Addendum to my recent ‘Venn diagram’ post

After publishing My ‘Snowden – Seddon’ Venn diagram post on this blog, a reader decided to share it via LinkedIn (which I appreciate – many thanks Sam).

I (usually) choose not to ‘push’ my material onto social media – I’m not trying to sell something (I don’t derive income from it) or gain any ‘influencer’ status.

However, if someone ‘pulls’ it to themselves and for others (e.g. by reposting etc.) then this gives me useful feedback that they see some utility within (even if it is just to prompt a level of reflection).

The loading of the blog post link onto LinkedIn prompted one of the subjects, Dave Snowden, to provide a response. In the interests of transparency (i.e. if you have, or go on to, read the post) I think it’s useful for you to know what Dave wrote, and my thoughts on this:

Dave’s comment on LinkedIn (with me splitting it into – what I see as – the four distinct points within):

“[1] You only have 2 of the 5 (9 if you include liminal) Cynefin domains & [2] even then they do not equate to a split between manufacturing & service. [3] CAS of which Cynefin is a part would reject the whole idea of archetypes. [4] Your descriptions seem designed to support your thesis 🙂 “

My reply:

“Hello Dave, thanks for providing some thoughts on my recent blog post. Rather than attempting to add my thoughts within a small LinkedIn reply box, I’ve chosen to add an addendum to my post that a) makes your comment transparent to any readers and b) provides some thoughts in reply. Regards, Steve”

My thoughts on Dave’s four points:

1. Yes, I am aware that I am only referencing a small part of the Cynefin sense-making framework, hence me writing in the post (emphasis added): “it very usefully differentiates (amongst many other things) between ordered and complex domains”; and me providing a reference in the footnotes to where readers can find out more about Cynefin; and me noting that there is a Cynefin wiki…which I’m happy to link to here.

For the avoidance of doubt: I find the full (and regularly maturing) Cynefin framework interesting. However, it was a particular aspect of it that was the focus of my reflection in my post.

2. Yes, I realise that (emphasis added) “they [Complex vs. Ordered] do not equate to a split between manufacturing and service”, which is why I wrote what I did, how I did, under the subheading title of ‘Making sense of the problem space’ (i.e. the intersect). I am not attempting to argue that anything is ‘the same’ within the post. I am setting out ‘the bones’ of useful linkages (as I currently see them). My last sentence was deliberate in writing (emphasis added) “I see people-centred as being the closest intersection with Snowden’s complex problem space.”

Note: If anyone wanted to understand what I was meaning by the phrase ‘people-centred’ then I provided a link to go to within the post.

3. Archetypes: I’m not sure what Dave is saying is being rejected within CAS (by which I think CAS is short for Complex Adaptive Systems)

  • the basic definition of an archetype? (“a typical example of something, or the original model from which others are copied” – Cambridge Dictionary); or
  • how the word has been used in, say, the school of System Dynamics?

For clarity: Seddon’s use of the word ‘archetype’ within his writings (as I understand it) does not equate to its usage by the likes of, say, Peter Senge within System Dynamics.

For example: the archetype of what Seddon refers to as a ‘break – fix’ service may be seen in many different settings (ref. an IT support desk, a social housing repairs service, an insurance claims process…)

4. Yes, I agree that my thinking cannot help but be shaped by my experiences to date, and so (like all of us) is biased accordingly. I’m not attempting to put forward some new theory. I’m choosing to use the medium of ‘writing it down’ to cause me to think and of ‘sharing it’ (via a personal blog) to cause me to think more carefully.

Regarding my bias: I don’t consider myself to be a ‘Seddonista’ or a ‘Snowdenite’ (no disrespect meant by using these terms), although I enjoy exploring, and considering if/how I can usefully apply both of their bodies of work (amongst many others).

In addition:

I also noted a number of comments from others in the related LinkedIn thread(s) making essentially the same point: that I had chosen to use the phrase ‘systems theory’ (in my Venn diagram and in my point 9 intersect), when I should probably have written ‘systems theories’. I’m more than happy with this suggested improvement.

Anyone reading Mike Jackson’s book (as referenced in footnote 4 of the post) would appreciate why the point is a good one.

My ‘Snowden – Seddon’ Venn diagram

This post is a long, meaty one. So, if this interests you, make yourself a cup of tea and settle in. If it’s not for you, no worries, ‘as you were’…but still make yourself that cuppa 🙂  

I first ‘got into’ systemsy stuff about 20 years ago1. I began with W. Edwards Deming (a peripheral figure in the systems literature) and then went in a variety of directions.

These include:

  • A number of ‘systems theorists’, such as Forrester, Meadows, Beer, Ackoff & Checkland
  • John Seddon’s work (noting his down-to-earth writings2)
  • Dave Snowden’s work (noting his desire for precision3)

As an aside: I’m a big fan of Mike Jackson’s work4 to clearly lay out ‘who’s thought what’ in the systems space, and his aim of providing a balanced ‘value vs. critique’ review on each.

During my journey – and most recently via the wonders (or is that curse?) of social media – I’ve noted what I might describe as various ‘turf wars’ going on. If you’ve been following along (e.g. Twitter, LinkedIn,…) then you could be forgiven for believing that the three groups noted above (or at least their thinking) are ‘poles apart’.

