Beer is one of many who have given us models for thinking about a business as an activity system. This chapter is not about the practical use of such models. It is about the applicability of harder science terms and concepts in softer sciences.

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Contents

Beer’s inspiration. 1

Project Cybersyn. 2

The Viable System Model (VSM) 5

Conclusions and remarks. 10

Beer’s inspiration

"If cybernetics is the science of control, management is the profession of control.” Beer

Stafford Beer (1926- 2002) beer was a theorist, consultant and professor at the Manchester Business School. W. Ross Ashby (1903-1972) was a psychologist and systems theorist who popularised the usage of the term 'cybernetics' to refer to self-regulating (rather than self-organising) systems. Beer regarded Ashby as a grandfather of cybernetics. They knew each other, and I believe Ashby was a godfather to one of Beer’s children.

Beer is probably best known for extending the applications of cybernetics from biology and engineering to management science. Beer’s “Brain of the Firm” was published in 1972 (the year Ashby died). The title echoes Ashby’s “Design for a Brain” 20 years earlier; and it easy to see why.

In Ashby’s “Design for a Brain”, the human is a homeostatic machine that maintains essential state variables. And the brain-to-body relationship is seen as a regulatory system with feedback loops.

In Beer’s “Brain of the Firm”, a business is a homeostatic machine that maintains essential state variables. And the management-to-worker relationship is seen as a regulatory system with feedback loops.

Beer leaned heavily Ashby’s ideas.

"According to the science of cybernetics… there is a natural law that governs the capacity of a control system to work. It says that the control must be capable of generating as much "variety" as the situation to be controlled." "Management Science" Beer, (p. 37), 1968.

It is presumed here you have read the chapter on Ashby’s law of requisite variety, which explains why it is difficult to apply cybernetics to sociology and management science.

Project Cybersyn

On taking office in 1970, the new Chilean president, Allende faced a problem.

“How was he to nationalize hundreds of companies, reorient their production toward social needs, and replace the price system with central planning, all while fostering the worker participation that he had promised?” Ref 3.

Beer was hired to help, and named his project Cybersyn, short for “cybernetics synergy”.

“For Beer, in fact, corporations are homeostats. They have a clear goal—survival—and are full of feedback loops: between the company and its suppliers or between workers and management. And if we can make homeostatic corporations why not homeostatic governments.” Ref. 3

The use of the hub and spoke pattern

Having nationalised hundreds of companies in key industries, an aim of the government was to help and direct them. Beer interpreted this, cybernetically, as monitoring critical variables so managers could detect and head off problems.

What resources and supplies (fuel, tin cans, sugar, fruit) were critical to the economy? What variables (fuel stocks, peeled fruit stocks, the number of cans in the factory line, delivery times) mattered? How could those variables be measured (mechanically or manually) and reported to managers both locally and in the center?

In software architecture there are several centralizing versus distributing design pattern pairs. For example:

Centralised pattern	Distributed pattern
Hierarchy	Network
Hub and spoke	Point to point
Client sever	Peer to peer

A theme in Beer’s later work was distribution of control and local autonomy. However, project Cybersyn centralized the definition of key variables, and control of deviations from the norm.

At that time, computing resources were very limited. The project relied on central IT resources to facilitate inter-business coordination. So, Beer used a hub and spoke communication pattern rather than a point-to-point pattern.

“one central computer, analyzing reports sent by telex machines installed at state-run factories, could inform the firm of emerging problems and, if nothing was done, alert agency officials.” Ref. 3

In 1972, this pattern was used successfully in an impromptu way.

“A nationwide strike by truck drivers, who were fearful of nationalization, threatened to paralyze the country. Fernando Flores had the idea of deploying Cybersyn’s telex machines to outmaneuver the strikers, encouraging industries to coördinate the sharing of fuel.” Ref. 3

(Today, the hub could be a web page with information about fuel resources. Any actor with a fuel stock can post a message; any actor with a fuel need can sort the messages by stock location and volume. Distributed actors can create and operate countless such hubs – independent of each other – and countless overlapping social networks. Each central hub models only a fraction of what the actors it connects are interested in.)

In practice, point-to-point communication sometimes beat hub-and-spoke communication.

“In one instance, a cement-factory manager discovered that an impending coal shortage might halt production at his enterprise, so he travelled to the coal mine to solve the problem in person. Several days later, a notice from Project Cybersyn arrived to warn him of a potential coal shortage—a problem that he had already tackled. With such delays, factories didn’t have much incentive to report their data.” Ref. 3

Beer also used the central IT resources to help each factory set production goals, optimise resource use and make investment decisions. So far, the project looks like a central IT function doing what it can to support remote business units. So where did Beer’s cybernetic ideas come in?

The vision of a homeostatic control system for business operations

The Wikipedia entry on project Cybersyn summarizes how Beer designed a nervous system for the Chilean government to monitor and direct the actions of actors in Chile’s nationalised businesses. Beer chose a hierarchical rather than a network design pattern. There would be four levels of control:

· Total

· Sector

· Branch

· Firm

The system prescribed a management hierarchy and some bureaucratic actions expected of managers. So-called “algedonic alerts” would be sent upwards when a resource or performance measure strayed outside a defined range, typically after a timeout. The higher levels would respond by cascading directions downwards to restore the state of business operations to a homeostatic norm.

