Hello all,

This week is the second part in my new series on sense-making, which began last week.

It’s easy to think of “sense-making” as anything that helps to explain something. But if we’re going to dig into it properly, even if we’re going to avoid dense academic language, we need to define it a little more specifically than that. This week’s article tries to do just that. Enjoy!


This week’s article

Defining sense-making

“Sense-making” is a useful concept, but can be frustratingly hard to pin down. What makes it what it is?

“Sense-making” can be a tricky concept to define, simultaneously obvious and elusive. In the introduction to this series, I used Dave Snowden’s appealingly simple definition: to Snowden, sense-making is answering the question “how do I make sense of the world so I can act in it”. It is a beautifully simple definition, but I can see how it also leaves a lot of room for interpretation, and is sufficiently expansive that you could use it to define almost anything as sense-making if you squinted hard enough. “Sense-making is making sense? Well, duh…”

If we’re going to get our heads around sense-making and use it as a tool, it’s important to understand what it is and what it isn’t, and to do so without resorting to highfalutin’ academic language. Is taking notes sense-making? Is writing a to-do list? Is talking about work with a colleague? Can merely thinking count as sense-making, or do you have to write something down or say something to someone else?

To me, sense-making differs in six crucial ways from other things that it superficially resembles. Sense-making is:

  1. Complex, not simple
  2. Narrative, not numeric
  3. Plausible, not correct
  4. Social, not individual
  5. External, not internal
  6. Continuous, not static

Complex, not simple

Sense-making is about navigating situations in which the relationship between cause and effect is uncertain, in which there are lots of variables, in which little is known and little is predictable. You can use sense-making while plotting the future of your career; you can’t use it to figure out a maths problem.

Narrative, not numeric

Sense-making uses stories to explain the world; it recognises that the best way to deal with complexity is to explain it in narrative form, rather than to build an accurate mathematical model of it. Likewise, it recognises that good narratives are often themselves complex and nuanced.

Plausible, not correct

Sense-making favours usefulness over accuracy. It often distorts or ignores information as necessary, in order to provide compelling narratives that are a springboard for further action.

Social, not individual

Sense-making is fundamentally communicative; it’s about telling stories to other people, listening to their stories, and together shaping new ones. It’s about collective action and collective decision-making. Narratives that are useful are retained in the social fabric of the group, and shared in the stories that they tell; ones that aren’t are discarded.

External, not internal

Sense-making is about your relationship to the external world. It’s about responding to your environment, which in turn has the potential to shape and re-shape that environment.

Continuous, not static

Sense-making is not about coming up with definitive, final explanations for things. It’s a process of continual refinement, adapting and reacting to the situation as it changes and incorporating new information into narratives as appropriate.

Pulling all that together, we can arrive at a definition that perhaps lacks the pithiness of Snowden’s, but that ticks all the right boxes. Sense-making is a continuous social process by which people come to both understand and shape their environments, explaining complex situations through plausible narratives that are then adopted and refined by others.

As the series progresses, we’ll dig deeper into the implications of some of these points, and how they apply to real-world situations and organisations.

Click here to read the article »

This week’s three interesting links

Britain is Dead

Samuel McIlhagga strikes a pessimistic note about Britain’s prospects:

“The overall trajectory becomes obvious when you look at outcomes in productivity, investment, capacity, research and development, growth, quality of life, GDP per capita, wealth distribution, and real wage growth measured by unit labor cost. All are either falling or stagnant. Reporting from the Financial Times has claimed that at current levels, the UK will be poorer than Poland in a decade, and will have a lower median real income than Slovenia by 2024. Many provincial areas already have lower GDPs than Eastern Europe.”

…and, most interestingly, digs into the long historical context that leads up to this point; this modern malaise has deep roots. #

The Platypus in the Room

Drew Breunig compares AI to a platypus – usefully, as it happens:

“When trying to get your head around a new technology, it helps to focus on how it challenges existing categorizations, conventions, and rule sets. Internally, I’ve always called this exercise, ‘dealing with the platypus in the room.’ Named after the category-defying animal; the duck-billed, venomous, semi-aquatic, egg-laying mammal.

“There’s been plenty of platypus over the years in tech. Crypto. Data Science. Social Media. But AI is the biggest platypus I’ve ever seen… Nearly every notable quality of AI and LLMs challenges our conventions, categories, and rulesets.”


Normalising Feedback

Lingjing Yin thinks about how to get better at delivering feedback within teams, something that people are generally pretty bad at:

“How might we treat feedback as an opportunity to learn rather than to teach and go into it with a curious mindset to explore the strengths, gaps and opportunities of each other and the context we are part of?”