I’d agree that it’s very healthy for people to robustly test their thinking against others5 – it’s incredibly useful to understand a) boundaries of application and b) where there is more work to be done.

However, I feel that those trying to follow along could end up ‘throwing the baby out with the bathwater’ because we fail to see (or acknowledge) the significant intersections between the groups.

This post is about me exploring (some of) what I see as useful intersections.

I love a diagram, so I’ll use the one below to anchor what follows. It’s the typical Venn diagram, highlighting three sets and the relationships between them. The overlaps are the intersections:

I’m mainly concerned with the ‘Snowden – Seddon’ intersection within this post (because this currently interests me the most). You’ll have to bear with me on this because the intersections may not be apparent to those reading their work or listening to them speak. Further, they themselves may not accept my (current) view about if, and how, they intersect.

As an aside: I’d note that it’s not uncommon for similar things to be discovered/ worked out by different people in different settings…and this (almost inevitably) means that they will talk about similar things but use different language (or notation) to each other.

A couple of celebrated examples that I’m aware of:

  • Newton and Leibniz re. the invention of calculus
  • Darwin and Wallace re. the theory of evolution

The trick (so to speak) would be to spot the intersections and then build upon them. Newton and Leibniz (and their supporters) had an argument. Darwin and Wallace entered a collaboration.

I’ve thought about the following ‘Snowden – Seddon’ intersections:

  1. On making sense of the problem space
  2. On working with complexity
  3. On the importance of failure
  4. On facilitating change within the complex domain
  5. On scaling change within the complex domain
  6. On measurement
  7. Combining quantitative with qualitative
  8. On the use of tools
  9. On systems theory

Each explanation below will have two halves. I’ll start with a Snowden perspective, and then move to a Seddon viewpoint. Each half will deliberately begin with “as I understand it” (I’ll underline these so that you can clearly see me swapping over).

Here goes…

1. On making sense of the problem space

As I understand it, Snowden’s Cynefin framework6 aims to help decision makers make sense of their problem space…so that they respond appropriately. It very usefully differentiates (amongst many other things) between ordered and complex domains. In short:

  • An ordered system is predictable. There are known, or knowable cause-and-effect relationships and, because of this, there are right answers;
  • A complex system is unpredictable. The elements (for example people) influence and evolve with one another. The past makes sense in retrospect (i.e. it is explainable) BUT this doesn’t lead to foresight because the system, and its environment, are constantly changing. It’s not about having answers, it’s about what emerges from changing circumstances and how to respond.

As I understand it, Seddon realised that there is a seriously important difference between a manufacturing domain and a service domain and that this difference had huge implications as to how decision makers should act.

  • A widget being manufactured requires a level of consistency. Further, it is an inanimate object (ref: I’m just a spanner!);
  • A human being needing help from a service is unique. Further, they have (a degree of) agency;
  • As such, any system design needs to properly take this into account. An ordered response (e.g. pushing standardised ‘solutions’) to a complex problem space will not work out well (ref. failure demand7).

Of interest to me is that, whilst the widget production line may fit the ordered problem space, it usually involves human beings to run it. So, at a 2nd order level, it is complex – those workers are unique and possess agency. It would be a good idea to design a system that engaged their brains and not just their motor skills.

From reading about the Toyota Production System (TPS) over the years, I believe that this is perhaps what Taiichi Ohno and his colleagues knew… and what those merely trying to copy them didn’t (ref: Depths of ‘Transformation’).

As I understand it, Seddon would suggest that there are a number of service archetypes8 (from transactional…through to people-centred). I see people-centred as being the closest intersection with Snowden’s complex problem space, which leads on to…

2. On working with complexity

As I understand it, Snowden would suggest that the appropriate way to work with complexity would be to:

  • encourage interactions
  • experiment with possible ways forward
  • monitor what emerges and adjust accordingly
  • be patient: allow time for outcomes to emerge, and for reflection

I understand that this may be summarised as probe – sense – respond.

As I understand it, Seddon would suggest that the appropriate way for people-centred services to work would be to:

  • provide ‘person – helper’ continuity, to build trusting relationships between them
  • take the time to understand the person, their situation, and their needs
  • provide ‘person – helper’ autonomy: to try things, to reflect, to adjust according, to go in useful directions according to what emerges

I understand that this may be summarised as designing a system that can absorb variety rather than trying to specify and control.

I see a very strong intersection between the two. I see Seddon as arguing against an ordered response within a people-centred domain.

I note that Snowden uses the metaphor of the resilient salt marsh as compared to the robust sea wall. The former can absorb the variety of what each ‘coming of the tide’ presents, whilst the latter predictably responds but can’t cope when its utility is breached. Seddon is arguing for a ‘salt marsh’ people-centred system design, rather than the conventional sea wall.

3. On the importance of failure

As I understand it, Snowden is clear that we humans learn the most from failure – because we are exposed to the unexpected, and have to wrestle with the consequences (ref. reflection).

We may learn little from supposed ‘success’, where everything turns out as expected. We risk complacency.

As I understand it, Seddon arrived at the definition of failure demand7 because he realised that:

  • those accountable for the performance of a system are often (usually) not aware of the types (and frequencies) of failure demands caused by its current design
  • the act of seeing, and pondering, failure demand exposes them to reality, and provides a powerful lever for reflection as to why it occurs…and to new ways of thinking about design.

