On Organizations and Machines

My previous post Where does learning take place? was prompted by a Twitter discussion in which some of the participants denied that organizational learning was possible or meaningful. Some argued that any organizational behaviour or intention could be reduced to the behaviours and intentions of individual humans. Others argued that organizations and other systems were merely social constructions, and therefore didn't really exist at all.

In a comment below my previous post, Sally Bean presented an example of collective learning being greater than the sum of individual learning. Although she came away from the reported experience having learnt some things, the organization as a whole appears to have learnt some larger things that no single individual may be fully aware of.

And the Kihbernetics Institute (I don't know if this is a person or an organization) offered a general definition of learning that would include collective as well as individual learning.

If you understand #learning is the process of acquiring #knowledge which is a measure of an individual's "fitness" in performing a given task, you can use the same system model on both humans and organizations.

— The Kihbernetics Institute (@Kihbernetics) January 3, 2022

I think that's fairly close to my own notion of learning. However, some of the participants in the Twitter thread appear to prefer a much narrower definition of learning, in some cases specifying that it could only happen inside an individual human brain. Such a narrow definition of learning would not only exclude organizational learning, but also animals and plants, as well as AI and machine learning.

As it happens, there are differing views among botanists about how to talk about plant intelligence. Some argue that the concept of plant neurobiology is based on superficial analogies and questionable extrapolations.

But in this post, I want to look specifically at machines and organizations, because there are some common questions in terms of how we should talk about both of them, and some common ideas about how they may be governed. Norbert Wiener, the father of cybernetics, saw strong parallels between machines and human organizations, and this is also the first of Gareth Morgan's eight Images of Organization.

Margaret Heffernan talks about the view that organisations are like machines that will run well with the right components – so you design job descriptions and golden targets and KPIs, manage it by measurement, tweak it and run it with extrinsic rewards to keep the engines running. She calls this old-fashioned management theory.

Meanwhile, Jonnie Penn notes how artificial intelligence follows Herbert Simon's notion of (corporate) decision-making. Many contemporary AI systems do not so much mimic human thinking as they do the less imaginative minds of bureaucratic institutions; our machine-learning techniques are often programmed to achieve superhuman scale, speed and accuracy at the expense of human-level originality, ambition or morals.

The philosopher Gilbert Simondon observed two contrasting attitudes to machines.

First, a reduction of machines to the status of simple devices or assemblages of matter that are constantly used but granted neither significance nor sense; second, and as a kind of response to the first attitude, there emerges an almost unlimited admiration for machines. Schmidgen

On the one hand, machines are merely instruments, ready-to-hand as Heidegger puts it, entirely at the disposal of their users. On the other hand, they may appear to have a life of their own. Is this not like organizations or other human systems?

---

Amedeo Alpi et al, Plant neurobiology: no brain, no gain? (Trends in Plant Science Volume 12, ISSUE 4, P135-136, April 01, 2007)

Eric D. Brenner et al, Response to Alpi et al.: Plant neurobiology: the gain is more than the pain (Trends in Plant Science Volume 12, ISSUE 7, P285-286, July 01, 2007)  

Anthea Lipsett, Interview with Margaret Heffernan: 'The more academics compete, the fewer ideas they share' (Guardian, 29 November 2018)

Gareth Morgan, Images of Organization (3rd edition, Sage 2006)

Jonnie Penn, AI thinks like a corporation—and that’s worrying (Economist, 26 November 2018)

Henning Schmidgen, Inside the Black Box: Simondon's Politics of Technology (SubStance, 2012, Vol. 41, No. 3, Issue 129 pp 16-31)

Geoffrey Vickers, Human Systems are Different (Harper and Row, 1983)

Related post: Where does learning take place? (January 2022)

Where does learning take place?

This blogpost started with an argument on Twitter. Harish Jose quoted the organization theorist Ralph Stacey:

Organizations do not learn. Organizations are not humans. @harish_josev

This was reinforced by someone who tweets as SystemsNinja, suggesting that organizations don't even exist. 

Organisations don’t really exist. X-Company doesn’t lie awake at night worrying about its place in X-Market. @SystemsNinja

So we seem to have two different questions here. Let's start with the second question, which is an ontological one - what kinds of entities exist. The idea that something only exists if it lies awake worrying about things seems unduly restrictive. 