Managers in an operations room at any level would:

· be notified when a variable in a lower level system moved out of range, for an unacceptable time

· read the report, make a plan, then

· cascade advice and directives using telex messages.

In February 1973, Project Cybersyn delivered the first operational version of the system.

The vision of a big data for central planning

The vision went beyond enabling and coordinating regular business operations. Beer argued that “information is a national resource” and anticipated what we might now call big data.

“At the center of Project Cybersyn” was the Operations Room, where cybernetically sound decisions about the economy were to be made. Those seated in the op room would review critical highlights… from a real-time feed of factory data from around the country.” (Ref. 3)

Data gathered from business operations was to be input into economic simulation software. So, government planners could forecast the possible outcomes of different economic decisions.

Moreover, data would be collected from citizens as well. Around 1970, several thinkers spoke of the imminent collapse of government institutions. Beer believed governments did not have enough variety –enough data to control an economy or society. Project Cyberfolk was to track the real-time happiness of the Chilean nation in response to decisions made in the Operations Room.

“Beer built a device that would enable the country’s citizens, from their living rooms, to move a pointer on a voltmeter-like dial that indicated moods ranging from extreme unhappiness to complete bliss.... so that the total national happiness at any moment in time could be determined... to show whether government policies were working.” (Ref. 3)

Some cyberneticians have promoted a “maximize internal variety” principle.

"Since the variety of perturbations a [control] system can potentially be confronted with is unlimited, we should always try maximize its internal variety (or diversity), so as to be optimally prepared for any foreseeable or unforeseeable contingency." Principia Cybernetica.

This can result in redundant design effort, inefficient system operation and data quality issues. When people come to use the data, they find it is out of date, doesn’t mean what they thought, or is simply inaccurate.

The vision of worker participation in central planning

An aim was to involve workers in planning by applying cybernetics. Was it achieved?

“One of the participating engineers described the factory modelling process as “fairly technocratic” and “top down”. It did not involve “speaking to the guy who was actually working on the mill or the spinning machine.” Ref. 3.

Who defined the target system? Project analysts modelled the processes workers performed and resources they used.

Who monitored workers in the performance of defined processes? In normal operations, factory managers did this. Exception conditions would be reported to a higher-level Ops Room.

Who planned what to do when an algedonic alert was sounded? Those in Ops Room would decide what to do and cascade directions by Telex.

Who made plans about factory expansion or closure, and the national economy? Government planners would do this based on collecting data and using forecasting software.

Of course, people at the higher levels in a bureaucracy always delegate some responsibility to those at lower levels. And it is said that the system in Chile delegated more responsibility to factory managers than the system in the Soviet Union. Still, both were based on the idea of a hierarchical bureaucracy in which each level monitors the values of variables designed to measure lower-level activities.

Workers were expected to perform processes and use resources in ways that had been planned and modelled. Exception conditions would be reported upwards; corrective directives would be cascaded downwards. Bureaucratic feedback loops led from bottom-up reports to top-down directions.

Did this particular application of cybernetic principles herald the advent of a participatory democracy?

“Frustrated with the growing bureaucratization of Project Cybersyn, Beer considered resigning. “If we wanted a new system of government, then it seems that we are not going to get it,” he wrote to his Chilean colleagues that spring [1973]. “The team is falling apart, and descending to personal recrimination.” Confined to the language of cybernetics, Beer didn’t know what to do. (Ref. 3).

Were the difficulties rooted in Beer’s theory or practice?

Ashby’s law does not enable you to control a target system in which every actor is free agent, able to act before or regardless of direction from a controller. Questions you might ask include:

· Is a business a stable homeostat or continually reorganizing itself?

· How far should operations be monitored and regulated from the center?

· What is better controlled and what is better left to evolve naturally?

· Which of infinite possible business state variables need to be monitored?

· Do people in a central control room know how to address deviations from a norm?

· Might regulation be challenged by parallel competing influences?

The main challenge, expressed simply and generally, is not specific to Ashby's law or cybernetics, viz: you cannot control a target that is in reality controlled by other levers, outside your control.

The Nobel prize-winning economist Hayek knew Beer, but they never agreed about planning. In 1974, Hayek gave a famous prize acceptance speech called “The Pretence of Knowledge”. He coined the term “scientistic” meaning “a mechanical and uncritical application of habits of thought to fields different from those in which they have been formed.”

This distillation of Hayek’s “Pretence of Knowledge” speech includes this expression of Hayek’s view.

“Fooled into believing that the measurable variables are the most critical, economists propose “solutions” that actually worsen the problem.”

Did Hayek have had in mind the application of cybernetics to the requirement for worker participation in planning? Is it a coincidence that in a New Yorker article (ref. 3), Morozov concluded the project was utopian and scientistic - the word Hayek had invented?

In 1973, six months after its launch, the project ended when Allende was overthrown and Chilean politics swung away from central planning.

Beer learned from project Cybersyn. He retreated from the world for a while. He polished his ideas about business management, and gathering feedback from workers. He returned to offer the world a richer and more widely interpretable picture of how to run a business.

The Viable System Model (VSM)

The first general system theorist, Bertalanffy, was a biologist, and interested in where systems in other domains can be compared to organisms. Ever since, people have mapped structures or patterns they envisage in softer sciences (sociology, economics or business management) to structures or patterns observed in harder sciences (biology, chemistry or physics).