I would link the idea of ‘inattentive blindness’ (as regularly explained by Snowden) – where we may not see what is in plain sight (ref. the case of the radiologists and a gorilla).

Seddon’s method of uncovering failure demand is to enable management to begin the journey of seeing their gorilla(s).

4. On facilitating change within the complex domain

As I understand it, Snowden and his colleagues have defined a set of principles to follow, a key tenet of which is to design the change process in such a way that participants ‘see the system’ and discover insights for themselves (as opposed to being given answers).

As such, the role of the facilitator [interventionist] is to provide an environment in which the participants’ learnings can emerge. Those facilitating do not (and should not) act as ‘experts’. Further, the responsibility for producing an outcome shifts from facilitator to the group of participants.

As I understand it, Seddon’s life work centres around intervention theory and that ‘true human change is normative’ – people changing their thinking, where this is achieved through experiential learning. This would be the opposite of rational attempts at change via ‘you talk, they listen’.

As such, the role of the interventionist is to provide a method whereby they act as a ‘mirror, not an expert’ (ref. ‘Smoke and mirrors’). Further, the responsibility for outcomes lays squarely with those who are accountable for the system in question (ref. ‘leader-led’). ‘Change’ cannot be outsourced to the interventionist9.

5. On scaling change within the complex domain

Given the intersection above, it follows that it matters how we go about scaling change.

As I understand it, Snowden lays out the principle that:

“you don’t scale a complex system by aggregation and imitation. You scale it by decomposition and recombination.”

This area of thinking is currently a stub within the Cynefin wiki, which suggests that it is yet to be clearly set out. However, (to me) it is stating that you can’t just ‘copy and paste’ what apparently worked with one group of humans onto another. Well, you could try…. but you can expect some highly undesirable outcomes if you do (ref. disengagement, disenfranchisement, defiance…)

It also says to me that you can expect different ‘solutions’ to come from different groups, and this is completely fine if they are each ‘going in a useful direction’. Further, they can then learn from each other (ref. parallel experiments and cross pollination of ideas).

As I understand it, Seddon makes clear the problem with ‘rolling out’ (attempting to implement) change onto people. Instead, he defined the concept of ‘roll in’:

Roll in: a method to scale up change to the whole organisation that was successful in one unit. Change is not imposed. Instead, each area needs to learn how to do the analysis for themselves and devise their own solutions. This approach engages the workforce and produces better, more sustainable results.”

It’s not about finding an answer, it’s about moving to a new way of working whereby it is the norm for those in the work to be experimenting, collaborating, learning, and constantly moving to better places (ref. Rolling, rolling, rolling)

6. On measurement

As I understand it, Snowden holds that the appropriate way to measure change within a complex system is with a vector – i.e. speed and direction, from where we were to where we are now. This is instead of acting in an ordered way of setting a goal and defining actions to achieve it (which incorrectly presumes predictability).

As I understand it, Seddon’s colleague, the late Richard Davis, set out measurement of people-centred help in a similar ‘speed and direction’ manner (ref. On Vector Measurement for a more detailed discussion).

“But what about ‘Purpose’?”: You may know that Seddon is laser-focused on the purpose of a service system, from the point of view of those that it is there to help (e.g. the customer). This purpose acts as an anchor for everyone involved.

You might think that Seddon’s ‘purpose’ view clashes with Snowden’s ‘don’t set a goal within a complex system’ view.

I don’t see ‘purpose’ (as Seddon uses it) to be the setting of an (ordered) goal. I see it more as setting out the desirable emergent property if the system in question was ‘working’.

I probably need to set that out a bit more clearly. Here goes my attempt:

Definition: Emergent system behaviours are a consequence of the interactions between the parts.

Example: The individual parts of a bird (its bones, muscles, feather etc) do not have the ability to overcome gravity. However, when these parts usefully inter-relate, they create the emergent property of ‘flight’…and yet ‘flight’ is not a part that we can point at. It is something ‘extra/ more than’ the parts.

…and so to Purpose: The definition of the desirable emergent property (i.e. what we would ideally want ‘the system’ to be achieving) allows a directional focus. It’s not an ordered goal, with a set of specified actions to achieve. It’s a constant sense-check against “are we (metaphorically) flying?”

In a people-centred service, it would be “are we actually helping people [with whatever their needs are]?

7. Combining quantitative with qualitative

As I understand it, Snowden would say that there is a need to combine stories and measurement.

“Numbers are objective but not persuasive. Stories are persuasive but not objective. Put them together.” (Captured from Snowden workshop Aug. ‘22)

The power in stories is that they are authentic – they possess many useful qualities such as:

  • an actuality (evidence rather than opinion)
  • showing variation (noting that ‘the average’ doesn’t exist)
  • revealing ambiguity (causing us to think deeply about)
  • …etc.

However, given this, those wanting to understand at a ‘system level’ need to combine the micro into a macro picture – to see the patterns within (ref. Vector Measurement as per above).

As I understand it, Seddon tells us to study ‘in the work’ (get knowledge) and that this can be done by observing demands placed on the system in focus, and in following the flow of those demands – from need through to (hopefully) its satisfaction, and everything that happens (or doesn’t) in-between.