How can we talk about organizations or other systems if they don't exist in the first place? SystemsNinja quotes several leading systems thinkers (Churchman, Beer, Meadows) who talk about the negotiability of system boundaries, while Harish cites Ryle's concept of category mistake. But just because we might disagree about what system we are talking about or how to classify them doesn't mean they are entirely imaginary. Geopolitical boundaries are sociopolitical constructions, sometimes leading to violent conflict, but geopolitical entities still exist even if we can't agree how to name them or draw them on the map.

Exactly what kind of existence is this? One way of interpreting the assertion that systems don't exist is to imagine that there is a dualistic distinction between a real/natural world and an artificial/constructed one, and to claim that systems only exist in the second of these two worlds. Thus Harish regards it as a category mistake to treat a system as a standalone objective entity. However, I don't think such a dualism survives the critical challenges of such writers as Karen Barad, Vinciane Despret, Bruno Latour and Gilbert Simondon. See also Stanford Encyclopedia: Artifact.

Even the idea that humans (aka individuals) belong exclusively to and can be separated from the real/natural world is problematic. See for example writings by Lisa Blackman, Robert Esposito and Donna Haraway.

And even if we accept this dualism, what difference does it make? The implication seems to be that certain kinds of activity or attribute can only belong to entities in the real/natural world and not to entities in the artificial/constructed world. Including such cognitive processes such as perception, memory and learning.

So what exactly is learning, and what kinds of entity can perform this? We usually suppose that animals are capable of learning, and there have been some suggestions that plants can also learn. Viruses mutate and adapt - so can this also be understood as a form of learning? And what about so-called machine learning?

Some writers see human learning as primary and these other modes of learning as derivative in some way. Either because machine learning or organization learning can be reduced to a set of individual humans learning stuff (thus denying the possibility or meaningfulness of emergent learning at the system level). Or because non-human learning is only metaphorical, not to be taken literally.

I don't follow this line. My own concepts of learning and intelligence are entirely general. I think it makes sense for many kinds of system (organizations, families, machines, plants) to perceive, remember and learn. But if you choose to understand this in metaphorical terms, I'm not sure it really matters.

Meanwhile learning doesn't necessarily have a definitive location. @systemsninja said I was confusing biological and viral systems with social ones. But where is the dividing line between the biological and the social? If the food industry teaches our bodies (plus gut microbiome) to be addicted to sugar and junk food, where is this learning located? If our collective response to a virus allows it to mutate, where is this learning located?

In an earlier blogpost, Harish Jose quotes Ralph Stacey's argument linking existence with location.

Organizations are not things because no one can point to where an organization is.

But this seems to be exactly the kind of category mistake that Ryle was talking about. Ryle's example was that you can't point to Oxford University as a whole, only to its various components, but that doesn't mean the university doesn't exist. So I think Ryle is probably on my side of the debate.

The category mistake behind the Cartesian theory of mind, on Ryle’s view, is based in representing mental concepts such as believing, knowing, aspiring, or detesting as acts or processes (and concluding they must be covert, unobservable acts or processes), when the concepts of believing, knowing, and the like are actually dispositional. Stanford Encylopedia

---

Lisa Blackman, The Body (Second edition, Routledge 2021)

Roberto Esposito, Persons and Things (Polity Press 2015)

Harish Jose, The Conundrum of Autonomy in Systems (28 June 2020), The Ghost in the System (22 August 2021)

Bruno Latour, Reassembling the Social (2005)

Gilbert Simondon, On the mode of existence of technical objects (1958, trans 2016)

Richard Veryard, Modelling Intelligence in Complex Organizations (SlideShare 2011), Building Organizational Intelligence (LeanPub 2012)

Stanford Encyclopedia of Philosophy: Artifact, Categories, Feminist Perspectives on the Body

Related posts: Does Organizational Cognition Make Sense (April 2012), The Aim of Human Society (September 2021), On Organizations and Machines (January 2022)

And see Benjamin Taylor's response to this post here: https://stream.syscoi.com/2022/01/02/demanding-change-where-does-learning-take-place-richard-veryard-from-a-conversation-with-harish-jose-and-others/

Operational Excellence and DNA

In his 2013 article on Achieving Operational Excellence, Andrew Spanyi quotes an unnamed CIO saying operational excellence is in our DNA. Spanyi goes on to criticize this CIO's version of operational excellence, which was based on limited and inadequate tracking of customer interaction as well as old-fashioned change management.