In Brain of the Firm, Beer presented a Viable System Model (VSM) for the structure of a business and how information flows around it. He dedicated the book to his colleagues with the words "absolutum obsoletum" which he translated as "If it works it’s out of date".

Beer presented the VSM as a) an application of Ashby’s cybernetics and b) isomorphic with the human nervous system. How true those assertions?

The five subsystems of the VSM

The VSM is a complex model. For an illustration, find “Diagnosing the system for organisations” (1985) on the internet and look at Figure 37, or else the exemplar in Wikipedia here.

In essence, the VSM is a structure that divides a business or business unit into five subsystems, each with its own functions. The tabular representation of the VSM below is simplified from the already much simplified list in this Wikipedia entry. Its purpose in this chapter is only to inform the discussion in the next section.

	VSM System	A naïve interpretation
Meta system	S5: makes policy decisions to steer the whole organization and balance demands from different units.	Executive
	S4: looks out to the environment and monitors how the organization must change to remain viable.	Strategic planning and enterprise architecture
	S3: establishes the rules, resources, rights and responsibilities of System 1, and interfaces with Systems 4/5.	Solution architecture and agile development
System	S2: scheduling resources to enable primary activities	Scheduling and operations management
System	S1: the primary/core business activities (each may be described as viable system)	Business operations

Beer was interested in information flows between systems – both between VSM systems at one level of a business, and between levels.

Flows within a level

Beer came from a world of material product manufacture and logistics, in which information systems are seen as distinct from business operations that produce, use and move materials. The distinction is blurred in information processing businesses, like a school, where the primary business operations are the interactions in which teachers and pupils exchange information, in the delivery of lessons and of homework.

Flows between levels

The VSM can be applied to activities at different levels of a business activity composition or decomposition – as may be shown in a hierarchical structure, what business architects call a “functional decomposition diagram”.

If several levels of VSM-conformant organisation are defined, they must be connected by information flows up and down the hiearchy. Remember the four levels of control in project Cybersyn above?

Is such an organization fractal? No. A fractal has two defining characteristics. First it is infinitely high and deep. By contrast, a functional decomposition is finite. It is typically decomposed to down to a 3^rd level, and occasionally down to 5^th or 6^th level.

Second, a fractal looks exactly the same at every level as you zoom in and zoom out. Hierarchical activity decomposition is very different. Every activity in a functional decomposition is unique.

Beer’s use of the biology-sociology analogy

The VSM captures Beer’s insights into business management. The question here is not about those insights, or how the VSM is used; it is about how far the VSM is based in science. Beer followed in the tradition of social systems thinkers who have drawn a biology-sociology analogy

He wrote: "We will seek the source of effective organisation in the cybernetics of natural processes - the brain itself.”

(Did Beer know the brain is modelled as having six layers - as described here <https://en.wikipedia.org/wiki/Cerebral_cortex>? He could not have understood the information flows to/from each layer, because nobody understands them - certainly not well enough to design a comparable system.)

Beer looked beyond the brain, to the human central nervous system. He divided the body into five major components, and divided his VSM into five somewhat analogous components. Below is my attempt to tabulate a mapping.

Human Central Nervous System	Viable System Model
Higher brain: memory, voluntary movement, speech and cognition	S5: defines goals, sets policies, steers the organization in line with goals, and balances demands from different units.
Mid brain: involuntary movement, the eye, auditory and visual processing.	S4: monitors changes in the environment and informs S3 and S5.
Base brain: basic functions like breathing and sleeping	S3: establishes the rules, resources, rights and responsibilities of S1 and S2. S3* monitors and S1 and S2 and reports to S5.
Nervous system: fight, flight and freeze; resting, breeding and digestion.	S2: coordinates primary activities by scheduling and moving resources
Body: organs, sensors and motors	S1: the primary/core business functions or activities needed to serve customers. Each should be a viable system.

Note there are other views of the human nervous system. Some divide it into two connected subsystems - central and peripheral. Others (see table below) divide it into three subsystems, which interact in some functions. The first two can be seen as working in opposition; the third is a semi-autonomous “second brain”.

Structures	Functions
Sympathetic nervous system	mobilizes for intense activity: fight, flight and freeze
Parasympathetic nervous system	dampens activity: resting, digesting and breeding
Enteric nervous system	semi-autonomous “second brain” controls digestion in the gastrointestinal system

How isomorphic are the VSM and HCNS?

Isomorphism means “similar in pattern” - as a photograph is to its negative. Ashby defined two kinds of isomorphism.

First, model-to-machine isomorphism. Like a map is isomorphic to the territory it describes. And like the VSM to a business organization? One may design a business to work according to some interpretation of the VSM, near enough, to claim that kind of isomorphism.

Second, model-to-model isomorphism. Ashby’s exemplified this be comparing two models, one of an electrical circuit and one of a mechanical device. “Two machines are isomorphic if [the model of] one can be made identical to the other by simple relabelling.”

Both the VSM and a model of the nervous system have five named components. But their interconnections don't correspond, and the two cannot be “made identical” as Ashby put it, because the functions of the five components do not correspond.

