Chapter 4. Ashby’s Law of Requisite Variety
Pal’chinskii’s first principle[1] — to experiment with a variety of ideas to increase the chances of success — was echoed years later by a leading British scientist, W. Ross Ashby. In “An Introduction to Cybernetics”[2] Ashby introduced what became known as the ‘first law of cybernetics’ — the science of communication and control in living and mechanical systems. Ashby’s “Law of Requisite Variety” states that the amount of variety in a system must match the amount of variety in its environment to achieve control. In other words, if your environment is changing faster than your organisation’s ability to respond, you’re in trouble.
To understand ‘Ashby’s Law’, picture a thermostat controlling the temperature in a room by switching the heating system on or off whenever it reaches a fixed level. Now imagine that, instead of constantly monitoring the room’s temperature and responding accordingly, the thermostat only checks it once a day. Some days the room will overheat because the heating stayed on — other days, it will be too cold as the heating stayed off. In this case, we can say that the thermostat — the room’s ‘control mechanism’ — lacks the ‘requisite variety’ of information flowing in to respond effectively to changing conditions.
Management is the ‘control mechanism’ in organisations. They choose the direction, hire teams, set incentives, develop processes and decide which technologies to invest in to deliver results. However, unlike the predictable mechanical system a thermostat controls, management has to deal with an unpredictable human system. Faced with this uncertainty many managers try to turn the organisation into a predictable, ‘well-oiled machine’ in order to make it easier to control: They favour “best practices”[3] over disruptive new ideas; measure success against fixed KPIs rather than how well they adapt to changes in the environment; and push out mavericks — contrarian individuals who challenge the status quo — in favour of those they consider a better ‘cultural fit’ and less likely to rock the boat.
This pursuit of predictability gives managers a comforting sense of control, but it also creates a dangerous disconnect from their environment. By filtering out disruptive ideas the organisation fails to develop the ‘variety’ of responses necessary to adapt effectively when shocks — the emergence of a new, faster-moving rival, a game-changing technology, or an unexpected market shift — hit. Rigid organisations, built on ‘the one right way of doing things’, have no repertoire of alternatives to experiment with and no mavericks who can provide such alternatives fast. As a result, managers are left hoping everything will ‘go back to normal soon’, but hope is rarely a viable strategy. Irreversible decline awaits this unfortunate organisation.
Adaptivity Intelligence (AQ)
Adaptivity Intelligence (AQ) describes an organisation’s ability to respond effectively to changes. Organisations with low-AQ lack the range of options (or requisite variety of responses) needed to adapt to changing situations. These are “dead players”,[4] following outdated scripts and lacking the ability to innovate. In contrast, high-AQ organisations are “live players”, continuously experimenting with new ideas and technologies. When the old ways of working suddenly stop working (e.g. physical spaces close, customer behaviour shifts, supply chains are cut off) live players have a range of options (a requisite variety of responses) they can deploy quickly. This is how live players adapt and thrive — while dead players fade away.
When told something is “best practice” dead players ask: Who did this? What was the result? Can we copy it? But live players ask: Why is this best practice? When was it best practice? How does this apply to us today? Live players are open to learning from others but avoid relying on ‘past practices’ as this is backward looking which, in a fast-changing world, is like driving on a motorway while navigating through the rear-view mirror. Live players look forward, seeking out what works now in their context, embracing Pal’chinskii’s first principle — experiment with a variety of ideas to increase your chances of success. When a sudden change hits, they aren’t scrambling to respond, as they’ve already cultivated a variety of viable options they can deploy quickly.
Live players also avoid going all in on ‘big bang’ initiatives that promise to solve all their problems in one go. They understand that large projects often fail to get completed before conditions change again — creating additional problems as those who backed them throw good resources after bad rather than admit failure. Even when big projects succeed, they risk locking the organisation into a rigid way of operating that prevents it from adapting in future. Live players therefore also follow Pal’chinskii’s second principle — accepting some failure as inevitable, so keep projects small enough that failure is survivable. They favour multiple, small, (sometimes even contradictory) safe-to-fail[5] experiments that deliver quick results that can later be built on — rather than betting everything on a single initiative that takes a long time (and faith) before it yields results. This approach helps live players cultivate the requisite variety of responses needed to adapt quickly in times of uncertainty and change, giving them a significant competitive edge over their slower-moving, low-AQ rivals.
