No-One Understands How Systems Work.

You may have been listening to economists debating and arguing about the state of the economy and the future of inflation. Are we in a recession or not? What will the economy look like next year? What causes inflation? Will the rate of inflation increase or decrease? What can be done to alter the future direction of change?

There is no shortage of opinions, but a total lack of certainty, of confidence, or even of sound theory.

You probably find the same phenomenon when engaged in discussions about business – about how firms can do a better job of creating customer value, to grow and succeed. How can they achieve a rise in stock price? What are the most critical constraints? What’s the best process for driving innovation? What’s the best way to manage and incentivize employees and to build a strong culture? Those are the kinds of words and phrases business consultants and business school professors use – your own peer conversations are probably more to do with increasing sales, or lead generation or your P&L, or whether all the ingredients you need will be delivered. 

But the challenge, in all these cases is the same. No-one knows anymore how these systems actually work. We can extend the list to climate as a system – some scientists claim they know how it works and can forecast the future, and another set views it as unpredictable and unmanageable. 

We saw during the so-called pandemic that virologists and infectious disease experts and pandemic modelers got their predictions – and their policies – hopelessly wrong, and it cost millions of lives and billions if not trillions of lost economic production. We can see the might modeler Ph.D.’s at the Federal Reserve make the same hubristic mistakes with their models of money supply, inflation, employment, and economic growth. The only thing they’ve ever been is wrong.

In fact, there’s a whole new science of not understanding systems which is called complexity theory, which overlaps closely with chaos theory. It says the following: A system is a collection of elements, components, parts, pieces, or, generally, agents. In an economic system, the agents might include individuals, families, and firms. There are additional elements like processes, government and institutions, norms, traditions, and a whole lot more. These elements and agents interact with each other and with inputs and outputs. There is further interaction after feedback loops establish themselves – agents react to outcomes and results they didn’t expect or anticipate. There are so many variables – individual decisions and preferences, group behaviors, trends, technological changes, money supply changes, etc, etc – that the interaction is described as complex, which means beyond understanding, unpredictable, and non-linear (it goes off in directions and at speeds that no-one expects).

Complexity is science throwing up its hands and saying, we don’t understand these systems anymore, can’t predict them, can’t control them, and can’t manage them. We don’t even have any ideas on how to do so.

There are many fancy new words that come out of this science. One, for example, is emergence. Systems have emergent properties, meaning s*** happens that we can’t account for and couldn’t even imagine in advance. Emergence is a kind of magic.

Another new term is self-organization, which means that the system will evolve and develop as it likes without any input -or despite any input – from the scientists.

Don’t worry, there are lots of government grants being given for the study of complexity, lots of papers and journals, lots of conferences, and lots of sabbaticals being taken to contemplate future studies and grant applications. There is money in complexity.

What’s the alternative? Pragmatism.

When the system (of life, of business, of health, of the economy) is complex to the point of incomprehension and unpredictability, there is only one action: do something and see if it works or it doesn’t work. In business, it takes the form of what is called today A/B testing. Try two different actions (without any prediction or bias or even desire as to which outcome will result) and choose one that works, i.e. moves in the direction you feel is better. Then do another test and another and another until there’s a string of results. Expand the actions so long as they keep working. Start a small store and keep expanding it unit by unit until there’s a big store. Be prepared for things to change without notice. Go back to square one if they do. 

There are fancy terms for this too. Economists call it entrepreneurship. Constantly trying and re-trying, combining and recombining, testing and re-testing. If a promising pattern is established, pursue it and reproduce it, but only so long as the pattern holds. Drop it as soon as it becomes erratic. Start another one. Creativity is the required skill set, and the whole point about creativity is unpredictability. 

Creative entrepreneurship doesn’t try to study complexity. Entrepreneurs face it every day and they take action rather than studying it. 

160. Laura and Derek Cabrera: Systems Thinking For Business

Entrepreneurs can realize their goal to think better, think Austrian by taking a systems thinking approach. We can ditch linearity and hierarchies in favor of distributed networks and webs of causality and create better knowledge – more aligned with the real world — and better mental models. Professors Laura and Derek Cabrera of Cabrera Research Lab and Cornell University — leading authorities on systems thinking — speak to Economic For Business on the application of systems thinking for entrepreneurs, and everyone.

Key Takeaways and Actionable Insights

There’s a crisis in thinking in the business world.