But then what would you expect? One of the things that distinguishes humans from other species is how little of our knowledge and skill comes directly from our DNA. Some animals can forage for food almost as soon as they are born, and some only require a short period of parental support. Whereas a human baby has to learn nearly everything from scratch. Our DNA gives very little directly useful knowledge and skill, but what it does give us is the ability to learn.

Very few cats and dogs reach the age of twenty. But at this age many humans are still in full-time education, while others have only recently started to attain financial independence. Either way, they have by now accumulated an impressive quantity of knowledge and skill. But only a foolish human would think that this is enough to last the rest of their life. The thing that is in our DNA, more than anything else, more than other animals, is learning.

There are of course different kinds of learning involved. Firstly there is the stuff that the grownups already know. Ducks teach their young to swim, and human adults teach kids to do sums and write history essays, as well as some rather more important skills. In the world of organizational learning, consultants often play this role - coaching organizations to adopt best practice.

But then there is going beyond this stuff. Intelligent kids learn to question both the content and the method of what they've been taught, as well as the underlying assumptions, and some of them never stop reflecting on such things. Innovation depends on developing and implementing new ideas, not just adopting existing ideas.

Similarly, operational excellence doesn't just mean adopting the ideas of the OpEx gurus - statistical process control, six sigma, lean or whatever - but collectively reflecting on the most effective and efficient ways to make radical as well as incremental improvements. In other words, applying OpEx to itself.

Andrew Spanyi, Achieving Operational Excellence (Cutter Consortium Executive Report, 15 October 2013) registration required

Related posts: Changing how we think (May 2010), Learning at the Speed of Learning (October 2016)

Learning at the Speed of Learning

According to a recent survey by McKinsey,  "the great majority of our respondents expect corporate learning to change significantly within the next three years".

It seems that whatever the topic of the survey, middle managers and management consultants always expect significant change within the next three years, because this is what justifies their existence.

In this case, the topic is corporate learning, which McKinsey recommends should be done "at the speed of business", whatever that means. (I am not a fan of the "at the speed of" cliche.)

But what kind of change is McKinsey talking about here? The article concentrates on digital delivery of learning material - disseminating existing "best practice" knowledge to a broader base. It doesn't really say anything about organizational learning, let alone a more radical transformation of the nature of learning in organizations. I have long argued that the real disruption is not in replacing classrooms with cheaper and faster equivalents, useful though that might be, but in digital organizational intelligence -- using increasing quantities of data to develop and test new hypotheses about customer behaviour, market opportunities, environmental constraints, and so on -- developing not "best practice" but "next practice".

Richard Benson-Armer, Arne Gast, and Nick van Dam, Learning at the speed of business (McKinsey Quarterly, May 2016). HT @annherrmann

Chris Argyris and Donald Schön, Organizational Learning: A Theory of Action Perspective. Reading, MA, Addison-Wesley, 1978.

The Judgment of whole Kingdoms and Nations

@Cybersal @kirstymhall @UKParliament #Brexit #VoxPopuli

---

A radical Whig tract was published in 1709 under the title Vox Populi, Vox Dei. The following year, an extended version was published under the title The Judgment of whole Kingdoms and Nations. I want to use these two phrases as the starting point for my submission to the UK Parliament Public Administration and Constitutional Affairs Committee, which has launched an inquiry into the lessons that can be learned for future referendums.

The first thing I want to mention is the rushed timescale. The inquiry was announced on July 14th, with a deadline for submissions of September 5th. I shall argue that this rushed timescale is symptomatic of the referendum itself, in which people were asked to make a complex decision with inadequate information and analysis.

(For the sake of comparison, an inquiry on the future of public parks was announced on July 11th, with a deadline of September 30th. So we are given more time to analyse the physical swings and roundabouts of council-run playgrounds than the metaphorical swings and roundabouts of parliamentary sovereignty and media oversight.)

To be fair, most parliamentary inquiries only give you weeks rather than months to compose a submission. This effectively limits submissions to people who have already formed an opinion, and already have the evidence to support this opinion. In other words, experts.

