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TB871: Responding to change (and junking a lot of perfectly good habits in favor of awkward new ones)

Posted on by Doug Belshaw

Note: this is a post reflecting on one of the modules of my MSc in Systems Thinking in Practice. You can see all of the related posts in this category. 

Systems Thinking, to me at least, is about making strategy to change something within an organisation, or in an environment that contains organisations. As such, the fact that something is going to change is a given.

The received wisdom is that “people don’t like change.” But that’s not necessarily true, especially given what I’ve discussed in previous posts about personality and personality differences in teams. The module materials (The Open University, 2020) discuss Oreg’s Resistance to Change Scale and the four factors defining a disposition towards change:

  • Routine seeking
  • Emotional reaction to imposed change
  • Short-term focus
  • Cognitive rigidity.

Plotting these against the ‘Big Five’ personality traits leads to some interesting findings:

Table showing correlations between 'The Big Five' personality dimensions and resistance to change.
Table taken from module materials (The Open University, 2020)

As you can see, the table indicates that the strongest correlations are observed with extraversion and neuroticism. It suggests that individuals with a tendency towards neuroticism are more inclined to resist change, demonstrating positive correlations with routine seeking, emotional reaction, and short-term focus. On the other hand, those with a tendency towards extraversion show negative correlations with these factors, indicating they are less prone to resistance to change behaviours.

Beyond these strong correlations, the relationships between the Big Five dimensions and resistance to change factors are perhaps more nuanced. For instance, conscientiousness is positively correlated with routine seeking but negatively correlated with short-term focus, suggesting a complex interplay between an individual’s drive for order and their capacity for long-term planning. Openness, meanwhile, shows no significant correlation with any resistance to change factors, indicating that those who are open to new experiences do not necessarily exhibit higher or lower levels of resistance to change.

Resistance to change, though varying in intensity based on circumstances, is a natural trait to some extent in everyone. It includes scepticism, inertia, and ‘reactance’, which is a term borrowed from electronics, and defined as an immediate and unpleasant emotional response to perceived threats to freedom.

While resistance may be more pronounced in some individuals, possibly due to learned behaviours from childhood, studies show that there is no significant gender difference. However, greater resistance to change is more commonly found in younger people compared to older individuals, which I find interesting (and certainly backed up by my experiences as a parent). I think this is probably to do with people who have less knowledge of the world seeking reassurance through routines. But I’m speculating.

Reflecting on my own life, as someone who is apparently open, conscientious, introverted, strong-minded, and moderate, I have a complex relationship with change. In both my personal and professional life I enjoy strict routines but understand that these are temporary constructs. Regular readers of my blog will be unsurprised to see me reference once again Clay Shirky’s reflection that “current optimization is long-term anachronism” (Uses This, 2014). I’ve been validated and inspired over the last decade by his casual mention that how, “at the end of every year” he “junk[s]” a lot of perfectly good habits in favor of awkward new ones” (Ibid.).

References

TB871: 5 reasons why the unknown is not just a temporary or local state

Posted on by Doug Belshaw

Note: this is a post reflecting on one of the modules of my MSc in Systems Thinking in Practice. You can see all of the related posts in this category. 

A photograph of the vast, seemingly endless ocean, and sky.

The module materials (The Open University, 2020) outline five really useful reasons why the world is fundamentally unknowable:

  1. The overwhelming complexity of networks
  2. Processes that control stability and instability
  3. The unpredictability of developing patterns of relationships
  4. Social messes can be wicked
  5. Situations are not situations

Let’s consider at each in turn.

1. The overwhelming complexity of networks

Each person has a great number of different types of connections with humans. This exists within a vast network of close and distant relationships. So even with a relatively small number of people, number and nature of connections becomes highly complex. This increases exponentially when considering national or global populations, where a small number of individual connections contribute to an unfathomably large and intricate network. Counter-intuitively due to their size and complexity, large networks can often be resilient and maintain structural stability due to the sheer number of nodes.

The inherent stability of these networks does not mean that individual outcomes cannot be unpredictable. Emergent outcomes and behaviours can be unknowable and unexpected, for example as we’ve seen with the assault upon online social networks through misinformation, hacking, and more. Rather than anticipating specific outcomes, we live in a world where we need to focus on preparedness and reconsider what ‘stability’ looks like. Historically, ecosystems and cultures have changed rapidly due to ‘tipping points’ that we’ll consider in the next section.

2. Processes that control stability and instability

There are two types of causal loops that are used primarily by systems thinkers: balancing loops and reinforcing loops. While balancing loops help maintain stability, reinforcing loops lead to growth or collapse. The idea of ‘tipping points’ is often used to identify how these loops form, although they can be triggered by tiny changes, which makes them difficult to predict.

Reinforcing loops explain why ‘first impressions’ are often seen as so important. For example, an initial positive or negative interaction can set of an chain reaction and compound and reinforce that first impression. Similarly, ‘trophic cascades’ in ecosystems shows how complex interactions can result due to the presence (or absence) or predators; multiple potential tipping points exist, so a single ‘tipping point event’ can trigger a cascade of others.