Laura and Derek Cabrera have conducted deep research in the field of business thinking, and they’ve identified both the problems and the solution. The problems include reductionism (we’re taught to think about parts of systems instead of the system as a whole); hierarchical organization of thinking (versus complex distributed networks); thinking in categories versus breaking down part-whole groupings; thinking in terms of liner cause-and-effect versus webs of causality; and the prevalence of bivalent logic (right/wrong, black/white) rather than the multi-valent logic of many right answers.

This way of thinking is not well-aligned with the realities around us. The solution is systems thinking — the thinking of complex adaptive systems.

Systems thinking aligns with how the real world works.

Our mantra at Economics for Business is Think Better, Think Austrian. Systems thinking is better thinking (and Austrian economics fully embraces complex adaptive thinking — what Mises called constant flux and Hayek called spontaneous order and Lachmann called the market as a process of combination and recombination).

Systems thinking defines complex adaptive systems in this way:

Autonomous agents follow simple rules based on what’s happening locally around them, the collective dynamics of which lead to the emergence of the complex dynamics we see.

This description is actually a mental model of a complex adaptive system. The products of systems thinking are mental models. None are perfect representations of reality, but they help us when they are better representations of reality.

Four simple rules of systems thinking produce better mental models.

By following 4 simple rules, over and over again, anyone can become a practiced and adept systems thinker. The rules are captured in the acronym DSRP.

D is for Distinctions. Systems thinkers make distinctions between different things and different ideas. We can make distinctions between different customers, different costs, different sales channels, different suppliers, different employees. We identify boundaries, what’s inside and what’s outside. We differentiate, compare, and contrast.

S is for organizing ideas into systems of parts and wholes. Everything is a system because it contains parts. Every e-mail contains words that contain letters made up of pixels. We construct meaning when we organize different ideas into part-whole configurations. We split things up or lump them together in systems of context. We group, we sort, we classify, we assemble.

R is for identifying relationships between and among ideas. We can’t understand much about anything without understanding the relationships between or among the ideas or components. Relationships include causal, correlation, feedback, inputs/outputs, influence, etc. Fundamentally, relationships are action and reaction. We live in an infinite network of interactions, including between our own thoughts, feelings, and motivations. We connect, interconnect, associate and join.

P is for looking at things from different perspectives. When we make a distinction or identify parts and wholes or identify a relationship, we are always doing so from one particular perspective, made up of the point from which we are viewing and the thing or things in view. Being aware of the perspectives we take is paramount to understanding ourselves and the world around us. If we change the way we look at things, the things we look at change. We frame, we interpret, we empathize, and we negotiate from a perspective.

Systems thinking is not a set of steps but a set of rules, and from the interplay of these rules emerges the dynamics of systemic thought.

There are four types of action for systems thinkers applying the DSRP rules.

1) See Information and structure.

To construct meaning and mental models, we take in information and structure it. It’s important to recognize the difference between the information and how we structure it. A good way to do this is visualization: use whiteboards or sticky notes or software to map out systems and parts (e.g., boxes within boxes on a chart) and relationships (lines between the boxes). This physical manifestation of a system can help create new knowledge and point to solutions.

Laura and Derek told the story of a large conglomerate business that, by visualizing its divisions and functions and the information flows between them, was able to identify redundancies, see where communications and information was lacking or blocked off, and design a new and improved structure.

2) Use common patterns in the structure of mental models.

Laura and Derek use the term cognitive jigs: forms of information structuring that can be used again and again. A list is one type of cognitive jig. It can be used to order priorities or structure wholes into parts. Similes and metaphors are jigs. There’s another called a relationship distinction system (RDS) that can help solve silo problems in organizational design by identifying required relationships and the people responsible for them, and the resources required to operate the relationship. Excel spreadsheets and tables are jigs. Look for useful cognitive jigs and use them over and over again. They increase the efficiency and speed of thought.

3) Make structural predictions.

Austrians are wary of predictions because we know the future is uncertain. Here, we are not talking about predicting the future, but predicting the possibility of new knowledge existing after restructuring information. For example, a new relationship opportunity could emerge if we change our perspective. A new understanding could emerge if we break something that we were treating as a whole into its parts. We can identify gaps in our current thinking and make a bet that there’s something positive in changing that thinking. We can create new knowledge.

4) Embrace the logic of and/both.

