Foundations: Systems Principles and Laws for Founders
Why principles, not playbooks, are needed to manage complexity and drive change
Hey! It’s Andreas from Monetisation Matters, the home of in-depth articles and actionable insights on Strategy and Monetisation. Built for Founders, Product, and Product Marketing leaders as they navigate their $1m to $100m growth journeys.
This month’s article dives into complexity science, covering a selection of the most important systems laws and principles to help develop strategy and drive change.
Why this is important
We are allergic to playbooks at Notion Capital. A playbook mindset stops people from the difficult job of thinking. A tactic or strategy that worked in one business is likely to fail when context changes. Understanding why something worked, or didn’t, allows us to make adjustments as circumstances change. Principles over playbooks.
Businesses are complex systems. If we want to understand the principles and laws that govern them, we should be studying complexity science for answers. Look in places others don’t, and we are rewarded with a novel and powerful toolkit to develop strategy and drive change.
Managing complex systems
Businesses are complex, not just complicated. Complex because they consist of many moving parts; operate under uncertainty; in an environment that is constantly changing. VCs and startups talk about growth loops and flywheels - examples of closed loop systems. Closed loop because there is feedback, where outputs become inputs.
The basic components include:
some goals
a controller, for example a manager
the system in question e.g. an SDR team
output/performance of the system
measurement of variances
feedback to close the loop
How you draw a boundary around the system you are interested in depends on what you are trying to achieve. We can draw a box around the diagram above and call it a system. Every system sits within another system. They are recursive, and have a hierarchy. For example, an SDR team sits within the go-to-market function, within a business, industry, and economic system. Each is a system in its own right.
We hear a lot about the role of people, process, and technology, but nothing about the laws and principles that govern the systems we are trying to manage. It’s like focusing exclusively on the driver, engineers, and car of an F1 team without ever mentioning aerodynamics or grip. Cybernetics is the study of these laws and principles - a branch of complexity science applied to management.
“If cybernetics is the science of control, management is the profession of control.”
Stafford Beer
The below is adapted from Patrick Hoverstadt, a strategy consultant, author, and complexity practitioner. We could classify management based on three paradigms of sophistication.
Paradigm one: Garbage can management
Managers walk around with two garbage cans. One contains problems, the other solutions. When they come across a problem, they dig into their can and pull out a solution. If things are slow, they will navigate the business with a solution in hand, looking for a matching problem. They don’t operate with models or frameworks in mind, and are totally blind to second order effects. Instead they focus on immediate symptoms and fixes. Infantile management.
Paradigm two: Playbook reflex
Managers operate with models or frameworks, but they deploy them from ‘off the shelf’. They don’t adapt their approach based on context, expecting to achieve similar results in new situations. A mindset that is especially noticeable in managers that have achieved some success. Blind to the differences between contexts that really matter, they enter new situations with a deadly mix of hubris and incompetence.
Paradigm three: Modeling
Managers operate from a principles over playbook mindset (even when they talk about playbooks). Building or adjusting models to suit the problem and context they are looking at. They close the loop - adjusting their models based on real world feedback. Embracing experimentation, testing assumptions and refining their models to maintain fit with the environment.
Boundaries & perspective
Before we can manage a system we need to first define it. We do this by drawing a boundary around what is included and excluded. If we have a churn problem, do we draw a boundary around Customer Success only, or do we include Product? What about Sales or even customers themselves. Where we set those boundaries changes the system as well as our perspective, analysis, and conclusions.
Making a distinction
"We take as given the idea of distinction and the idea of indication, and that we cannot make an indication without drawing a distinction."
The quote above is from George Spencer-Brown’s Laws of Form. He’s pointing out that to talk about something you have to first make it distinct from everything else. It’s the fundamental starting point to systems thinking.
By drawing a boundary we are implicitly making a statement about what matters. We are stating that the thing we have drawn a boundary around is something distinct. Customer segmentation is an example of boundary setting. We carve up the market in a way that highlights the distinctions between groups of customers that really matter. Defining your ICP is a critical boundary setting exercise to help minimise complexity.
Perspective
“It is a narrow mind which cannot look at a subject from various points of view.”
The boundaries we draw, and where we sit in relation to them shapes our perspective. Which in turn drives the decisions we make. For example, does a CMO draw a boundary around the marketing function she leads, or around the executive team she is a member of, or the revenue function as a whole? Each boundary creates a different perspective. If she primarily sees herself as the leader of marketing, she will make different decisions vs. as a member of the executive team. Both perspectives matter, but her ability to cross boundaries and switch between perspectives will shape her models, objectives and decisions.
Different perspectives of the same function. None are wrong, but none capture the full complexity either.
Our perspective changes whether we sit outside, at the edge of, or well within a boundary. For example, customer success managers often sit right at the edge of their company's boundary. From there they can empathise with customers, providing invaluable insight to product management. Straying too far into the customer’s world though creates issues. They become their customers’ best friend and lose the ability to have difficult conversations.
Finally, we need to be aware of how boundaries create communication challenges. What makes sense within one boundary, might not make any sense when the message crosses into another system. Comms is such an important function because messages crossing a boundary from one system to another need to be translated so that they still make sense. For example, the decisions made at Board level, and the rationale behind those decisions require significant translation as they move across multiple boundaries. Not only vertically in terms of hierarchy but also horizontally across functions.
Decision making & control
Effective management relies on making good decisions quickly, translating them into action, and adjusting based on feedback. Modeling sits at the heart of this.
Contant-Ashby theorem
“Every good regulator of a system must be a model of that system.”