In the nervous system	In business
The higher brain (5) maintains the memory that guides purposeful activities	S1 and S2 maintain business state data needed to perform purposeful business activities
The base brain (3) controls primitive breathing and sleeping functions.	S3 establishes the business-specific rules, resources, rights and responsibilities of S1.
The nervous system (2) triggers fight, flight or freeze, resting, breeding and digestion, which are generic functions.	S2 schedules the core or primary business-specific activities produce the “value” the customer wants.

For sure, the business functions that Beer positioned in the structure of his VSM can be found in businesses. And information does flow into, around and out of a business. However, Beer’s biology-sociology analogy seems to me a weak device, even for teaching and promotion. Like many analogies, the more you think about it the less convincing it is.

This table lists some contrasts that merit consideration.

In VSM	In biology and/or business
Beer treated the human as his primary exemplar of a viable system.	Biology presents many other viable models tor the survival of an organism - with no central nervous system. E.g. a virus, a tree, an oyster, a bee hive). And for the survival of a species, biology gives us the radically different model of reproduction and cross-generation change.
People say the VSM can be used to design a fractal organisation	Neither biological organisms nor business organizations are fractal. Components at different levels of granularity (body, organs, cells) have different structures and behaviors.
People use a school timetable to illustrate coordination of activities by S2.	Coordination of activities in the body is by message passing, not by timetabling, by co-locating independent actors in time and space.
The mapping of system functions to people or organization units can be many to many	In biology, logical functions (e.g. breathing) are mapped physical structures (e.g lungs). There is very little sharing of a function between different physical structures
The VSM presumes a business survives in a changing world by using information feedback loops for both homeostatic and evolutionary change.	In biology, homeostasis works that way, but inter-generational evolution in a changing world works differently – by trial and error. Moreover, every organism dies to make room for its descendants!
The VSM features homeostatic adaptation – to regulate business operations.	A business may aim to grow indefinitely, diversify, and change the variables it measures itself by.
The VSM features evolutionary change Its “brain” defines and changes the “body’s” structures and functions.	In biology, the structure and behaviors of an organism emerge inexorably from bottom-up self-assembly and self-organization. The body’s structures (e.g. kidney and liver) are fixed, and their functions are fixed. Inter-generational change is steered by changes in the environment, rather than the brain.
S1 and S2 hold the memory of models of things the business monitors and directs. Regular business operations are performed without involving the “brain”.	The higher brain (system 5) holds a memory of things the body must monitor and direct. Regular human activities do involve the higher brain (system 5\|), and its memory. A human with no higher brain is vegetative and cannot (for example) feed themselves.
S5 as in human biology, is where cognition and conscious decision-making functions occur.	Surely a business needs S3 and S4 to have cognition and conscious decision-making functions? independently of system S5?
Like Descartes, Beer viewed the mind as the center of a nested mind-body-environment system.	Biologists today see the mind as inseparable from the body. The position called “cognitive embodiment” sees mental states and activities as being bodily states.
Beer seemed to focus on the sympathetic nervous system.	The VSM appears to have no equivalent to other nervous system structures. In which case, in what sense can it be called the viable system model?

Conclusions and remarks

“Few organizations have adopted the VSM as their formal organizational structure. But many consultants have used it to diagnose the way an organization is operating and where improvements are needed.” (Stuart Umpleby).

Some do find the VSM useful as tool to make "interventions" in the structures and operations of a business. The questions posed in this chapter are different.

Did Beer succeed in applying Ashby’s cybernetics to a nation's economy? This chapter suggests the success of project Cybersyn is questionable.

Does Beer’s VSM for the management of a business reflect the structure of the human nervous system? This chapter points to several differences. Other chapters have shown the analogy between a business organization and a biological organism is misleading. Drawing an analogy between social and biological phenomena to explain what can be justified by evidence or logic within the softer science is fine. Using it as the explanation or justification is problematic.

More generally, is the VSM scientific? A scientific theory is falsifiable. So, can we falsify the statement that "a viable business organization must have elements that perform the functions of the 5 VSM subystems”?

The application of science to social entities is always challenging. Let X be a business, or a primary activity of one, can you measure

· V, the viability of X (regardless of the VSM)?

· E, the presence and effect of a VSM subsystem on V?

· EV, the effectiveness required to increase V?

Can you demonstrate that any increase in V is not the result of the Hawthorne effect? Or that a business without VSM subsystems of required effectiveness is not viable?

“There are limits to what science and the scientific method can achieve. In particular, studying society generally shows how difficult it is to control. This truth may disappoint those who want to build a science to shape society. But the scientific method is not a recipe that can be mechanically applied to all situations.” From this distillation of Hayek’s “Pretence of Knowledge” speech

What did Beer say?

“There is no 'correct' interpretation of the VSM. We have spoken instead of more or less useful interpretations.” (Beer)

If any interpretation of the VSM that works is valid, and by implication, any interpretation that doesn't work is invalid, then the VSM is unfalsifiable.

It seems to me the success or failure of the VSM lies more in the experience and intuitions of its creator and users. Its usefulness is down to the experience of Beer as a manager, and of consultants who use it, rather than Ashby’ cybernetics or any model of the human nervous system.

Appendix: The New Yorker article

The Planning Machine: Project Cybersyn and the origins of the Big Data nation

In Allende’s Chile, a futuristic op room was to bring socialism into the computer age. In June, 1972, Ángel Parra, Chile’s leading folksinger, wrote a song titled “Litany for a Computer and a Baby About to Be Born.” Computers are like children, he sang, and Chilean bureaucrats must not abandon them. The song was prompted by a visit to Santiago from a British consultant who, with his ample beard and burly physique, reminded Parra of Santa Claus—a Santa bearing a “hidden gift, cybernetics.”