We are taught bivalent logic: there’s right and wrong, there’s black and white, there’s X and Y. There’s an alternative: multivalent logic. There can be more than one right answer. There can be a continuum rather than fixed points.

One example of multivalent logic applies in the analysis of what customers want. They have a variety of preferences, ordered in different ways at different times and in different contexts. They are continuously learning what to want, and always making trade-offs. Bivalent logic won’t help entrepreneurs understand customers’ choices or decision-making processes.

Another example of bivalent versus multivalent logic is cause and effect compared to a web of causality. We tend to think of cause and effect as neighbors on a timeline. The cue ball of cause strikes the colored ball of effect and moves it in a designated direction. But it’s more realistic to think of the events of our lives or our business having multiple causal factors. There are so many mediating factors and external and internal variables that lead us to be more systematic in our thinking about them. Purposely look for webs of causality rather than shoehorn observed phenomena into a linear causal model that doesn’t match the reality of the world.

Systems thinking includes the recognition of individual subjective purpose and intent.

The perspective of methodological individualism leads Austrians to worry about whether systems thinking is well-aligned with Austrian thinking. I asked Laura and Derek this question. The response: “I would say that’s precisely what systems thinking entails — the notion that each individual agent is following simple interaction rules with other agents, and that those interaction rules are leading to the system and its emergent properties.

An example of an interaction rule from Austrian economics: humans act in order to improve their circumstances. Another is that they use their own subjective value system to determine what is an improvement. The action axiom, subjective value, opportunity cost in choosing between alternatives, profit and loss and the context of constant change are the simple rules of Austrian economics.

Practice, practice, practice.

Systems thinking is something everyone should be able to do. It can be practiced. Our brains are already building mental models about the world. It’s already in us and so it pays to be aware of it. 

It’s like any exercise: more reps make us stronger. Look at anything through the DSRP lens when you are feeding your dogs or driving down the highway observing billboard advertisements. Make the neuronal pathways of DSRP second nature.

This can occur at the level of individual learning or of organizational learning. In episode #152 (, we discussed the organizational model of VMCL — an organization using learning to acquire the capacity to do its mission every day to achieve its vision.

Additional Resources

“How to Become A Systems Thinker” (PDF):

“Practical Systems Thinking Actions and Behaviors” (PDF):

Systems Thinking Made Simple: New Hope for Solving Wicked Problems by Derek and Laura Cabrera:

Cabrera Research Lab:

The Accelerating Ascendancy Of Austrian Economics.

We are entering an entrepreneurial age. Colleges and universities are teaching entrepreneurship, professors are researching it, and children’s books are being written about it. Policy-makers are appreciating it as a better way out of poverty than welfare. Large companies are striving to be more entrepreneurial. More and more young people are creating new entrepreneurial business models, utilizing easily accessible infrastructure from Google and AWS. Entrepreneurship is the zeitgeist.

In a recent article at, Per Bylund, who teaches entrepreneurship at Oklahoma State University, suggested that every entrepreneur should become familiar with Austrian economics. What is that? It’s the method of economics that recognizes entrepreneurship as the driver of prosperity and provides the design blueprint for the system that best unleashes potential economic growth for everyone to enjoy.

Austrian economics is an unfortunate brand name. It reflects the origins of the tradition in the University of Vienna, but that’s a long way in the past. A better brand name would be entrepreneurial economics. However, we’re unlikely to be successful with that re-branding, so we won’t attempt it for now.

More important than the brand name are the knowledge, insights, and business tools that Austrian economics can deliver. Austrian economics is on-trend for business in the digital age.

Management Science Is Moving In The Direction Of Austrian Economics

in an essay titled The Logic Of Entrepreneurship, Mohammad Keyhani of the Haskayne School Of Business points out that traditional business school teaching of strategic management is based on the old economics, usually called neo-classical. This is an economics of mathematical models, with no sense of humanity. It studies non-existent states referred to as equilibrium, where theoretical competitive structures can be analyzed to identify whether any firms have an “advantage”.

The new management science is replacing mathematical modeling with human modeling: how do people act to create value for each other? This is not math, although it can be simulated in computers by giving virtual economic actors human values and projecting the outcomes. The new entrepreneurial business thinking draws from Austrian economics: human, creative, and focused on value creation. The entire business discipline is moving in this direction, replacing the concept of management with the concept of entrepreneurship.