A case study can be a powerful story, providing an authentic understanding (from the customer’s point of view) of:

  • why this particular scenario arose
  • what happened10 and the associated ‘lived experience’, and
  • (with the appropriate reflection) why it occurred in this manner (ref. system conditions)

However, whilst such case studies can be eye-opening, they may be dismissed as ‘not representative’ if used on their own – the risk of ‘just dealing in anecdotal stories’.

They need to be combined with macro measures that show the predictability of what the stories evidence (ref. demand types and frequencies, measures of flow,…[measures against that desirable emergent purpose])

In short, the micro and the macro are complimentary. Both are likely to be necessary.

8. On the use of tools

As I understand it, Snowden and his collaborators are clear that there may be ‘lots of tools out there’ but its very important to ‘know enough’ before applying a tool (ref: ‘bounded applicability’):

“If we work with tools without context, in other words we don’t know enough to know the tool doesn’t fit the situation, the intervention will suffer, as will the overall outcome.” (Viv Read, Cynefin: weaving sense-making into the fabric of our world)

As I understand it, Seddon sets out the dangers of attempting to produce change via merely applying tools (ref. Seddon’s ‘Watch out for the Toolheads’ admonition) and the risk of using the wrong ‘tool’ on the wrong problems:

“The danger with codifying method as tools is that, by ignoring the all-important context, it obviates the first requirement to understand the problem” (Seddon)

I believe that Snowden and Seddon would concur that the start is to understand the problem space, and then (and only then) pick up, or design, applicable tools to assist. Conversely, I believe that they would rebuke anyone carrying around a codified method (‘tool’), looking for any place to use it.

9. On ‘Systems Theory’

As I understand it, both Snowden and Seddon are critical of aspects of systems theory.

  • Snowden argues against the (so called) hard forms of systems theory (ref. Cybernetics, System Dynamics)
  • Seddon argues for a practical approach that starts with studying ‘in the work’, to get knowledge.

Whilst their critiques may differ, the fact that they think differently to others re. systems theory is an intersect 🙂

I think that they would align with the following quote:

“[Theory] without [method] is a daydream. [Method] without [theory] is a nightmare”

 

“What a load of rubbish!”

To those ‘Seddonistas’11 or ‘Snowdenites’ out there who may baulk at the intersections above, I’m not suggesting that John Seddon and Dave Snowden think the same. I’m also not suggesting any superiority (of ideas) between them. Far from it. I believe that they’ve been on very different journeys (haven’t we all?).

 “So, it’s nirvana then?”

Nope – I’m not proposing that I’ve solved anything/ moved things to new places. I just find (what I see as) intersections to be interesting and potentially useful to ponder/work with/ build on.

I don’t expect that Snowden and Seddon are fully aligned – I’m (almost) sure that there’s plenty in the Venn diagram that doesn’t overlap.

As an aside, I think that Snowden and Seddon have both developed a reputation for ‘saying what they think’. I really like their desire, and ability, to provide solid critique – that ‘cuts through the crap’.

I do hope, though, that those geniuses amongst us ninnies (e.g. Snowden, Seddon) focus on education, rather than guru status.

 Further work: On the other intersections

I expect that there are lots of ‘thinking things’ that fit into the other intersections:

  • Where Snowden overlaps with the systems theorists
  • Where Seddon overlaps with the systems theorists
  • Where all three overlap

You may also be able to point to yet more ‘Snowden – Seddon’ intersections.

You are welcome to take this on as ‘homework’ 🙂

 

Addendum: Please see this link to an addendum referring to a response from Dave Snowden.

 

Footnotes

1. I’m not claiming expertise. I am but an amateur with a great deal more to learn.

2. An enjoyable read: John has written a number of books to date. I’ve found them a joy to read. This contrasts with other books, which can be torture.

3. Precision and words: If you know of Snowden’s work, you’ll probably be aware that it’s littered with (what I see as) ‘new words’, or at least new uses for them.

4. Mike Jackson’s book is called ‘Critical Systems Thinking and the Management of Complexity’.

5. Robust testing: personally, I’d like such testing to be carried out in a highly respectful (mana enhancing) way.

6. The Cynefin framework is set out (amongst other places) in Snowden and Boone’s ‘A Leader’s framework for decision making’, HBR Nov. 2007.

7. Failure demand was defined by Seddon as “Demand caused by a failure to do something, or to do something right for the customer”. It might also be called/ thought of as ‘preventable demand’. Its opposite is Value demand.

8. Service archetypes: See ‘Autonomy – autonomy support – autonomy enabling’ for an explanation from my perspective.

9. Attempts at outsourcing change: This is why all those outsourced improvement projects, carried out by specialist improvement roles don’t result in transformational change (ref. all those typical Lean Six Sigma ‘Green belt’ projects etc.).

10. What happened: the scope of a case study could range from a journey:

    • over a couple of days (likely relevant to a transactional archetype)
    • over weeks/ months (likely relevant to a process archetype)
    • to many years (a people-centred archetype)

11. ‘Seddonistas’ is a playful term I read in Mike Jackson’s book (ref. the chapter on the Vanguard Method). It refers to those that passionately ‘support’ John Seddon. I’ve made up the ‘Snowdenites’ word to provide a pairing (I think it’s fair to do so as I believe that I have noted a similar ‘supporters club’ phenomenon for Dave Snowden).