The consultant, Stafford Beer, had been brought in by Chile’s top planners to help guide the country down what Salvador Allende, its democratically elected Marxist leader, was calling “the Chilean road to socialism.” Beer was a leading theorist of cybernetics—a discipline born of midcentury efforts to understand the role of communication in controlling social, biological, and technical systems. Chile’s government had a lot to control: Allende, who took office in November of 1970, had swiftly nationalized the country’s key industries, and he promised “worker participation” in the planning process. Beer’s mission was to deliver a hypermodern information system that would make this possible, and so bring socialism into the computer age. The system he devised had a gleaming, sci-fi name: Project Cybersyn.

Beer was an unlikely savior for socialism. He had served as an executive with United Steel and worked as a development director for the International Publishing Corporation (then one of the largest media companies in the world), and he ran a lucrative consulting practice. He had a lavish life style, complete with a Rolls-Royce and a grand house in Surrey, which was fitted out with a remote-controlled waterfall in the dining room and a glass mosaic with a pattern based on the Fibonacci series. To convince workers that cybernetics in the service of the command economy could offer the best of socialism, a certain amount of reassurance was in order. In addition to folk music, there were plans for cybernetic-themed murals in the factories, and for instructional cartoons and movies. Mistrust remained. “Chile Run by Computer,” a January, 1973, headline in the Observer announced, shaping the reception of Beer’s plan in Britain.

At the center of Project Cybersyn (for “cybernetics synergy”) was the Operations Room, where cybernetically sound decisions about the economy were to be made. Those seated in the op room would review critical highlights—helpfully summarized with up and down arrows—from a real-time feed of factory data from around the country. The prototype op room was built in downtown Santiago, in the interior courtyard of a building occupied by the national telecom company. It was a hexagonal space, thirty-three feet in diameter, accommodating seven white fibreglass swivel chairs with orange cushions and, on the walls, futuristic screens. Tables and paper were banned. Beer was building the future, and it had to look like the future.

That was a challenge: the Chilean government was running low on cash and supplies; the United States, dismayed by Allende’s nationalization campaign, was doing its best to cut Chile off. And so a certain amount of improvisation was necessary. Four screens could show hundreds of pictures and figures at the touch of a button, delivering historical and statistical information about production—the Datafeed—but the screen displays had to be drawn (and redrawn) by hand, a job performed by four young female graphic designers. Given Beer’s plans to build an entire “factory to turn out operations rooms”—every state-run industrial concern was to have one—Project Cybersyn could at least provide graphic designers with full employment.

Beer, who was fond of cigars and whiskey, made sure that an ashtray and a small holder for a glass were built into one of the armrests for each chair. (Sometimes, it seemed, the task of managing the economy went better with a buzz on.) The other armrest featured rows of buttons for navigating the screens. In addition to the Datafeed, there was a screen that simulated the future state of the Chilean economy under various conditions. Before you set prices, established production quotas, or shifted petroleum allocations, you could see how your decision would play out.

One wall was reserved for Project Cyberfolk, an ambitious effort to track the real-time happiness of the entire Chilean nation in response to decisions made in the op room. Beer built a device that would enable the country’s citizens, from their living rooms, to move a pointer on a voltmeter-like dial that indicated moods ranging from extreme unhappiness to complete bliss. The plan was to connect these devices to a network—it would ride on the existing TV networks—so that the total national happiness at any moment in time could be determined. The algedonic meter, as the device was called (from the Greek algos, “pain,” and hedone, “pleasure”), would measure only raw pleasure-or-pain reactions to show whether government policies were working.

Project Cybersyn can also be viewed as a dispatch from the future. These days, business publications and technology conferences endlessly celebrate real-time dynamic planning, the widespread deployment of tiny but powerful sensors, and, above all, Big Data—an infinitely elastic concept that, according to some inexorable but yet unnamed law of technological progress, packs twice as much ambiguity in the same two words as it did the year before. In many respects, Beer’s cybernetic dream has finally come true: the virtue of collecting and analyzing information in real time is an article of faith shared by corporations and governments alike.

Beer was invited to Chile by a twenty-eight-year-old technocrat named Fernando Flores, whom Allende had appointed to the state development agency. The agency, a stronghold of Chilean technocracy, was given the task of administering the newly nationalized enterprises. Flores was undeterred by Beer’s lack of socialist credentials. He saw that there was a larger intellectual affinity between socialism and cybernetics; in fact, both East Germany and the Soviet Union considered, though never actually built, projects similar to Cybersyn.

As Eden Medina shows in “Cybernetic Revolutionaries,” her entertaining history of Project Cybersyn, Beer set out to solve an acute dilemma that Allende faced. How was he to nationalize hundreds of companies, reorient their production toward social needs, and replace the price system with central planning, all while fostering the worker participation that he had promised? Beer realized that the planning problems of business managers—how much inventory to hold, what production targets to adopt, how to redeploy idle equipment—were similar to those of central planners. Computers that merely enabled factory automation were of little use; what Beer called the “cussedness of things” required human involvement. It’s here that computers could help—flagging problems in need of immediate attention, say, or helping to simulate the long-term consequences of each decision. By analyzing troves of enterprise data, computers could warn managers of any “incipient instability.” In short, management cybernetics would allow for the reëngineering of socialism—the command-line economy.