But then most parliamentary inquiries are about issues that people have been concerned about for a much longer time: Bus Services, Employment Opportunities for Young People, Food Waste. There is an existing body of knowledge relating to each of these topics, and it is not unreasonable to ask people to base a submission on their existing knowledge.

In contrast, nobody knew precisely how this referendum was going to be mismanaged until it actually happened. Although many people (including some Brexiteers as well as many Remainiacs) predicted that it would end in tears, and can now say "we told you so".

I can read you like a magazine ... Don't say I didn't say I didn't warn you (Taylor Swift)

No doubt the Select Committee can expect to receive a number of submissions that fall under the heading of what the Dictionary of Business Bullshit calls "Pathologist's Interest".

But told-you-so is not a good starting point for a proper analysis, because it concentrates on confirming one's previous expectations, rather than discovering new patterns. So the Select Committee might not get much well-grounded analysis. Partly because there isn't time to do it properly, and partly because many of the potential "experts" are affiliated to UK universities, which are currently on summer vacation. Looks like the Select Committee is falling in line with Michael Gove's idea that "the people in this country have had enough of experts".

("The Voice of Gove is the Voice of Government". I wonder what that would look like in Latin?)

The official announcement sidesteps from "the lessons that can be learned" to "lessons learned", which is not the same thing at all. The former suggests an open exploration, while the latter suggests merely rattling through a project postmortem for form's sake. The timescale does not seem particularly conducive to the former. So is this apparent haste triggered by thoughts of a second referendum, or it is just intended to curtail criticism of Parliament for its earlier folly?

As I have argued elsewhere (including my book on Organizational Intelligence) complex sense-making and decision-making cannot go straight from the Instant of Seeing to the Moment of Concluding, but require what Lacan calls Time for Understanding. In this respect, the inquiry repeats one of the errors of the referendum itself.

The timescale and debating rules for the Brexit referendum were modelled on a General Election campaign. But a General Election has three important characteristics that were absent from Brexit. Firstly the electorate is generally familiar with the main parties: Labour and Conservative were around before any of us were born, and the Lib Dems also have long-established roots. Secondly, there is some rough notion of symmetry between the two main parties. Thirdly the parties make promises to which they will be held accountable in the event of victory. In other words, the General Election campaign can be compressed into a matter of weeks precisely because the rules of engagement are broadly understood, and there is very little new material for the electorate to process.

In comparison, as Kirsty Hall argues, the referendum for Scottish Independence was given a lengthy period of debate and analysis, because of the perceived complexity of the issues that needed to be considered. This would have been a much better model for the Brexit referendum.

Finally, let me return to the phrase "the judgement of whole kingdoms and nations", which of course raises the prickly subject of sovereignty. Although we supposedly have a system of parliamentary sovereignty in this country, parliament occasionally permits the voice of the people to be heard. As the Latin phrase has it, The Voice of the People is the Voice of God; and as the Establishment has discovered, the People can be a vengeful God. Parliament is still learning to listen to this vengeful voice. But who will teach what these lessons mean, and in what timescale? Or will the Establishment just adopt a Brechtian solution?

Would it not be simpler,
If the government simply dissolved the people
And elected another?#Brechtsit

— Richard Veryard (@richardveryard) June 30, 2016

---

Update (September 2016): Since I wrote this post, the Electoral Reform Society has published a critical report on the Brexit referendum, which makes the same unfavourable comparison with the Scottish Independence referendum that Kirsty Hall made in June. The Society has confirmed that it will be making a submission to the Parliamentary Inquiry.

Update (January 2019): The Prime Minister has recently made reference to the Welsh Devolution referendum. Her memory has been corrected in a Twitter thread by Professor Richard Wyn Jones.

Unexpectedly, the 1997 referendum on Welsh devolution is back in the news.

Setting aside Theresa May's misremembering/rank hypocrisy [delete according to taste] concerning her own and her own party's position, the lesson of Wales 1997 is actually about 'loser's consent' 1/

— Richard Wyn Jones (@RWynJones) January 14, 2019

Update (April 2019): The New European observes that the referendum failed to comply with the Venice Commission's Code of Good Practice on Referendums, which the UK Government signed up to in 2006.