12. Image credits: Climber scaling cliff image by ‘studio4rt on Freepik’

On Vector Measurement: the ‘what’ and ‘why’ of

I’ll start this post with an excerpt from a podcast in which Stephen Fry was the guest. He recalled the following passage from a Sherlock Holmes book:

“You know Watson, the statistician has shown that we can predict, to an extraordinary order of accuracy, the behaviour of the ‘average man’

…but no one has yet, and probably never will be able to predict how an individual will behave.” (Sherlock Holmes, ‘The Sign of Four’ as verbally recalled by Stephen Fry)

Fry went on to add:

“We can be talked about as ‘a mass’, and advertisers and politicians…and all kinds of other people are very good at knowing how we behave as a group, but as individuals we are unknowable without face-to-face conversation, and [knowing a person’s] history and so on.” (Stephen Fry)

This made me smile. He is discussing a point that is (for me) quite profound and I’d like to use it to link a few things together1.

A reminder about Complex vs. Complicated

I wrote a post ages ago that explained the difference between a complex and ordered system (ref. ‘It’s complicated…or is it?’)

If you’d really like to delve into this, then I’d recommend looking at the Cynefin sense making framework2.

In short3:

  • An ordered system (whether simple or complicated) is predictable. There are known or knowable cause-and-effect relationships.

There are right answers (which may be self-evident or may require expert diagnosis)

  • A complex system is unpredictable. The elements (for example people) influence and evolve with one another. The past makes sense in retrospect (i.e. it is explainable) BUT this doesn’t lead to foresight because the system, and its environment, are constantly changing.

 It’s not about having answers, it’s about what emerges from changing circumstances and how to respond.

The difference between the two is hugely important.

On working in a system with a purpose of helping people

There are many social systems that are put in place with the intent of helping people with their lives. As an example: most (so called) developed countries have social welfare systems that provide a level of income support. They also help people with their housing needs and gaining employment.

Each of these welfare systems has a choice as to how it sees the people that need their help, and therefore how they choose to design their response.

The ‘average person’ response

The welfare system can look at their population of ‘clients’ and create a host of data about ‘the average’.

They can even break this population down into cohorts and look at more detailed ‘averages’. They might even design ‘personas’ around the ‘average’ per cohort.

But, if they design responses to individuals with reference to these averages, then they are falling into Sherlock Holmes’ stated error – that they believe they can know about an individual from an average.

They would be presuming an ordered (complicated) system and designing answers in response.

Example4:, We can all understand that, on average, it is beneficial for a person to gain employment and thus be able to become independent from the welfare system…so the ‘ordered’ answer must surely be ‘get everyone into work’…so let’s direct all our focus (and targets) to achieving this!

The ‘individual’ response

Each person reliant on a welfare system has a complexity to their life (whether we see this or not).

Expanding upon this, the complexities for many ‘clients’ can be huge – such as:

  • dependents (children, and others that they care for)
  • lack of permanent address and other financial barriers
  • limited education and work experience
  • mental health (incl. depression, anxiety), habits and addictions
  • physical disabilities
  • family violence
  • criminal records
  • history of institutional care
  • …etc.

If those working in the welfare system want to achieve meaningful help, then the starting point is for them to know the client as an individual, and then iteratively work alongside them according to what emerges.

Measurement of success

We would hope that each welfare system has thought about what its purpose is, from a client’s point of view, and that this is the anchor point from which everything else is tethered.

Such a purpose will likely be about helping people towards ‘good’ outcomes (such as independence, safety, …and other dimensions of wellbeing)

A welfare system should want to measure its performance against that purpose.

If I’ve assumed an ordered system (via the ‘average person’ design response) then I will take my ordered answers (in this example ‘getting people into work’) and likely measure things like ‘Number of clients into employment this period’. I might even set targets to (ahem) motivate my staff….

…and I will predictably (though unintentionally) promote dysfunctional behaviour5:

  • A mindset of whose ‘on my books’? (and therefore, who can I get off them)
  • Who can I get into work quickly? (with the reverse effect of leaving the ‘difficult ones’ languishing to one side)
  • What work can I get them into? (as opposed to what will help them succeed)
  • Who needs coaxing/ persuading and what can I use as levers to do this?
  • Who got themselves into work by themselves (i.e. without any help from us)…so that I can ‘count them in my numbers’
  • ….

Attempting to push someone into work might be an incredibly dumb thing to do for that individual (and for those that depend upon them).

The above is not blaming anyone working in such a system. It is to say that these are, sadly, “healthy responses to absurd work” (Herzberg).

To Vector Measurement

If I correctly see that the welfare system is a complex one, then I realise that I need to work at the level of the individual.

The type of measure that fits for a complex system is a vector measure. A reminder from schoolboy maths that a vector has both speed and direction. It is especially used to determine the position of one thing, in relation to another.

I will know the performance of my system if I regularly measure, for each individual, their speed and direction of travel – from where they are now towards, or away from, a better place (as defined by them).