To take advantage of automated computer analysis, managers would need to get a clear view of daily life inside their own firm. First, they would have to locate critical bottlenecks. They needed to know that if trucks arrived late at Plant A, then Plant B wouldn’t finish the product by its deadline. Why would the trucks be late? Well, the drivers might be on strike, or lousy weather might have closed the roads. Workers, not managers, would have the most intimate knowledge of these things.

When Beer was a steel-industry executive, he would assemble experts—anthropologists, biologists, logicians—and dispatch them to extract such tacit knowledge from the shop floor. The goal was to produce a list of relevant indicators (like total gasoline reserves or delivery delays) that could be monitored so that managers would be able to head off problems early. In Chile, Beer intended to replicate the modelling process: officials would draw up the list of key production indicators after consulting with workers and managers. “The on-line control computer ought to be sensorily coupled to events in real time,” Beer argued in a 1964 lecture that presaged the arrival of smart, net-connected devices—the so-called Internet of Things. Given early notice, the workers could probably solve most of their own problems. Everyone would gain from computers: workers would enjoy more autonomy while managers would find the time for long-term planning. For Allende, this was good socialism. For Beer, this was good cybernetics.

Cybernetics was born in the mid-nineteen-forties, as scholars in various disciplines began noticing that social, natural, and mechanical systems exhibit similar patterns of self-regulation. Norbert Wiener’s classic “Cybernetics; or, Control and Communication in the Animal and the Machine” (1948) discussed human behavior by drawing on his close observation of technologies like the radar and the thermostat. The latter is remarkable for how little it needs to know in order to do its job. It doesn’t care whether what’s making the room so hot is your brand-new plasma TV or the weather outside. It just needs to compare its actual output (the temperature right now) with its predefined output (the desired temperature) and readjust its input (whatever mechanism is producing heat or cold).

Wiener held that a patient suffering from purpose tremor—spilling a glass of water before raising it to his lips—was akin to a malfunctioning thermostat. Both rely on “negative feedback”—“negative” because it tends to oppose what the system is doing. In a way, our bodies are feedback machines: we maintain our body temperature without a specially programmed response for “condition: bathhouse” or “condition: tundra.” The tendency to self-adjust is known as homeostasis, and it’s ubiquitous in both the natural and the mechanical worlds. For Beer, in fact, corporations are homeostats. They have a clear goal—survival—and are full of feedback loops: between the company and its suppliers or between workers and management. And if we can make homeostatic corporations why not homeostatic governments

Yet central planning had been powerfully criticized for being unresponsive to shifting realities, notably by the free-market champion Friedrich Hayek. The efforts of socialist planners, he argued, were bound to fail, because they could not do what the free market’s price system could: aggregate the poorly codified knowledge that implicitly guides the behavior of market participants. Beer and Hayek knew each other; as Beer noted in his diary, Hayek even complimented him on his vision for the cybernetic factory, after Beer presented it at a 1960 conference in Illinois. (Hayek, too, ended up in Chile, advising Augusto Pinochet.) But they never agreed about planning. Beer believed that technology could help integrate workers’ informal knowledge into the national planning process while lessening information overload.

Project Cybersyn, to be sure, lacked the gizmos available to contemporary organizations. When Beer landed in Santiago, he had access only to two mainframe computers, which the government badly needed for other tasks. Beer chose the “cloud” model: one central computer, analyzing reports sent by telex machines installed at state-run factories, could inform the firm of emerging problems and, if nothing was done, alert agency officials.

But computer analysis of factories was only as good as the underlying formal model of how they actually work. Hermann Schwember, a senior member of Cybersyn, described the process in a 1977 essay. The modelling team dispatched to a canning plant, for example, would start with a list of technical questions. What supplies—tin cans, sugar, fruit—were critical to its over-all activity? Were there statistics—say, the amount of peeled fruit, the number of cans in the factory line—that offered an accurate snapshot of the state of production? Were there any machines that might automatically provide the indicators sought by the team (the counter of the sealing unit, perhaps)? The answers would yield a flowchart that started with suppliers and ended with customers.

Suppose that the state planners wanted the plant to expand its cooking capacity by twenty per cent. The modelling would determine whether the target was plausible. Say the existing boiler was used at ninety per cent of capacity, and increasing the amount of canned fruit would mean exceeding that capacity by fifty per cent. With these figures, you could generate a statistical profile for the boiler you’d need. Unrealistic production goals, overused resources, and unwise investment decisions could be dealt with quickly. “It is perfectly possible . . . to capture data at source in real time, and to process them instantly,” Beer later noted. “But we do not have the machinery for such instant data capture, nor do we have the sophisticated computer programs that would know what to do with such a plethora of information if we had it.”

Today, sensor-equipped boilers and tin cans report their data automatically, and in real time. And, just as Beer thought, data about our past behaviors can yield useful predictions. Amazon recently obtained a patent for “anticipatory shipping”—a technology for shipping products before orders have even been placed. Walmart has long known that sales of strawberry Pop-Tarts tend to skyrocket before hurricanes; in the spirit of computer-aided homeostasis, the company knows that it’s better to restock its shelves than to ask why.