---

Will Brett, Doing Referendums Differently (Electoral Reform Society, 1 September 2016)

Kirsty Hall, Brexit was a Con (28 June 2016) HT @cybersal @MerrickBadger @Koann

Jonathon Read, The UK has ignored its own code on referendums (New European, 17 April 2019) HT @drpaulmorgan

Richard Wyn Jones and Roger Scully, Wales Says Yes: Devolution and the 2011 Welsh Referendum (2012)

Richard Veryard, Lessons Learned from the EU Referendum (5 September 2016)

UK Parliament: Future of Public Parks, Lessons Learned from the EU Referendum (launch), Lessons Learned from the EU Referendum (report and evidence)

Wikipedia: Venice Commission, Vox Populi, Vox Dei 



Updated 18 April 2019

Are we making progress?

In a great post, @JohnQShift explains how to build a culture of learning in your business. He calls this A Matter of Life or Death (Feb 2013)

In the post, John reports one of his clients observing that they had made some progress in their business over the year.  By progress, the client meant that

• people were beginning to take up more responsibility and initiative without having to wait for the boss to tell them what to do
• there was more discussion amongst the staff as to how to manage some of the day-to-day challenges they meet and less referring to the boss for the “answer”
• mistakes were being used as entry points to examining business processes and working out how they could be improved
• they had a clearer idea of their collective purpose and how important relationship is to achieving that purpose
• the leaders were devoting more of their time to ensuring the conditions and structures of the business were optimised so that people could get on with their jobs (and less time micro-managing operational tasks).

Learning Lessons Learned

#orgintelligence Adapted from my contribution to a Linked-In discussion on "Lessons Learned".

---

There are several strands of learning from experience, and it may be useful to call these out explicitly.

1. Signals. What signals (that turned out to be important) could we have picked up sooner? What signals (that turned out to be unimportant) did we pay too much attention to?

2. What outcomes were achieved? To what extent did these outcomes match requirements and/or expectations? To what extent did requirements and expectations change during the project? Do we now recognize that some of the original requirements and expectations were inappropriate or unachievable?

3. Sense-making. How do we explain the things that went well and not so well? How much of what happened can be attributed to random variation? Which factors could have been better controlled?

4. Policy-making. What measures could be put in place to improve outcomes in future? How should these measures be communicated and enforced?

5. Learning. How many similar lessons were identified by previous projects and not implemented? How do we explain this? (For example, have voluntary guidelines worked in the past, or is a more formal governance called for?) How shall we check whether future projects learn any of these lessons?

OrgIntelligence in the Control Room

A control room provides a thin but panoramic view of everything that is going on. The French sociologist Bruno Latour calls this an oligopticon: he describes how Paris is controlled by a collection of separate control rooms, each focused on a different slice of reality; these control rooms may only talk to each other at the margins, or in major emergencies; there is no supreme control room commanding all the others.

"Water, electricity, telephony, traffic, meteorology, geography, town planning: all have their oligopticon, a huge control panel in a closed control room. From there very little can be seen at any one time, but everything appears with great precision owing to a dual network of signs, coming and going, rising and descending, watching over Parisian life night and day. No single control panel or synoptic board brings all these flows together in a single place at any one time." [Invisible Paris, pdf]

Each control room monitors and directs a particular set of systems, and has some responsibility for the smooth, efficient and safe operation of these systems. Except in a fully automated plant, such as a nuclear power plant, the responsibility may be shared with skilled operators and supervisors in the field, such as inspectors and engineers, bus and train drivers, policemen, etc., who not only pass situation reports to the control room (thus acting as the eyes and ears of the control room), but also may have a fair amount of autonomy and initiative to solve local problems, perhaps supported by up-to-date information from the control room or elsewhere. So we may regard the control room as the hub of a larger distributed control system, involving operational people as well as the control room staff.

My interest here is in the collective intelligence of these control systems. As the operational environment becomes more complex and demanding, collective intelligence becomes more and more critical in ensuring smooth, efficient and safe operation. Collective intelligence depends not just on the individual capabilities of the people, but on how the work is organized and how well the various technologies (information systems, screens, dashboards, communication devices) are designed and integrated to support the work. (In other words, we're talking about sociotechnical intelligence - intelligent collaborations of people and technology.)

Organizational intelligence has six constituents, so there are six areas we need to consider.

• Information gathering - what signals and messages are fed into the control room, and are these sufficient to enable critical situations to be quickly recognized or even anticipated?