Such a measure causes a total focus on the individual:

  • whether things are working for them or not
  • whether to continue with the current stimuli and perhaps amplify them; or
  • whether to dampen them and work to stimulate new ideas

It’s very likely that there will be a collection of unique needs per individual, and therefore a set of vectors to be monitored (one per need). These may cluster around the various dimensions of wellbeing (see footnote for a wellbeing model6).

Example: My financial wellbeing might be slightly (and temporarily) better off because you pushed me into a job, but my mental wellbeing might be sinking like a stone because it really wasn’t appropriate.

Which leads to…

Measuring over time

Vector measurement shouldn’t be one-off thing. The individual is on a (lifelong) journey. The reference point is continually changing, but the question of ‘better or worse off?’ (or perhaps progressing vs regressing) is a constant.

As such, each person steps from one place to another, sometimes forwards (i.e. towards where they thought they wanted to go), sometime diagonally (to new possibilities that have emerged) and sometimes backwards (requiring reflection and perhaps some helpful interventions).

Playing with a way to visualise such a journey7, it might look something like this:

If we were measuring the performance of a system aimed at helping individuals, we would want:

  • the aggregate of our clients to be going forwards (and most certainly not be stuck and dependent on us); and
  • to spot the individuals who are stuck or, worse, going backwards, so that we can (quickly) help;

Returning to the ‘average person’

Every welfare system says that it wants good outcomes for those that they are tasked with helping. Whether this happens will depend upon how we think this can be achieved.

I contrast:

  • Fighting people into (what we have determined for them as) good outcomes;

with

  • Dancing8 with people towards what they arrive at as their good outcomes

I hope you can see that if we truly help ‘the individual’ then, on average, people are quite likely to move towards employment (and better mental health and…). But this is a case of ‘cause’ (helping individuals) and ‘effect’ (improving the average).

Conversely, I can ‘badger the non-existent average’ till I’m blue in the face…but it would be the wrong place to work from!

In summary:

I’ll end with one of my favourite quotes:

“Simple, clear purpose and principles give rise to complex intelligent behaviour.

[Complicated] rules and regulations give rise to simple stupid behaviour(Dee Hock)

The simple, clear measure of ‘are you better or worse off (as defined by you)’? will give rise to all sorts of varied, individualised and highly relevant actions and interaction.

The complicated rules around, say, how many people a team is supposed to get into employment this period, what counts as ‘getting employment’, what rules determine who gets the credit, how long does this ‘employment’ need to be sustained to keep the credit,…and so on, will give rise to simple, stupid behaviour.

 

Footnotes:

1. Sources for this post: As is so often the case when I am energised to ‘write it down’ in a post, the ideas within are because of a coming together (at least in my mind) between a few separate things.

The main two for this post are:

Whilst the former is about ‘the individual’ and the latter is (I think) written with respect to, say, an organisation (or bigger system), I see them as complimentary.

Richard Davis’ Chapter 4 ‘Using data’ nicely shows an example of an individual with a set of needs (as defined by them), and how they are doing against each over time.

Dave Snowden’s piece adds to, and broadens, Richard Davis’s work by naming, and clearly articulating, vector measurement.

2. Cynefin: There’s also a useful book called ‘Cynefin: weaving sense-making into the fabric of our world’ by Dave Snowden and friends

3. Sensemaking framework: I have chosen to provide a very brief reminder here. I have omitted the ideas of chaos, disorder, and liminality.

4. Employment as an example: I could have used various examples to make this point. I picked employment after reading an article about a new UK Govt. initiative called ‘The way to work’, with a target to get 500,000 into work.

The article is titled ‘Way to Work Scheme: forcing people into jobs they aren’t suited for has damaging effects’.

The article also links on to a systematic review by University of Glasgow on the research in this area. The abstract notes

“…we found that labour market studies…consistently reported positive impacts for employment [i.e. yes, we can ‘force people into work’] but negative impacts for job quality and stability in the longer term, along with increased transitions to non-employment or economic inactivity. …increased material hardship and health problems. There was also some evidence that sanctions were associated with increased child maltreatment and poorer child well-being.”

5. Dysfunctional behaviour: A reminder that this isn’t a case of ‘bad people’; this is normal people attempting to survive within their system.

6. Wellbeing: Googling the (often referenced) notion of wellbeing shows that there are lots of different (though similar) n-dimensional models of wellbeing ‘out there’.

Using the Te Whare Tapa Whā model, as derived by Sir Mason Durie, four core dimensions of wellbeing are:

  • Taha tinana: Our physical health
  • Taha hinengaro: Our mental and emotional health
  • Taha whānau: Our social wellness (e.g. a sense of connection, belonging, contributing, and being supported)
  • Taha wairua: Our spiritual wellness (g. a sense of purpose and meaning in life/ the degree of peace and harmony in our lives )

Other dimensions that feed into (i.e. will likely affect) these four core wellbeing dimensions include:

  • Our financial/ economic situation (now) & outlook (expected)
    • e.g. access to resources (food, clothing, shelter,…)
  • Our environmental situation – where we live
    • e.g. safe, clean, pleasant, cohesive, with access to facilities
  • Our intellectual situation – what we do (education, work, and leisure)
    • e.g. stimulating/ creative, productive/ useful, learning/ developing/growth, autonomous (self-determining)

7. Visualising the journey: I’m sure that there are lots of people far more skilled than me that could really ‘get into’ how to visualise a person’s journey (and probably have).