3. The unpredictability of developing patterns of relationships

There is something called Conway’s Game of Life which I don’t completely understand, but apparently is a mathematical simulation which uses simple rules to generate complex behaviours. I prefer the example of birds flying in formation, to be honest, but the point is the same: simple, rule-based systems can produce intricate, delicately-balanced outcomes that can be difficult to predict.

This obviously causes significant challenges around strategic planning. If we fit humans into stable patterns, then we can plan base on linear, predictable responses. If behaviours deviate, then planning becomes more complex. This, I suppose, is the difference between Homo economicus which is the rational view of humans presented by economic theory and, well, how humans actually act in the real world. As a result, strategic planning needs to recognise and address blind spots, stay flexible, and be aware how assumptions influence behaviours.

4. Social messes can be wicked

A ‘wicked problem’ is a form of unpredictable social mess that I’ve discussed before as part of this module, as well as in TB872. It’s “a complex, multifaceted problem with no clear solution, often characterized by interdependencies, changing requirements, and multiple stakeholders” to quote the latter post.

As I reflected on separately in a post about the croquet game in Alice’s Adventures in Wonderland, structured problem-solving is difficult because people don’t always ‘play the game’ or even understand the rules. Real life problems are somewhat unruly. They are often embedded deeply within complex networks of relationships, and can ‘cascade’ much like the trophic cascade within ecosystems mentioned above. There are conflicting perspectives, for example relating to the climate emergency, or rewilding, or almost anything you can think of. The only way to really deal with this complexity is to involve diverse stakeholders and be open to creating entirely new approaches.

5. Situations are not situations

Following on from ‘wicked problems’ the notion that ‘situations are not situations’ is a way of highlighting that our attempts to address or even contemplate a situation alters it in some way. It’s a bit like Schrödinger’s cat in that respect, because we’re never dealing with a fixed target, but rather a construct of language. Italian physicist Carlo Rovelli writes that, “a storm is not a thing, it’s a collection of occurrences” which starts to help us out of our linguistic trap of seeing stability where there is none.

Systems thinking therefore needs to embrace the fact that situations never stop changing. This means that tradition decision-making methods are likely to be ineffective, and even incremental change approaches might be limited in success because they assume static conditions rather than dynamic contexts. We must instead account for a fluid world in which we design or organise against a background of constant transformation.

References

Image: Dim Hou

TB872: Avoiding systemic failures

Posted on by Doug Belshaw

Note: this is a post reflecting on one of the modules of my MSc in Systems Thinking in Practice. You can see all of the related posts in this category.

When it comes to managing change effectively, the goal is to do it in a way that prevents the kind of problems that affect the whole system. These kind of problems are called systemic failures, and often bring unexpected negative results that can ripple through the entire structure we’re dealing with — whether it’s a business, a healthcare system, or a community.

The ‘sweet spot’ we’re aiming for is to make changes in a way that fits well with what everyone wants and what actually works in the real world. In other words, changes that are not only good in theory but also work well in practice (and are accepted by the culture of the organisation).

Situational change dynamic of focus in this module – change in situations over time (S1 to S2 to some future Sn) brought about by changes in what is considered systemically desirable (as understood through systems thinking in practice) and culturally feasible.

For example, with reference to the above diagram from the course materials, let’s say we’re looking at a situation where we want to make some changes (Situation 1 or ‘S1’). We’ve got an idea of where we want to get to (Situation 2 or ‘S2’). We might even have a vision for the future beyond that (referred to as ‘Sn’). The trick here is therefore figuring out what changes will be both systemically desirable (good for the system as a whole) and culturally feasible (acceptable/practical within the cultural context).

The diagram is like a map showing the journey of change which is a bit like watching ripples spread out after throwing a stone into a pond. The ripples represent the waves of change. The horizontal axis shows the extent of culturally feasible change over time, which we can understand as what changes the culture will accept, and when. Meanwhile, the vertical axis shows the extent of systemically desirable change over time, which we can understand as the changes that would be good for the system.

This is really interesting to me, as there are definitely some places that I’ve worked that were very resistant to change even when there was a general understanding it would be good for the whole system. Likewise, there have been others where they have adopted change much more readily.

Usually, though, getting the organisational culture to accept change takes longer than the amount of change that’s desirable. I usually sum this up by saying that humans are more difficult to deal with than technology! This discrepancy between desirable change and culturally-feasible change creates a pattern in the ripples (aka the journey of change).

When we’re trying to ‘manage’ change, therefore, it’s a constant balancing act between what’s best for the system with what the culture will support. This makes a lot of sense based on my career history. It’s basically an ongoing process of enquiry and understanding, specific to the context we’re in. It’s definitely true that what works in one place might not work in another, even if the context superficially looks similar.

The last thing to say is that what’s considered systemically desirable and culturally feasible now may change in the future. I guess that’s a bit like the Overton Window, but from system change perspective. Our job, of course, is to navigate this changing landscape carefully and thoughtfully.

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