A Constructivist’s View of POSIWID:

POSIWID or “Purpose Of a System Is What It Does” is a famous dictum in Cybernetics. This is attributed to the Management Cybernetician Stafford Beer. Beer noted:

A good observer will impute the purpose of the system from its actions and thus from the resultant state.

Hence the key aphorism:

The purpose of a system is what it does.

There is, after all, no point in claiming that the purpose of a system is to do what it consistently fails to do.

I have written about this before here – https://harishsnotebook.wordpress.com/2019/02/18/purpose-of-a-system-in-light-of-vsm/ and here – https://harishsnotebook.wordpress.com/2020/06/14/hegel-dialectics-and-posiwid/

In cybernetics, the emphasis is on what a “system” does, and not especially what a “system” is, or what the designer or management of the “system” claims what the “system” is doing. Thus, we can see that POSIWID has a special place in every cybernetician’s mind. A “system” is a collection of variables that an observer purposefully selects to make sense of the world around them. The boundaries, parts etc. of the “system” vary according to who is doing the observing, and the purpose also is assigned by the observer. Beer explains this clearly:

The point that I find that I am most anxious to add is that this System has a PURPOSE. The trouble is: WHO SAYS SO?

So where does the idea that Systems in general have a purpose come from? IT COMES FROM YOU!

 It is you the observer of the System who recognizes its purpose. Come to think of it, then, is it not just YOU — the observer — who recognizes that there is a System in the first place?

Another key point to mention is that an observer may impute several purposes for the “system”. Beer continues:

Consider the System called a tiger…

The purpose of a tiger is:

  • to be itself
  • to be its own part of the Jungle System
  • to be a link in animal evolution
  • to eat whatever it eats, for Ecology’s sake
  • to provide tiger-skins
  • to perpetuate the genes of which it is the host

For the moment, I am prepared to say that the purpose of a tiger is to demonstrate that the recognition of a System and of its purpose is a highly subjective affair.

Understanding the purpose of a “system” helps us in understanding how we construct the “systems” themselves:

All of this turns out to mean that we simply cannot attribute purposes, or even boundaries, to systems as if these were objective facts of nature. The facts about the system are in the eye of the beholder. This sounds like an unproductive conclusion, but we can make something of it. It means that both the nature and the purpose of a System are recognized by an observer within his perception of WHAT THE SYSTEM DOES.

From Beer’s writing, it is clear that the POSIWID is dependent upon the observer. This is also the basis of constructivism. In constructivism, the observer is the king or queen. The “system” is a selection of variables chosen by the observer to improve their understanding of a phenomenon. The boundaries drawn by the observer are entirely arbitrary and contingent on the mood of the observer. A “system” is thus a mental construct of the observer. For example, an educational “system” may have physical artifacts in the world such as buildings, books, chalk boards etc. However, depending upon the observer, what the “system” entails will change. For a student, it is “system” for education, or it is a “system” to get away from their hometown. For a teacher, it is a “system” to provide meaning to their lives or it is a “system” to spend time while doing another job on the side. There can be as many “systems” involving the same collection of parts as the number of the observers. Beer continues:

The definition of the purpose of a System as being what it does lays the onus not on ‘nature’ but on the particular observer concerned. It immediately accounts for UNRESOLVABLE disagreements about systems too. For two people may well disagree about anything at all, and never become reconciled. They say that they will be convinced, and give way, if the FACTS show that they were mistaken. But the facts about the nature and purpose of a System are not objective realities. Once you have declared, as an observer, what the facts are, the nature and purpose of the System observed are ENTAILED.