• Sense-making - how well are complex incidents interpreted, and the possible knock-on effects predicted?

• Decision-making - how well are resources allocated, problems prioritized and solved, operational policies suspended or adjusted?

• Memory - how well are past situations and problems referenced in solving today's problems and anticipating tomorrow's problems?

• Learning - how do we continually improve the performance of the operating environment, as well as improving the effectiveness of the control system?

• Communication - how well do we communicate internally (within the control room), outwards (to people in the field), sideways (to other control rooms) and upwards (to management or other governance bodies)?

A control room or control system may have opportunities to improve in some or all of these areas, and the leverage yielded by such improvements can be very considerable. For example, with a fixed level of intelligence in a traffic control system, it may be impossible to increase traffic volumes without compromising safety. But if we can increase the effective intelligence of the control system, it may be possible to increase traffic volumes: for example, instead of having a standard minimum distance between vehicles, or time between signals, it may be possible to implement a variable rule that is more complicated, more difficult to enforce, but yielding more efficient utilization of resources. The point is that variable rules only work if you have enough sociotechnical intelligence in the control system to manage them properly; the more intelligence you can build into the system, the more variation (and therefore fine-grained and dynamic optimization) the system will be able to cope with.

A control room typically operates on at least three different tempi (speeds).

1. There is a real-time or near-real-time tempo, in which an event triggers an automatic or pre-programmed response, almost like a reflex. These responses are designed according to some pre-established operational model that allows the designer to reason about causes and effects, and should be monitored to make sure that these reflex mechanisms are working.

2. There will be a continuous stream of incidents requiring human intervention. The people in the control room will have to verify what exactly has happened, and then take appropriate action, based on their training and expertise, past experience, as well as practical common sense. The elapsed decision time may be measured in minutes or hours, and the situation as a whole may take days to clear.

3. Then there is a much longer-term learning cycle, where people are constantly looking for more effective ways of controlling the system and improving its performance. This might include analysing patterns of activity and identifying weak signals that would give early warning of possible future incidents, analysing system behaviour to check if the desired outcomes are being consistently met, exploring alternative ways of exercising control, experimenting with design improvements to the technical systems, and so on. The learning cycle may also include occasional crisis management exercises based around a simulated incident, to test the responses to a major emergency. In a rapidly evolving world, this kind of continuous improvement is a vital aspect of collective intelligence, to make sure that the control system maintains its ability to fulfil its responsibilities.

The relationship between 2. and 3. is an interesting one. Sometimes the people responsible for 3. don't actually sit in the control room, and may even report into a different part of the management hierarchy. But although we certainly cannot ignore the formal management structure, the real question here is about the effectiveness of feedback and learning, and in providing as many people as possible with the opportunity to contribute to the learning process, and therefore to the intelligence of the whole system.

Lots of interesting issues here then, both in terms of organizational change and technological change, with the possibility of producing large improvements at relatively small cost.

---

This is an extract from my eBook on Organizational Intelligence.
https://leanpub.com/orgintelligence/

Changing how we think

@benjaminm quotes John Seddon "Change in performance requires a change to the system and to change the system, management have to change the way they think". But (I wondered) does he mean new beliefs and mental habits (content) or a new method of arriving at beliefs and mental habits (process)?

@benjaminm would say both: "they need to unlearn assumptions/develop new ways of 'knowing' by studying the system". @benjaminm adds that "Seddon seems admirably focussed on an intervention model based on managers/teams studying the work to discover for themselves", and recommended @dpjoyce's write-up of Jeremy Cox's workshop at the Vanguard Network Day 25th February 2010.

However, although this piece explicitly references both Chris Argyris' double-loop learning and Gregory Bateson's second-order learning, much of the rhetoric seems aimed at simply replacing one set of assumptions and beliefs (which Vanguard calls "Command-and-Control View") with a new set of assumptions and beliefs (which Vanguard calls "Systems Thinking View"). 