In relation to management, if you want to be a good manager, you need to have a model of the thing you are trying to manage. It doesn’t need to be an exact reflection of reality, but must capture the structure and dynamics that matter. Having a model in place allows you to orientate and speed up decision making. If you then plug real world feedback into the model, you can adjust and improve it over time. The rise of RevOps is a clear sign of the growing recognition of modeling and its impact on performance - practical systems thinking at its best.
The London tube map is a useful model if you want to navigate the underground. Useless if you want to walk it. You’ll quickly find the distances between stations are distorted, and the different lines don’t give you much guidance over where you need to go. So the models we build need to be fit for purpose - recognising that all models are wrong, but some are useful.
Law of requisite variety (Ashby’s law)
“Only variety absorbs variety.”
To be effective, a manager must have at least as many ways to react as the variety of situations he might face. You can increase your variety of control, or you can reduce incoming variety. What matters is that they match. Reducing incoming variety is especially important in the early phases of a start-up as so little process and policies are in place. Over time, it can build more internal variety, which allows it to take on more complexity from the environment e.g. serve additional segments of the market.
In competitive situations, the player or team with more variety will tend to win. Greece unexpectedly won the UEFA European Championship in 2004 because they deployed a variety of play that opposing teams couldn’t match. They changed formations depending on who they played, had a formidable defence that was difficult to break down, well drilled set piece plays, and a team that worked seamlessly together. A much less talented team beat the greats of Europe. That’s not luck, it’s Ashby’s law at work.
Redundancy of potential command principle
“Power resides where information resides.”
The first implication is that as long as you can get the right information to decision makers, you can distribute authority. Distributing information across the organisation becomes synonymous with distributing authority. Information becomes the key ingredient to move away from a command and control approach.
Second, decision makers will make the decisions that they have the information available to make. So if you want quick decision making, information needs to be prepared in advance. Collecting information before you need it makes it technically redundant, which leads us to our final implication.
Third, having spare / redundant capacity is a source of resilience. If one part of the business goes down, another can step in. This is only possible if information is distributed.
Balancing autonomy and cohesion
“Managers should maximise the freedom of colleagues, within the constraint of fulfilling the business’s purpose.”
This touches on Paul Graham’s flawed essay on ‘Founder Mode’. The key point he should have been addressing is the tension between providing colleagues with autonomy, whilst ensuring that everyone is working together in a cohesive way. This has nothing to do with professional managers vs. founders.
Maximising the freedom of colleagues within constraints has both moral and practical dimensions to it. Moral, because everyone wants to live a life free from control and coercion. Practical, because autonomy gets you speed, flexibility, and the capacity to deal with massive complexity. The right balance depends on the nature of the challenge and the purpose of the system.
An F1 pit crew needs maximum cohesion, and minimal autonomy during a race. Everyone has to be in exactly the right place, at the right time, executing in perfect synchrony. Imagine the chaos if each member had the autonomy to decide what to do and when. On the other end of the spectrum is an improv comedy show. Each comedian has a lot of freedom to express themselves. The need for cohesion is minimal. They just have to be on time, and act in a way that’s consistent with their purpose - to make people laugh.
Recursion is at the crux of why this balance is universal to absolutely every team and colleague. You can always move up or down the hierarchy and find functions which want cohesion from the teams and individuals that sit within the function, and autonomy from the hierarchy above.
Change & survival
Performance is systemic. It’s an emergent property of the whole business and its relationship with the market. As the market changes, so to must the business in order to maintain fit. Otherwise it wont survive.
POSIWID
“The purpose of a system is what it does”
Performance is a perfect reflection of the business you’ve built. If you want to see different outcomes, you have to change its structure or orientation. A massive red flag is when a business isn’t growing and the CRO makes statements to the effect of “failure isn’t an option, we have no choice but to grow”. No one doubts intentions - but trying harder isn’t a strategy.
Gall's Law
"A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work."
Gall’s law highlights the dangers of over-engineered solutions. Iteration provides the time needed to test and learn before committing. Simple unoptimised solutions provide more flexibility to adjust as circumstances change. Simple is also cheaper. You can keep burn low by matching complexity to the scale of the challenge, focusing instead on doing just enough to remove limiting factors.
It explains the popularity and effectiveness of the ‘Lean Startup’ approach, in particular building an MVP which can then be used to test and learn. The same logic applies to new processes. Starting with minimum viable processes, and then adjusting through real world experience, rather than over-engineered approaches which end up being misspecified.
Fitness
“Survival of the fittest.”
Fit is one of the few principles that is talked about extensively, but it's applied too narrowly to a product and its market. Instead, it is a principle of universal applicability. Relevant to the relationship between a business and industry or founder and evolving start-up. The implication for founders is to change and evolve as their business grows, maintaining fit with what the business demands of them. And for the business, to match the average rate of change of its industry to maintain fit.
Information plays a central role to building and maintaining fit, which I’ve written about here and here. Hiroyuki Itami covers this elegantly in his book ‘Mobilising Invisible Assets’. The logic works as follows: accumulating information drives fit, which drives growth, which requires a series of overextensions. No different from an individual pushing themselves outside of their comfort zone to keep learning.
Closing remarks
The cross-discipline nature of complexity science is what makes it so powerful and interesting. Researchers from disciplines who historically did not work together, or understand each other have been collaborating increasingly closely over the last 70 years, creating a new kind of science. They were the weirdos, and outcasts, who’s work is now slowly going mainstream. There is so much the business world can learn from this new science, bringing a level of rigor it badly needs.
“The twenty-first century will be the century of complexity.”
Stephen Hawking
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