Governments, with oceans of information at their disposal, are following suit. That’s evident from an essay on the “data-driven city,” by Michael Flowers, the former chief analytics officer of New York City, which appears in “Beyond Transparency: Open Data and the Future of Civic Innovation,” a recent collection of essays (published, tellingly, by the Code for America Press), edited by Brett Goldstein with Lauren Dyson. Flowers suggests that real-time data analysis is allowing city agencies to operate in a cybernetic manner. Consider the allocation of building inspectors in a city like New York. If the city authorities know which buildings have caught fire in the past and if they have a deep profile for each such building—if, for example, they know that such buildings usually feature illegal conversions, and their owners are behind on paying property taxes or have a history of mortgage foreclosures—they can predict which buildings are likely to catch fire in the future and decide where inspectors should go first. The appeal of this approach to bureaucrats is fairly obvious: like Beer’s central planners, they can be effective while remaining ignorant of the causal mechanisms at play. “I am not interested in causation except as it speaks to action,” Flowers told Kenneth Cukier and Viktor Mayer-Schönberger, the authors of “Big Data” (Houghton Mifflin), another recent book on the subject. “Causation is for other people, and frankly it is very dicey when you start talking about causation. . . . You know, we have real problems to solve.”

In another contribution to “Beyond Transparency,” the technology publisher and investor Tim O’Reilly, one of Silicon Valley’s in-house intellectuals, celebrates a new mode of governance that he calls “algorithmic regulation.” The aim is to replace rigid rules issued by out-of-touch politicians with fluid and personalized feedback loops generated by gadget-wielding customers. Reputation becomes the new regulation: why pass laws banning taxi-drivers from dumping sandwich wrappers on the back seat if the market can quickly punish such behavior with a one-star rating? It’s a far cry from Beer’s socialist utopia, but it relies on the same cybernetic principle: collect as much relevant data from as many sources as possible, analyze them in real time, and make an optimal decision based on the current circumstances rather than on some idealized projection. All that’s needed is a set of fibreglass swivel chairs.

Chilean politics, as it happened, was anything but homeostatic. Cybernetic synergy was a safe subject for the relatively calm first year of Allende’s rule: the economy was growing, social programs were expanding, real wages were improving. But the calm didn’t last. Allende, frustrated by the intransigence of his parliamentary opposition, began to rule by executive decree, prompting the opposition to question the constitutionality of his actions. Workers, too, began to cause trouble, demanding wage increases that the government couldn’t deliver. Washington, concerned that the Chilean road to socialism might have already been found, was also meddling in the country’s politics, trying to thwart some of the announced reforms.

In October, 1972, a nationwide strike by truck drivers, who were fearful of nationalization, threatened to paralyze the country. Fernando Flores had the idea of deploying Cybersyn’s telex machines to outmaneuver the strikers, encouraging industries to coördinate the sharing of fuel. Most workers declined to back the strike and sided with Allende, who also invited the military to join the cabinet. Flores was appointed Minister of Economics, the strike petered out, and it seemed that Project Cybersyn would win the day.

On December 30, 1972, Allende visited the Operations Room, sat in one of the swivel chairs, and pushed a button or two. It was hot, and the buttons didn’t show the right slides. Undaunted, the President told the team to keep working. And they did, readying the system for its official launch, in February, 1973. By then, however, long-term planning was becoming something of a luxury. One of Cybersyn’s directors remarked at the time that “every day more people wanted to work on the project,” but, for all this manpower, the system still failed to work in a timely manner. In one instance, a cement-factory manager discovered that an impending coal shortage might halt production at his enterprise, so he travelled to the coal mine to solve the problem in person. Several days later, a notice from Project Cybersyn arrived to warn him of a potential coal shortage—a problem that he had already tackled. With such delays, factories didn’t have much incentive to report their data.

One of the participating engineers described the factory modelling process as “fairly technocratic” and “top down”—it did not involve “speaking to the guy who was actually working on the mill or the spinning machine.” Frustrated with the growing bureaucratization of Project Cybersyn, Beer considered resigning. “If we wanted a new system of government, then it seems that we are not going to get it,” he wrote to his Chilean colleagues that spring. “The team is falling apart, and descending to personal recrimination.” Confined to the language of cybernetics, Beer didn’t know what to do. “I can see no way of practical change that does not very quickly damage the Chilean bureaucracy beyond repair,” he wrote.

It was Allende’s regime itself that was soon damaged beyond repair. Pinochet had no need for real-time centralized planning; the market was to replace it. When Allende’s regime was overthrown, on September 11, 1973, Project Cybersyn met its end as well. Beer happened to be out of the country, but others weren’t so lucky. Allende ended up dead, Flores in prison, other Cybersyn managers in hiding. The Operations Room didn’t survive, either. In a fit of what we might now call PowerPoint rage, a member of the Chilean military stabbed its slides with a knife.

Today, one is as likely to hear about Project Cybersyn’s aesthetics as about its politics. The resemblance that the Operations Room—with its all-white, utilitarian surfaces and oversized buttons—bears to the Apple aesthetic is not entirely accidental. The room was designed by Gui Bonsiepe, an innovative German designer who studied and taught at the famed Ulm School of Design, in Germany, and industrial design associated with the Ulm School inspired Steve Jobs and the Apple designer Jonathan Ive.