As a constructivist, this is an important concept to grasp. If there are two observers and each is constructing the “system”, they each will come up with their own “systems” and varying POSIWIDs. Our first step in Systems Thinking then is to understand how the other participants view the “system” as, their assigned purposes, and how they see the POSIWIDs as. Even if they assign a purpose for the “system”, the outcome that they perceive may not match what they expect. I have come to take away some important points from our discussion so far:

  1. There are always multiple participants in the social realm. It is very important to understand what the “system” means for each stakeholder. This includes the parts, the whole, the assigned purposes and the POSIWIDs. There is no POSIWID(s) without an observer.
  2. It is important to understand that there is always a gap between what we believe the purpose(s) of a “system” should be, and what it actually is doing. It is tempting to assign an objective reality to the “IT” here. We should resist this temptation and understand that the “IT” or the “system” is an “as-if” model or abstraction that we employ to make sense.
  3. To carry on from the previous point, in order to understand the gap, we need good comparators in place to allow us to measure what the gap between the expected and actual is. POSIWIDs are entirely dependent upon the variety of the observer to distinguish what is happening. A good example to point this out further will be to take the cliché fictional example of Sherlock Holmes and Inspector Lestrade. Holmes, the master observer, is able to distinguish much more attributes than Inspector Lestrade, which would correlate to more POSIWIDs.
  4. On a similar note, what we perceive as the “system” is doing could be faulty. This means that we need an ongoing error correction step to improve our ability to manage the “system”. We need to interact with the “system” as much as possible, and also welcome input from other participants and their perspectives. We cannot manage a “system” unless we are a part of the “system”. We should embrace and own our epistemic humility.
  5. The POSIWID(s) should be reinterpreted as often as possible, with input from others. They help us understand the dynamics of the various parts and how they interact with each other.
  6. We should focus on only a few POSIWIDs at a time. Since we lack the variety to manage all the external variety thrown at us, we should attenuate and filter out the unwanted POSIWIDs.
  7. We cannot predict what the POSIWID(s) will be beforehand. Due to complexity of connections between the parts, and the nonlinear relations between them, POSIWIDs are more likely to be unpredictable. This is another reason we should resist the temptation to treat “systems” as objective realities in the world.

One of the main struggles I had when I started my journey into constructivism is how we can manage a “system” if it is entirely “subjective”? I have put the term subjective in quotes because there is no subject/object distinction in constructivism. I will write more on this later. For the moment, I will carry on with the use of the term “subjective”. Beer explained this well:

‘How is it that systems are subjective, while some of them can be singled out and declared to be viable?’

‘Once you have defined them, you can tell whether they are viable or not.’

‘And those criteria are suddenly supposed to be objective?’

‘Well, it’s all about necessity and sufficiency within a stated frame of reference.’

if systems are subjective phenomena, then we are going to have trouble in determining a measure. The whole idea of measures is to be objective… Yet the problem we face is not unique. In fact, the measures that we are accustomed to call objective work only because we accept a set of conventions about how they are to be employed. For example, if we quote the height of Mount Everest, we do not mean that this is the distance you would travel from the base camp to climb it; nor do we mean that if we look at Mount Everest while holding a ruler at arm’s length, we can read off its height. We might have agreed on either of these conventions: they would both work, given certain other stateable conditions. It seems that objective measures, like objective systems, exist only as conventional crystallizations of one out of a virtually infinite number of subjective possibilities.

Stay safe and always keep on learning…

In case you missed it, my last post was Systems in Quotes vs. Systems Without Quotes:

Source: The Heart of Enterprise (Stafford Beer, 1979)


The Cybernetics of “Here & Now” and “There & Then”:

In today’s post, I am looking at difference. Difference is a big concept in Cybernetics. As Ross Ashby noted:

The most fundamental concept in cybernetics is that of “difference”, either that two things are recognizably different or that one thing has changed with time.

In Cybernetics, the goal is to eliminate the difference. If we take an example of a steersman on a boat, they are continuously trying to correct their course so that they can reach their destination correctly. The course has set the path, and any difference due to environmental conditions or other things will need to be corrected. This is a negative feedback cycle, where the current value is compared against a set value, and any difference will trigger an action from the steersman. If the steersman has enough variety, in terms of experience or technology, they can easily correct the difference.