The point is to be able to see it, as a vector, moving over time, comparing ‘where I was’ to ‘where I am now’ on some useful dimensions. These could be:

  • a set of needs as identified through actively listening to the person (as per Richard Davis); and/or
  • a set of wellbeing dimensions (as derived from a useful wellbeing model)

 To clarify: This would be the opposite of scoring where the person is at on a goal set by the welfare system that is ‘managing’ them.

A reminder that the former recognises the person’s complexity, whilst the latter assumes an ordered reality…which is not the case.

8. Re. Dancing with people: This phrase might sound flippant – I have no wish to be simplistic about people whose lives are really tough. It comes from the rather nice concept as explained by Miller and Rollnick in their book on Motivational Interviewing.

It’s complicated!…or is it?

mandelbrot-setI’ll  start with a question: What’s the difference between the two words ‘Complex’ and ‘Complicated’?

Have a think about that for a minute…and see what you arrive at.

I did a bit of fumbling around and can report back that:

  • If you look these two words up in the Oxford English Dictionary (OED), then you’d think they mean the same thing; however
  • If you search Google for ‘complex vs. complicated’, then you’ll find oodles of articles explaining that they differ, and (in each author’s opinion) why; and yet
  • …. if you were to read a cluster of those articles you’d find totally contradictory explanations!

Mmmm, that’s complicated…or is that complex?

This post aims to clarify, and in so doing, make some incredibly important points! It’s probably one of my most ‘technical’ efforts…but if you grapple with it then (I believe that) there is gold within.

Starting with definitions:

Here are the OED definitions:

Complex: consisting of many different and connected parts.

  • Not easy to analyse or understand; complicated or intricate”

Complicated: consisting of many interconnecting parts or elements; intricate.

  • Involving many different and confusing aspects
  • In Medicine: Involving complications.”

So, virtually the same – in fact one refers to the other! – but I think we can agree that neither are simple 🙂 . They are both about parts and their interconnections.

Turning to the ‘science’ of systems:

scienceWhilst the OED uses the ‘complex’ and ‘complicated’ words interchangeably, Systems Thinkers have chosen to adopt distinctly different meanings. They do this to usefully categorise different system types.

Reading around systemsy literature2, I repeatedly see the following categorisation usage:

Simple systems: Contain only a few parts interacting, where these are obvious to those that look; Extremely predictable and repeatable

Example: your seat on an aeroplane

Complicated systems: Many parts, they operate in patterned (predictable) ways but ‘how it works’ is not easily seen…except perhaps by an expert

Example: flying a commercial aeroplane…where, of note, its predictability makes it very safe

Complex systems: unpredictable because the interactions between the parts are continually changing and the outcomes emerge – and yet look ‘obvious’ with the benefit of hindsight.

Example: Air Traffic Control, constantly changing in reaction to weather, aircraft downtime…etc.

“…and the relevance of this is?”

There is a right way, and many a wrong way, to intervene in systems, depending on their type! Therefore, correct categorisation is key.

A (the?) major mistake that ‘leaders’ of organisations make is they presume that they are dealing with a complicated system…when in fact it is complex4. If you initially find this slightly confusing (it is!) then just re-read, and ponder, the definitions above.

Management presume that they are operating within a complicated (or even simple) system whenever they suppose that they can:

– administer a simple course of ‘best practise’ or external expert advice…and all will be well;

– plan in detail what something will turn out like, how long it will take and at what cost…when they’ve never done it before!;

– implement stuff as if it can simply be ‘rolled back’ to an earlier state if it doesn’t work out…not understanding that, once acted upon, the people affected have been irrevocably changed (and regularly suffer from what I refer to as ‘change fatigue’5);

– isolate and alter parts of the system to deliver a predicted (and overly simplistic) outcome…by which I am referring to the slapstick ‘benefits case’ and it’s dastardly offspring the ‘benefits realisation plan’…

…Management can, of course, invoke the Narrative Fallacy to convince themselves that all that was promised has been achieved (and will be sustained)…whilst ignoring any inconvenient ‘side effects’;

– strip out (and throw away) fundamental parts of a system whilst invoking their constant simplification battle cry…because they can’t (currently) see, let alone understand, why these parts are necessary;

…and I’m sure you can carry on the list.

The distinction between ‘complicated’ and ‘complex’ fits quite nicely with Russell Ackoff’s distinction between deterministic (mechanistic) and organic systems; and  John Seddon’s distinction between manufacturing and service organisations (and the complexity of variety in customer demand).

Put simply 🙂 , in complex systems, it’s the relationships between the parts (e.g. people) that dominate.

So what?

jack-deeWell, if Management understand that they are dealing with a complex organisation then they will (hopefully) see the importance of designing their system to take advantage of (rather than butcher) this fact.

Such a design might include:

  • aligning individual and organisational purpose, by sharing success (and removing management instruments that cause component-optimising behaviours)
  • putting capability measures into the hands of front line/ value creating workers, where such measures:
  • allowing and supporting the front line/ value creating workers to:
    • absorb the customer variety that presents itself to them; and
    • imagine, and experiment with, ways of improving the service for their customers
  • …and much much more systemsy thinking

This would mean creating a system that is designed to continuously adjust as its components change in relation to one another. That would be the opposite of ‘command and control’.