But Cybersyn anticipated more than tech’s form factors. It’s suggestive that Nest—the much admired smart thermostat, which senses whether you’re home and lets you adjust temperatures remotely—now belongs to Google, not Apple. Created by engineers who once worked on the iPod, it has a slick design, but most of its functionality (like its ability to learn and adjust to your favorite temperature by observing your behavior) comes from analyzing data, Google’s bread and butter. The proliferation of sensors with Internet connectivity provides a homeostatic solution to countless predicaments. Google Now, the popular smartphone app, can perpetually monitor us and (like Big Mother, rather than like Big Brother) nudge us to do the right thing—exercise, say, or take the umbrella.

Companies like Uber, meanwhile, insure that the market reaches a homeostatic equilibrium by monitoring supply and demand for transportation. Google recently acquired the manufacturer of a high-tech spoon—the rare gadget that is both smart and useful—to compensate for the purpose tremors that captivated Norbert Wiener. (There is also a smart fork that vibrates when you are eating too fast; “smart” is no guarantee against “dumb.”) The ubiquity of sensors in our cities can shift behavior: a new smart parking system in Madrid charges different rates depending on the year and the make of the car, punishing drivers of old, pollution-prone models. Helsinki’s transportation board has released an Uber-like app, which, instead of dispatching an individual car, coördinates multiple requests for nearby destinations, pools passengers, and allows them to share a much cheaper ride on a minibus.

Such experiments, however, would be impossible without access to the underlying data, and companies like Uber typically want to grab and hold as much data as they can. When, in 1975, Beer argued that “information is a national resource,” he was ahead of his time in treating the question of ownership—just who gets to own the means of data production, not to mention the data?—as a political issue that cannot be reduced to its technological dimensions.

Uber says that it can monitor its supply-and-demand curves in real time. Instead of sticking to fixed rates for car rides, it can charge a floating rate depending on market conditions when an order is placed. As Uber’s C.E.O. told Wired last December, “We are not setting the price. The market is setting the price. We have algorithms to determine what that market is.” It’s a marvellous case study in Cybersyn capitalism. And it explains why Uber’s prices tend to skyrocket in inclement weather. (The company recently agreed to cap these hikes in American cities during emergencies.) Uber maintains that surge pricing allows it to get more drivers onto the road in dismal weather conditions. This claim would be stronger if there were a way to confirm its truth by reviewing the data. But at Uber, as at so many tech companies, what happens in the op room stays in the op room.

Stafford Beer was deeply shaken by the 1973 coup, and dedicated his immediate post-Cybersyn life to helping his exiled Chilean colleagues. He separated from his wife, sold the fancy house in Surrey, and retired to a secluded cottage in rural Wales, with no running water and, for a long time, no phone line. He let his once carefully trimmed beard grow to Tolstoyan proportions. A Chilean scientist later claimed that Beer came to Chile a businessman and left a hippie. He gained a passionate following in some surprising circles. In November, 1975, Brian Eno struck up a correspondence with him. Eno got Beer’s books into the hands of his fellow-musicians David Byrne and David Bowie; Bowie put Beer’s “Brain of the Firm” on a list of his favorite books.

Isolated in his cottage, Beer did yoga, painted, wrote poetry, and, occasionally, consulted for clients like Warburtons, a popular British bakery. Management cybernetics flourished nonetheless: Malik, a respected consulting firm in Switzerland, has been applying Beer’s ideas for decades. In his later years, Beer tried to re-create Cybersyn in other countries—Uruguay, Venezuela, Canada—but was invariably foiled by local bureaucrats. In 1980, he wrote to Robert Mugabe, of Zimbabwe, to gauge his interest in creating “a national information network (operating with decentralized nodes using cheap microcomputers) to make the country more governable in every modality.” Mugabe, apparently, had no use for algedonic meters.

Fernando Flores moved in the opposite direction. In 1976, an Amnesty International campaign secured his release from prison, and he ended up in California, at Berkeley, studying the ideas of Martin Heidegger and J. L. Austin and writing a doctoral thesis on business communications in the office of the future. In California, Flores reinvented himself as a business consultant and a technology entrepreneur. (In the early nineteen-eighties, Werner Erhard, the founder of est, was among his backers.) Flores reëntered Chilean politics and was elected a senator in 2001. Toying with the idea of running for President, he eventually launched his own party and found common ground with the right.

Before designing Project Cybersyn, Beer used to complain that technology “seems to be leading humanity by the nose.” After his experience in Chile, he decided that something else was to blame. If Silicon Valley, rather than Santiago, has proved to be the capital of management cybernetics, Beer wasn’t wrong to think that Big Data and distributed sensors could be enlisted for a very different social mission. While cybernetic feedback loops do allow us to use scarce resources more effectively, the easy availability of fancy thermostats shouldn’t prevent us from asking if the walls of our houses are too flimsy or if the windows are broken. A bit of causal thinking can go a long way. For all its utopianism and scientism, its algedonic meters and hand-drawn graphs, Project Cybersyn got some aspects of its politics right: it started with the needs of the citizens and went from there. The problem with today’s digital utopianism is that it typically starts with a PowerPoint slide in a venture capitalist’s pitch deck. As citizens in an era of Datafeed, we still haven’t figured out how to manage our way to happiness. But there’s a lot of money to be made in selling us the dials.