We can see from the example that there has to be a set value so that the current value can be compared against it. This comparison has to be either continuous (if possible) or as frequent as possible to allow the steersman to be control the external variety. If the steersman is not able to steer the boat to be in a “zone of safety”, they will lose control of the boat. If the feedback is received in long intervals, the steersman will not be effective in steering the boat. This basic idea can be applied to all sorts of situations. Basically, we identify a goal value, and then have processes in place to ensure that the “system” of interest is kept with in an allowable range of the goal value. From this standpoint, we can identify a problem as the difference of the goal value and the current value. When this difference is beyond an allowable value, we have to initiate an action that will bring the system back into the tolerable range.

This discussion points to the importance of maintaining the system between the viable range for selected essential variables. These could be the number of sales or rate of employee retention for an organization. This is about the ongoing survival by keeping the organization viable. We can see that this is a homeostatic type loop about the “here and now” for the organization, where selected essential variables are kept within a tolerance range. As noted before, this loop has to be either continuous if possible, or as frequent as possible.

What we have discussed does not address how an organization can grow. Our discussion has been about how to keep the organization surviving. Now we will look at the cybernetics of growth, which is also an important aspect for viability of an organization. For the growth part, similar to the first loop, we need a second loop where the goal value is an ideal state. This ideal state is “there and then” for the organization. This is a long-term goal for the organization, and unlike the homeostatic loop, this second loop does not have to be continuous or frequent. This second loop utilizes more infrequent comparisons. The emphasis is still keeping the essential variables in check by frequently keeping an eye on what is going on here and now, while at the same time looking out into the near future (“there and then”) infrequently. I encourage the reader to look into Stafford Beer’s VSM model that looks at the “here and now” and “there and then” ideas to ensure viability of an organization. I have written an introduction to VSM here.

For some of the readers, this might remind you of the Roman God, Janus. Janus has two heads, looking in opposite directions. He is viewed as the God of change or transitions sometimes depicted as having one head looking into the past/current, while the other head looking into the future.

This may be paradoxical for some readers. In order to be adaptive, maintaining the status quo is very important. A smaller frequent feedback loop for status quo, and a larger infrequent loop for adjusting the course into the future is needed for viability. The idea of the two self-correcting loops goes back to Ross Ashby. I have written about it here.

A keen reader might see traces of Chris Argyris and Donald Schon’s “double loop” learning here. That is the case because Argyris and Schon were inspired by Ashby. They note the following in Organizational Learning II:

We borrow the distinction between single- and double-loop learning from W. Ross Ashby’s ‘Design for a Brain’. Ashby formulates his distinction in terms of (a) the adaptive behavior of a stable system, “the region of stability being the region of the phase space in which all the essential variables lie within their normal limits,” and (b) a change in the value of an effective parameter, which changes the field within which the system seeks to maintain its stability. One of Ashby’s examples is the behavior of a heating or cooling system governed by a thermostat. In an analogy to single-loop learning, the system changes the values of certain variables (for example, the opening or closing of an air valve) in order to keep temperature within the limits of a setting. Double-loop learning is analogous to the process by which a change in the setting induces the system to maintain temperature within the range specified by a new setting.

Please maintain social distance, wear masks and take vaccination, if able. Stay safe and always keep on learning…

In case you missed it, my last post was The Cybernetics of Bayesian Epistemology:

Purpose of a System in Light of VSM:

Varieties 2

In today’s post, I am looking at the concept of POSIWID (“Purpose Of a System Is What It Does”) Please note that VSM stands for “Viable System Model” and not “Value Stream Mapping”.

The idea of POSIWID was put forth by the father of Management Cybernetics, Stafford Beer. As Beer puts it: [1]

A good observer will impute the purpose of a system from its actions… There is, after all, no point in claiming that the purpose of a system is to do what it consistently fails to do.

An organization is a sociotechnical and complex system. This means that it cannot be controlled by simple edicts that are put top down from the management. We should not go by what the “designer” of the system says it does, we should impute the purpose from what the system actually does.