COMMAND-AND-CONTROL THINKING		SYSTEMS THINKING
Top-down, hierarchy	PERSPECTIVE	Outside-in, system
Functional	DESIGN	Demand, value and flow
Separated from work	DESIGN-MAKING	Integrated with work
Output, targets, standards: related to budget	MEASUREMENT	Capability, variation: related to purpose
Contractual	ATTITUDE TO CUSTOMERS	What matters?
Contractual	ATTITUDE TO SUPPLIERS	Cooperative
Manage people and budgets	ROLE OF MANAGEMENT	Act on the system
Control	ETHOS	Learning
Reactive, projects	CHANGE	Adaptive, integral
Extrinsic	MOTIVATION	Intrinsic

source: John Seddon, Systems Thinking in the Public Sector, Triarchy 2008, p70.


Vanguard clearly regards the new set of assumptions and beliefs as "true"; thus the question about "changing how managers think" becomes a tactical question - how do you create a learning environment in which managers adopt the Vanguard principles for themselves, without obvious coercion. So the new beliefs (content) are primary, and the process of arriving at the new beliefs is merely a secondary means to an end. This is where the Vanguard notion of "Systems Thinking" diverges radically from those schools of systems thinking that focus primarily on the process of thinking deeply about systems, and regard the insights that emerge from this process as important but secondary.

Whatever advantages Vanguard's "Systems Thinking View" may have over the "Command-and-Control View", the two views appear to be at the same logical level in Bateson terms. Simply replacing one set of assumptions with another set of assumptions is merely changing WHAT you think, not HOW you think.

So I fully agree with @antlerboy, when he commented "as a starting point, mgrs/teams studying processes is brilliant. But not same as studying 'system' / knowing..."

---

If you just want people to adopt a new (replacement) set of mental habits, then this calls for mental training. If you want people to adopt a new (replacement) set of beliefs, then it calls for rhetoric and indoctrination. (Which is what makes Vanguard workshops look a bit like Alpha courses.) But if you want people to change their learning style, this is a much more fundamental and difficult change.

I just did an internet search for the phrase "changing how we think", and found a number of eloquent pages, many of them trying to reframe some familiar topics.

• @Adam Westbrook, It’s time to change how we think about “news”
• Doriah Williams, Changing how we think about climate change

I also found some psychological pages, trying to encourage and enable people to think "positive" rather than "negative" thoughts.

• Brett Steenbarger

Finally, I found some pages suggesting that various systems and technologies could alter our thinking processes, for good or ill.

• New memory tech will change how we think and learn
• Information sharing will change how we think

The value of time management ...

After I blogged about the value of getting things done, @johanlindberg asked me to look at a couple of other time management practices - Burn-Down Charts and the Pomodoro technique.

There must be hundreds of time management practices, and thousands of self-help books and websites encouraging people to organize themselves better. Some of them even tell you to stop reading and get on with stuff.

Why are there so many? Is it because they all work, or because none of them do? Is it because there isn't a single approach to time management that suits everyone, so we all need to read dozens of these before we find one that provides just the right combination of common sense and quirkiness that chimes with our own lives? Or is it because people who have difficulties with time management are always looking for further displacement activity - as if reading just one more book, or buying just one more iPhone app, will suddenly change us from muddled procrastinators into smooth and effective operators?

I cannot see a simple way to evaluate and compare these time management approaches as practical methodologies. Clearly there is enormous subjective value in organizing oneself, just as there is in coordinating a team, and we can certainly see the costs and risks associated with the lack of organization or coordination in particular situations, but organization and coordination are generally valued because they help us achieve our goals, rather than being primary goals in their own right.

What about judging a person or team in terms of achievement? There are levels of achievement that may be relevant here. Firstly, efficiency or productivity in handling a fairly uniform stream of events and tasks. Secondly, effectiveness in handling small variations in the event-stream - small adjustments that represent a continuous improvement loop - (in other words, single-loop learning to maintain a stable set of outcomes with variable inputs). Thirdly agility in anticipating and managing change (in other words, double-loop learning, where the desired outcomes may change as well as the strategies).

"Best practice" time management may help people become more efficient and effective in narrowly defined areas or known tasks. But sometimes the reason for procrastination is that people aren't sure whether that's the right thing to do. Sometimes it really is better to stop and think; and a time management practice that inhibits reflection may ultimately turn out to be a handicap.

Perhaps we should think of time management not as a best practice (which everyone needs all of the time) but as a kind of therapy (which many people need sometimes). In which case, it's not about getting everyone to adopt some standard technique, but having resources available to help people and teams when they experience a certain kind of stuckness. Sometimes true intelligence is knowing when you need help.

