a hypothesis rather than a prediction, but a starting point grounded in the literature beats gut feel by some distance (please contact hello@epion.co.uk for more information on assets like this).
| Practical example Flag carrier airline, Procurement TransformationThis one goes back well over a decade, to when a lot of flag carriers were under real pressure from the emerging budget airlines. An established, large, heavily regulated company ‘flipped’ into a highly innovative mindset aimed almost entirely at cutting costs. Strategically I’d say it was the wrong call (flag carriers shouldn’t be competing on price alone), but it certainly changed behaviour in the procurement function. I sat in meeting after meeting where staff worked out inventive ways to shave pennies and kilos off the refreshment trolley – reusing opened juice containers, dropping Business Class meal service from three plates to two. The question for leaders in slower industries is whether your culture could cope with that kind of disruption, because it increasingly feels less like a question of whether disruption will hit you but rather when. |
Checklist
- Factors that slow organisations down:
- Older organisations change more slowly, even once you control for size, sector and past performance
- Size compounds it – scale on its own slows change down.
- Public sector employees are significantly more risk-averse than private sector ones
- Regulated industries grow cultures that slow change down
- A traumatic crisis can ‘flip’ a company from risk-tolerant to risk-averse, and it’s one of the few things that changes culture quickly
- Competition and disruption push the other way and can partly inoculate a business – occasionally enough to offset age and size (though that’s rare)
- Epion’s Receptiveness Baseline Estimator gives you a starting hypothesis for how change-receptive your organisation is – get in touch for more.
Footnotes
- Le Mens, G., Hannan, M. T. & Pólos, L. (2015) ‘Age-related structural inertia: A distance-based approach’, Organization Science, 26(3), pp. 756–773. ↩︎
- Sørensen, J. B. & Stuart, T. E. (2000) ‘Aging, obsolescence, and organizational innovation’, Administrative Science Quarterly, 45(1), pp. 81–112. ↩︎
- Buurman, M., Delfgaauw, J., Dur, R. & Van den Bossche, S. (2012) ‘Public sector employees: Risk averse and altruistic?’, Journal of Economic Behavior & Organization, 83(3), pp. 279–291. ↩︎
- Srinivasan, S., Li, S. X., Rajgopal, S. & Wong, Y. T. F. (2024) ‘What board-level control mechanisms changed in banks following the 2008 financial crisis?’, Accounting, Organizations and Society. ↩︎
- Financial Stability Board (2014) Guidance on Supervisory Interaction with Financial Institutions on Risk Culture. Basel: FSB. ↩︎
- Hannan, M. T. & Freeman, J. (1984) ‘Structural inertia and organizational change’, American Sociological Review, 49(2), pp. 149–164. ↩︎