Huge clarification: Many a command-and-control manager may respond that, yes, they already continually adjust their system…I know you do!!!  It’s not you that should be doing the adjusting…and so to self-organisation:

From simple to complex…and back again6

answersThe giant systems thinker Donella Meadows wrote that highly functional systems (i.e. the ones that work really well) likely contain three characteristics – resilience7, self-organisation and hierarchy8.

I’ll limit myself here to writing about self-organisation:

“The most marvellous characteristic of some complex systems is their ability to learn, diversify, complexify, evolve…This capacity of a system to make its own structure more complex is called self-organisation(Meadows)

Wow, ‘complexify’ – a new word?!…and it can be a very good thing…and goes 1800 against the corporate simplification mantra:

“We would do better at encouraging, rather than destroying, the self-organising capacities of the systems of which we are a part….which are often sacrificed for purposes of short-term productivity and stabiliy7(Meadows)

It turns out that complexity isn’t of itself a bad thing…in fact quite the opposite – a system can achieve amazing things as it becomes more complex. Just consider that, through the process of evolution, ‘we’ have ‘complexified’ (can you see what I did there) from amoeba to human beings!

…but what’s REALLY interesting is that this complexity is enabled by simplicity!

“System theorists used to think that self-organisation was such a complex property of systems that it could never be understood…new discoveries, however, suggest that just a few simple organising principles can lead to wildly diverse self-organising structures.” (Meadows)

Meadows went on to note that:

“All of life, from viruses to redwood trees, from amoebas to elephants, is based on the basic organising rules encapsulated in the chemistry of DNA, RNA, and protein molecules.”

In short: Simple rules can allow complex systems to blossom, self-learn and grow.

I believe that a wonderful, and complex, organisation can be created and sustained from living a simple philosophy.

“Simple, clear purpose and principles give rise to complex and intelligent behaviour.

Complex rules and procedures give rise to simple and stupid behaviour.” (Dee Hock)

….so what might such a simple philosophy be? Well, Deming was ‘all over’ this with his ‘Theory of Profound knowledge’* and ’14 points for Management’.

* Deming explained simply that we should:

  • Observe, and handle, the world around us as systems (which, by definition, require a purpose that is obvious to all);
  • Expose, and understand, variation;
  • Gain knowledge through studying and experimenting;
  • Understand psychology and truly respect each and every human being ; and
  • Lead through our actions and abilities.

…and a final warning against that oversimplification thing:

“Collapse is simply the last remaining method of simplification.”  (Clay Shirky)

The short ‘simple’ version at the end of the long ‘complicated’ one 🙂

‘Complexity’ is not the inherently bad ogre as persistently painted by contemporary management. Rather, it can be a defining property of our organisational system that we would do well to understand and embrace.

Let’s feast at the ’complex but right’ bookcase of knowledge, design appropriate and evolving responses based on simple scientific wisdom and climb the mountain…rather than automatically follow the crowd over the ‘simple but wrong’ cliff!

Footnotes

1. Opening Image: This image is a part of the Mandelbrot Set – an amazingly complicated (or is that complex?) image that is derived from the application of a simple mathematical formula. It sits within the fractal school of Mathematics (repeating patterns) alongside others such as the Koch snowflake.

Image Source : CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=322029

2. Systems Thinking Literature: This systems thinking is taken, in part, from a 2011 HBR article Learning to Live with Complexity.

3. Dave Snowden’s Cynefin framework is built (partly) around the difference between complicated and complex….and the importance of correctly identifying your system type before intervening. Snowden’s framework also adds the idea of chaotic systems, where there is some emergency that requires urgent action (without the time to experiment)…where the action chosen may determine how the chaos is halted…which may or may not be in your favour!

4. The inclusion of people in a system likely makes it complex.

5. Change Fatigue: This is my phrase for those people who have worked for an organisation for many years and had the annual ‘silver bullet’ change programme rolled out on them…and got bored of the same lecture and the same outcomes. It is very hard to energise (i.e. excite) someone with ‘change fatigue’.

6. Cartoon: I LOVE this cartoon! It is sooo apt. The vast majority are on the simple road, following the crowd over an (unseen) cliff…or at least not seen until it is too late. A few turn right at the ‘bookcase of knowledge’ – they take a book or two and then travel a circuitous and uphill road to an interesting destination.

7. Resilience vs. stability clarification: “Resilience is not the same thing as being…constant over time. Resilient systems can be very dynamic….conversely, systems that are constant over time can be unresilient.” (Donella Meadows)

8. Hierarchy: I’m aware that some organisations have experimented without a formal hierarchy (e.g. Holacracy). However, even they create a set of rules to assist them co-ordinate their component parts.

It’s worth noting that “Hierarchies evolve from the lowest level up…the original purpose of a hierarchy is always to help its originating subsystems do their jobs better…[however] many systems are not meeting our goals because of malfunctioning hierarchies…

 To be a highly functional system, hierarchy must balance the welfare, freedoms and responsibilities of the subsystems and total system – there must be enough central control to achieve co-ordination towards the large-system goal, and enough autonomy to keep all subsystems flourishing, functioning, and self-organising.” (Meadows)