Fig.9: Adaptivity Intelligence (AQ) and Ashby’s Law of Requisite Variety
Thriving in uncertain times requires management — the organisation’s ‘control mechanism’ — to operate like a thermostat; monitoring a continual flow of information in and making real-time course corrections to keep the organisation on track. Unfortunately, many organisations make ‘big decisions’ just once a year, during the annual planning and budgeting cycle, with the rest of the year dedicated to making those plans a reality. But this approach is like putting on extra layers of clothing to keep warm instead of adjusting the heating, simply because the room was warm enough the last time the thermostat checked. Without information continually flowing in, organisations risk falling out of sync with changing conditions, forcing people to take unproductive action to deliver on plans that no longer reflect reality.
Why do managers cut themselves off from reality, only checking what’s really happening once a year? Part of the reason is that, like all humans, managers have a natural aversion to uncertainty.[6] It’s more comforting to act as though the world is the way you want it to be (a plan), rather than the way it is (reality). Another issue is the distorted information — caused by complex, ambiguous, unreliable or incomplete data[7] — managers have to rely on. In response to the flood of ‘noise’ in data today, many managers limit their intakes of information to short reports or quick debriefs. However, filtering out ‘noise’ also means filtering out critical signals about the changes they need to be aware of and respond to if the organisation is to survive or thrive.
So, what can managers do? The answer lies in Pal’chinskii’s third principle — developing effective feedback loops between decision-makers and those closest to the action, to quickly identify and select what works in the local context. Encouraging frontline staff — those closest to the action, in direct contact with customers — to experiment with new ideas provides management with reliable information about works for you, here, today and what doesn’t. This simplifies decision-making — we need to do more of this (that works) and less of that (that doesn’t). Management’s role shifts from predicting and controlling to enabling a sufficient variety of experiments to be launched (Pal’chinskii’s first principle) by hiring diverse talent[8] and then ensuring all experiments are safe-to-fail, (Pal’chinskii’s second principle) so failure doesn’t bring the organisation down, while successes can be amplified and, eventually, scaled up.
Rather than wasting time and resources every year trying to predict future revenues, simply for the sake of the budget,[9] managers should focus on increasing the diversity of experiments frontline people launch to respond to the ever-changing conditions. Local action — taken by your people, for your customers — provides the reliable and timely information management needs to make smarter decisions about what the organisation should (and shouldn’t) do next. This is how organisations cultivate the requisite variety of responses they need to adapt intelligently in a changing world. Let’s explore how one company did this in the next chapter.
1/ See chapter three — Pal’chinskii’s Principles.
2/ An Introduction to Cybernetics. W. Ross Ashby (1956) http://pespmc1.vub.ac.be/books/IntroCyb.pdf
3/ On the futility of copying “best practices” see the introduction to part one.
4/ https://samoburja.com/live-versus-dead-players/
5/ As opposed to ‘fail-safe’ (building something that won’t fail) ‘safe-fail’ encourages the launching of multiple experiments to learn what works or doesn’t in a particular context. The portfolio of experiments launched can even be contradictory in order to test competing hypotheses — far better to take action and learn what really works (and what doesn’t) in your context than waste time debating theoretical ideas in meetings, often based on data from the past extrapolated into the future and topped with wishful thinking. Experiments that have positive outcomes can then amplified with further action, whilst those with negative outcomes are dampened, with lessons learned as to why they failed fed into new experiments. This is an approach popularised by the Cynefin Framework.
6/ See introduction — Why Best Practices Hold You Back.
7/ See chapter one — Forget Strategic Plans.
8/ People from varied backgrounds, with diverse experiences and ways of thinking.
9/ By all means, calculate your costs to understand what you’re committing to spending and whether you can afford it. This is relatively easy since these factors are within your control. Unfortunately, you can’t predict revenues with the same certainty as you don’t control your customers. It’s far better to focus your resources on delighting customers so they choose you over your rivals, creating value for both them and yourselves. Remember, customers don’t care about your forecasts — they only what you can do for them.