In an earlier paper, the researchers Stephen Vargo and Robert Lusch were among the first to suggest that entrepreneurship should be elevated over management in business school. Management is a product of the now-past industrial age, tending to give us large bureaucratic firms driven by efficiency (avoiding waste) than effectiveness (creating new value), and emphasizing control in existing markets rather than the exploration of new ones. It’s time to abandon this whole way of thinking and organizing. Entrepreneurship gives us innovation, new value, and progress.

Austrian Economics Is Systems Thinking.

The newest advances of science in all fields are products of, or related to, systems thinking. This is true for economics, and Austrian economics has been called a type or branch of systems thinking. Brian Arthur of the Santa Fe Institute, the epicenter of the study of complex adaptive systems, developed the concept of Complexity Economics. The economy, industries, firms, and economic institutions are complex systems. They can’t be managed. there are too many elements, interactions, combinations, creative initiatives, and emergent outcomes for anyone to manage. He has documented the antecedents of this new economics, in which he includes the research work and theories of prominent Austrian economists F.A. Hayek and Ludwig von Mises, and the Austrian school in general.

Core Principles Of Austrian Economics Are Recognized In The Mainstream

The first principle of Austrian economics for entrepreneurs cited in Per Bylund’s article is consumer sovereignty. This term refers to the insight that the consumer or customer is the ultimate determinant of what is produced, what is profitable, what sells well and what doesn’t. The mechanism is buying or not buying. This simple insight explains why Google is the dominant search engine, why Amazon drives so relentlessly towards greater convenience, and why the conversion away from fossil fuels is not going as fast as the government wants.

Yet major corporations and their management teams have been utterly confused about this simple principle. They talk about shareholder value and stakeholder value and put them in conflict with customer value. Leading business writer Steve Denning is one of the leading edge commentators who is setting things straight and asserting that top management must change their fundamental assumptions and take the Austrian approach to the primacy of the customer.

Human Action And Human Values

Rather than the algebraic symbolism of the mathematical models that make up mainstream economics, Austrian economics deals with human action and human values. What do people do and why? How do they feel their lives can be made better, and how do they identify and choose the best means to attain that goal? Austrian insights into the human values that drive human behavior and collaboration can be applied in multiple areas. Business management is one of them. The old mental is summed up by Derek and Laura Cabrera in their management book Flock Not Clock as Plan, Command, Control, and Utilize. In this traditional view, management produces rigid plans, which they communicate through the hierarchical organization with the command to the lower levels to follow, aided by control mechanisms such as process flow charts, and look upon the workforce as a resource to be utilized. The Cabreras offer a more human alternative that revolves around the sharing of a beloved vision and understandable mission in everyone’s mind, building the capacity for everyone to help execute the shared mission, and the learning loops from the market to continually improve. This is human values in action.

Diana Jones has captured this principle in her term Leadership Levers. The levers for management to generate high performance from an organization are not plans and commands and control mechanisms, but relationships, emotion, and empathy. These are the same elements that Austrian economics studies to understand systems like the economy, industries, firms, and customer groups. Empathy, for example, is identified as the number one skill of the entrepreneur, a tool to understand what customers want. Value is understood as an emotion, a feeling about whether an experience was valuable or not. And the relationship between producer and customer is a collaboration, a way to co-create those valuable experiences. Jones’ levers are Austrian levers.

An Ascendant Future

All these instances suggest a future in which more and more practitioners in more and more fields take inspiration from or draw ideas from Austrian economics and incorporate its principles into their thinking. As we say: Think Better, Think Austrian.

Don’t Accept False Dichotomies. Entrepreneurs Exercise Integrated Systems Thinking.

We talk about politicians trying to divide us, but personnel consultants, business advisors, HR executives, and some psychologists are often worse in wanting to divide us into dichotomies. They tell us we’re either creative or logical, but we can’t be both. We are either intuitive or analytical. We have hard skills or soft skills. Some follow the heart, others the mind. The yin is the critical thinking, executive function, intellectual and cognitive side of us, and the yang is the emotional, prosocial, interpersonal side. Those consultants who exhibit a philosophical bent might talk in terms of Apollonian and Dionysian types of thinker – logic, rationality, and analysis versus intuition, feeling, and synthesis.