Workflow Learning

Jay Cross of the Workflow Institute raves about the component-based business (the subject of my 2001 book), which he calls a Business Singularity. He identifies some interesting consequences for what he calls Workflow Learning.

Workers are learning in small chunks delivered to individualized screens presented at the time of need. Learning is being transformed into a core business process measured by Key Performance Indicators.

This prospect raises interesting questions for what we might call the Architecture of Knowledge. If workers learn in small chunks, how can these chunks be assembled into a coherent body of knowledge? How does the way the work is decomposed between workers affect the learnings that are accessible to them?

---

In response to Jay's comment

Doesn't the underlying Business Process Management and Business Rules structure the KM as much as needed? The work itself lends the coherence, but some external taxonomy.

In my view, the structure provided by the Business Process Management and Business Rules is usually either underdetermined or overdetermined. The chunk is polymorphic, and takes on a different meaning according to the context in which it is framed.

Just because the workers digest chunks doesn't mean the chunks aren't part of a larger entity.

Indeed they may be part of a larger entity, but this doesn't happen by magic.



Think about the way a film director puts together a film. The actors may not know how their scene fits into the whole until they see the final cut. (Indeed, some directors deliberately leave their actors in the dark during the shoot.) Or think about the way a composer/arranger puts together strands of music. Composition/orchestration/editing is a skilled process, which the actors/musicians cannot always second-guess.



So if the work is distributed - perhaps across different organizations and locations - there is no guarantee that the coherence of the work is visible to the individual worker. Indeed, the composition of business processes out of services is one of the key challenges of the service economy. The point I was making here is that this composition also applies at the level of knowledge management and learning; and the possible fragmentation of knowledge is a serious issue.



More on this in my SOAPbox blog.

Notes on Failure and Blame

Identifying the causes of failure may be an essential condition for organizational learning. Refusal to blame may lead to a refusal to understand, or even a denial that failure has occurred / is occurring. 

However, where problems are systemic or due to process design, blaming individuals obscures the problem. A blame culture also leads to an avoidance of risk. 

 

Component as scapegoat - a part takes the blame for the whole

I have lost count of the number of analyses I have read about NASA and the failure of the space shuttle. Blame the O-ring. Blame the management. Blame the narcissism of the organization [Schwartz]. 

What was most striking about these investigations, especially in the early days as the press speculated on the findings, was the tendency to focus on what, in particular, had caused the problem. It had the flavour of trying to find an appropriate scapegoat, so that certain parts of the system could be free from blame. [Smith and Berg, p 156] 

Individual as scapegoat - a person takes the blame for the system

In both health and transport, there is a tendency to blame individuals for faults in the system. Individuals are characterized as Bad Apples, as if this acted as a satisfactory explanation or excuse. 

A recent British TV programme showed a number of cases of health workers whose careers were ruined by a single error. A nurse who picked up the wrong injection after a 30 year unblemished career, and killed the patient. A pharmacist who failed to distinguish between two almost identical packs. (Obviously higher status professionals don't get scapegoated so easily.) 

By blaming the individual, the system remains unaffected. Blame is therefore a mechanism for preserving the system.

 

With transport (e.g. rail crashes) we have two opposite tendencies. One is to automatically blame the driver or the pilot. The other is to postulate some outrageously expensive piece of technology, such as a state-of-the-art signalling and braking system, and claim that this technology would have magically eliminated all risk. The fault then lies with The Management for being too mean to invest in this life-saving technology. 

Grief (for example the bereaved relatives) can then be converted into anger. With rail crashes, the driver's often among the dead, so it's apparently better for the relatives (and the media) to have a living target for this anger (and revenge). Another mechanism which sustains a blaming culture.

And then there's the lawyers. 

 

Examples

Schrecklichkeit (August 2004), A Bit of a Dump (April 2008), Emotional Intelligence (September 2010), The Quantum Organization (November 2015), Jaywalking (November 2019)

 

References

H.S. Schwartz, Narcissistic Process and Corporate Decay: The Theory of the Organizational Ideal (New York: New York University Press, 1990)

K.K. Smith and D. N. Berg, Paradoxes of Group Life (San Francisco: Jossey Bass, 1987)

 

---

Originally published at http://www.veryard.com/tcm/failure.htm 26 July 2004