A good explanation comes from Dan Lockton: [2]

The implication of a posiwid approach is that it doesn’t matter why a system was designed, or whether the intention was to influence behavior or not. All that matters are the effects: if a design leads to people behaving in a different way, then that is the ‘purpose’ of the design. Intentionality is irrelevant: to understand the behavior of systems, we need to look at their effects… Essentially, a posiwid approach means that both `positive’ and `negative’ effects of a system must be dealt with. We might try to dismiss unintended effects, but they are still effects, and we need to recognize them, and deal with them. Undesirable phenomena are not simply blemishes they are [the system’s] outputs (Beer, 1974, p.7).

A general interpretation of an organization’s purpose is – to make money. This is the idea proposed by Eliyahu Goldratt in his famous book – The Goal. However, Beer’s view of the goal of an organization is to stay viable. Beer defines “viable” as “able to maintain a separate existence”. He identifies all organizations as viable systems. He was inspired by the human anatomy. He realized that the viable systems are recursive. In other words, Every viable system contains viable systems and is contained in a viable system. For example, a human being is a viable system, who is part of an assembly line which is also a viable system. This assembly line in turn is a part of a Value stream, which is again a viable system. This goes on and on. Beer developed Viable System Model (VSM) by exploring the necessary and sufficient conditions for viability in any complex system whether an organism, an organization or a country. 

There are three elements to a viable system:

  • The Operation – This is similar to the muscles and organs. This is what does the actual value adding functions. There can be several operation units in the system in focus.
  • The Meta system (Management) – This is similar to the brain and the nervous system. This is the glue that holds all the operational units and provides coherence to the structure.
  • The Environment – This is the relevant part of the external environment in which the system is in.

In an overall sense, management’s function is to manage complexity. Beer uses variety as a measure of complexity. Variety is the number of possible states of a system. The environment obviously has the maximum variety of the three elements. The operation has more variety than the management. Thus, we can denote this as. [3]


Here the amoeba shape represents the environment, the circle represents the operational unit and the square represents the management. “V” represents the variety possessed by each element. Management has to attenuate or filter out the extra variety while amplifying its variety in order to accommodate the variety that surrounds it. The same goes for the operational unit. Please note that we are dealing with continuous loops rather than simple connectivities. Beer postulates his Law of Inter-Recursive Cohesion based on this: Managerial, Operational and Environmental varieties, diffusing through an institutional system, TEND TO EQUATE; they should be designed to do so with minimum damage to people and to cost.

This idea is based on Ross Ashby’s Law of Requisite Variety – Only variety can absorb variety. In order to maintain viability, attenuators and amplifiers must be in place so that the three varieties are equivalent. There are homeostatic loops in place that amplify the lower varieties to absorb the higher varieties, and attenuate the higher varieties towards the lower varieties. This is depicted in the schematic below. Please note the adjustment to the scale of “V” to denote equivalence of variety achieved through attenuation and amplification.

Varieties 2

For a simple example, let’s look at a football game. There are 11 players for each team. There is one-to-one compensation of variety possible between the two teams playing. The officials, “managing” the game are able to match the variety from the players with the use of attenuators (rules, policies etc. of the game) and amplifiers (whistles, flags etc.).

Every viable system has five sub-systems, identified as Systems 1 through 5:

System 1 – Interacting operational units.

System 2 – Responsible for coordination between the interacting operational units, and provides stability via anti-oscillatory and conflict resolution strategies. An example is production control in a manufacturing plant.

System 3 – Responsible for control and optimization, and synergy between the organizational units. Often referred to as an “internal eye” focusing on “here and now”, internal and immediate functions. There is also a “Three*” subsystem that is responsible for monitoring/audit.

System 4 – Responsible for Planning and “Intelligence”. Often referred to as “external eye” focusing on “there and then”. System Four’s role is to observe the anticipated future environment and its own states of adaptiveness and act to bring them into harmony. [4]

System 5 – Responsible for developing “identity” and policy. Maintaining a good balance between System Three’s concern with the day to day running of affairs and System Four’s concentration on the anticipated future is a challenge for every organization. [4] System five is responsible for monitoring the balance between System three and System four.