Some personality tests utilize multiple variables and combine them in characterizing individuals who are subjected to their question banks. The output is said to represent our strengths (versus weaknesses) or typology (we’re this type, not that type). They’re still ultimately dichotomies, arrayed via X and Y axes or 2X2 charts or high-low graphs.

The dichotomy is false. Either/or thinking of any kind is an error, and the error is magnified when classifying human beings. People are complex systems, a dynamic integration of learning, preferences, genetics, family background, experiences, job history, health, and many, many more elements. They can’t be divided into two piles.

The alternative approach is systems thinking. According to Derek and Laura Cabrera in Systems Thinking Made Simple, we all have it in us to be:

  • critical thinkers who can analyze and solve problems;
  • creative thinkers who can see new and innovative solutions to problems;
  • scientific thinkers who can recognize biases;
  • prosocial thinkers who can work well with others and build strong communities;
  • emotionally intelligent individuals, posessing a sense of self and what we offer to the world.

How do we achieve this balance? It’s an emergent property of practicing systems thinking. We can think about how we think, and therefore how we act and how we collaborate with others. Awareness about how we think is essential for the kind of balance and integration the Cabreras advise is possible.

  • Awareness that everything we think about, perceive and experience is the product of our own mental model which is an approximation of the real world. Self-analysis regarding our own mental model – how good or poor an approximation of the real world is it? – is always a good basis for integrated thinking.
  • Awareness of the role of our own emotions, motivations and preferences in the distinctions we draw, the choices we make, and the decisions we take.
  • Awareness that both our own thoughts and those of others are influenced by unique individual perspectives rather than objective analysis.
  • Awareness that there are many ways to organize and interrelate ideas and things and your current way of doing so is just one of many possibilities.
  • Awareness that cognition, emotion and motivation all influence our mental models and our behavior, and the ability to distinguish among them.

Taken together, this integrated awareness constitutes what the Cabreras call metacognition: thinking about how we think. It’s often referred to as emotional intelligence. Insight into our own thoughts is key to high achievement in all domains.

In business, we refer to the individuals who exhibit integrated, balanced, and systems thinking at the highest level as entrepreneurial. Entrepreneurs, those who think about how to create new and higher levels of value for customers, are systems thinkers at their core:

  • They practice empathy, which is the building of mental models of others – i.e. customers – and the running of imagined value propositions through these models to understand their potential to generate a preferred experience that will result in a business success.
  • They translate the insights from these models into a deliverable service, an act of design that calls for the assembly and combination of multiple components, making choices from the customer’s perspective to decide on which elements to include and which to discard.
  • For service delivery to be accepted by customers, entrepreneurs identify all the possible perceived barriers to purchase from the customer’s point of view, and remove them by conceiving of the best-performing mechanisms.
  • They set up, monitor and resond to feedback lops, which is the essence of adaptive systems thinking.

There is no dichotomy in entrepreneurial thinking. It’s not mediated by strengths and weaknesses, and it’s dominated by neither emotion nor reason, but incorporates both. It’s creative and practical, objective and subjective, empathic and self-aware. Entrepreneurs consciously build their own mental models and continuously test them against the reality of the world of economics. The only dualism that’s relevant is what works and what doesn’t in the world of commerce, and these two possibilities are processed together as learning. The goal is durable success, and entrepreneurs exhibit no ambiguity in their assessment of results.

When the consultants and psychologists want to test you to ascertain whether you exhibit the entrepreneurial personality, it’s best to politely decline. There’s nothing of advantage to learn.

Better to focus on and sharpen your systems thinking:

  • Always thinking of the customer first, assessing their system and their place in it, all of the influences on their choices, and all their desires, preferences and dissatisfactions;
  • Working to translate your customer understanding into a deliverable service, which requires you to consider all the elements and components that make up that service, and how to combine them and integrate them in a single value proposition;
  • Identifying all the potential barriers to purchase – whether the barriers are feelings, insuffiicent knowledge, better alternatives, price or lock-in to existing choices. Removing all barriers requires identifying them – and how they work together – first.
  • Setting up feedback loops and adaptive mechanisms so that you can always respond to customer inputs. Develop an adaptive system.

By focusing on these rules, you’ll build an entrepreneurial system that gets stronger and stronger over time.

There’s no dichotomy. it’s not win-lose or strong-weak or logical-emotional. It’s an integration of components and elements into an entrepreneurial system that learns and consistently improves progress towards a goal.