As noted earlier, the strength of the VSM is in recursion. Every viable system at every recursion level must have the five subsystems working coherently in order to be viable.

Taken it all together, the Viable System Model looks like: [5]


The diagram can appear confusing due to the recursive nature of the viable systems within the viable system. There is lot more to the VSM than discussed here.


Due to the presence of viable systems within a viable system, the policies set by each System five may not be in alignment with the policy set by the System five in the larger viable system. Beer postulates that the observed and imputed “purpose” of the system and the “designed” purpose of the system are not in agreement. Beer states that the purpose is generally formulated within a higher recursion, thus, it is imperative that the purpose is restated at each low recursion in a language that the system understands. Based on this purpose, the system in focus will act by its proper inputs and reacts to its environment resulting in a new state of the system. The system should have a “comparator” that continuously compares the declared purpose and the purpose imputed from the results that the system delivers. This results in a feedback that leads to a modification of the original purpose. Beer states that:

This system will converge on a compromise purpose – it is neither what the higher recursion would like to see done, nor what the viable system itself would most like to see done, nor what the viable system itself would like to indulge in doing.

The purposes of the corporate system and those of System One are different, because System One consists of viable systems whose conditions of survival are formulated at a different level of recursion. The compromise convergence must continually act and this generally leads to lowest variety compromise possible. Please note that “what the system does” is done by System One. Beer postulated that autonomy is a computable function of the purpose of a viable system based on this. Autonomy is the maximum discretionary action available for the subsystem, short of threatening the integrity of the system as a whole.

Final Words:

Stafford Beer was man beyond his times for sure. I strongly encourage the readers to read as much of his works as you can. The VSM allows us to diagnose or even design an organization by making sure that the required homeostats, subsystems and channels are present to ensure viability. For those who wish to implement Lean or Six Sigma or Agile or any of other paradigms out there, I will finish with words of wisdom from Beer:

We manage through a model that we hold in our heads about how things work ‘out there’. If our model does not have Requisite Variety, then we ought to incorporate learning circuits that will enrich it. But if we are ideologically attached to our model, so that it is not negotiable, then it becomes a dysfunctional paradigm.

Always keep on learning…

In case you missed it, my last post was Cultural Transmission at Toyota:

[1] Diagnosing the System, Stafford Beer

[2] POSIWID and determinism in design for behaviour change, Dan Lockton

[3] World in Torment, Stafford Beer

[4] The Viable System Model and its Application to Complex Organizations, Allenna Leonard, Ph.D.

[5] VSM By Mark Lambertz – Own work, CC BY-SA 4.0,



Calculating Lead Times in a Value Stream Map

I was asked a question recently about the lead time calculations in a Value Stream Map. The question was specifically how the lead time is calculated.

There are two ways, that I have seen, of calculating lead times for value stream mapping. They both produce different results.

1) The first one is the one in “Learning to See”. Here the lead time is calculated as follows. Lead Time = Inventory/Daily Demand. There is no relationship with the consumption rate at the subsequent station. If the WIP is 1000 and the daily demand is 100, the lead time is 10 days. The assumption is that the inventory will be used up in only 10 days. This produces an inflated value for lead time and is not the true current state.

2) Calculation of Lead Time based on Little’s Law. To me, this is more realistic. Here the lead time is calculated as follows. Lead Time = WIP * Cycle Time of subsequent station. I know there is a lot of confusion regarding this.  Think of lead time calculation as the future tense. With the same example above, if the WIP is 1000 and cycle time at the station is 60 seconds, the lead time is 60000 seconds or 1000 minutes. Assuming 460 minutes in a day, this equates to 2.17 days (1000/460). In other words, lead time calculation is based on consumption rate.

The only thing to keep in mind with the second calculation is with the inventory we have at the last stage (Finished Goods). The lead time for this will be calculated as Inventory/Daily Requirement. This is because the customer is going to consume this at the rate of daily requirement.

In the end, please note that, “By overanalyzing the tool, don’t overlook the purpose of the tool.”

Keep on learning…