Cursor Curated
9th January 2024

How to plan for uncertainty

Predictability is a relic of the past

Cursor Curated Issue 25

Daniel Westlake

If 2023 has taught us one thing, it's that we live in an age of increasing uncertainty and volatility. The only thing we do know is that the future will be different and unexpected.

Looking ahead in 2024 is, therefore, a bit like trying to read a book in the dark. With global conflicts, a bumper election year and AI threatening to reshape our landscape; social, technological and economic change makes it increasingly difficult for leaders to plan for the future.

One valuable tool I have repeatedly used to navigate complex, changing situations throughout the past 20+ years at Cursor is the Cynefin framework.

The word 'Cynefin' (pronounced ‘ku-nev-in’) is Welsh, signifying a place, situation, or habitat.

Developed to help decision-makers navigate complex, complicated and chaotic situations, Cynefin offers a simple methodology to categorise and respond to different challenges.

Its appeal stems from its versatility, allowing it to be effectively applied to a wide range of scenarios. This ranges from minor, routine changes facing small teams to significant, strategic decision-making in large organisations.

This makes it a worthwhile addition to your decision making toolkit as we head into the new year.

Follow the procedure

Fundamentally the Cynefin framework categorises problems into several domains, starting with the 'Clear'. Sometimes people call this the 'known knowns' which refers to situations where both the problem and the solution are clear. However, I’m not keen on this language as I find it difficult to visualise so for now, let’s just stick to Clear.

For Clear problems, we know what to do and how to respond. We may even have a procedure in place which tells us what to do and how to do it. There is a single right way to do this and we should do it this way every time (like making a cup of tea for a colleague).

As leaders, we shouldn’t be worried about these types of problems. We can put a process in place and then you, or your team, can deal with it. These are also the situations where automation can often be applied due to the predictable nature of inputs and outputs.

The challenge often lies not in dealing with the problem itself but in selecting the appropriate procedure to follow. Once this decision is made though, action can be taken with confidence.

It's complicated

Unfortunately not all problems are clear and simple.

Many fall into the 'Complicated' category, where a single procedure doesn't fit all situations. These issues require deeper analysis and judgement, drawing upon existing expertise and experience. Complicated scenarios are common in software development and legal contexts, where specialists must dissect a problem to find a tailored solution.

A lot of our work at Cursor sits in the Cynefin domain of Complicated.

Consider the task of moving a website to a new domain. This process involves several interconnected steps: setting up redirects, maintaining SEO, and managing infrastructure changes and transaction processing.

The complexity of these tasks requires specialised knowledge and a nuanced approach. However, someone with a suitable level of expertise should be able to recommend a solution, based on best practices that are adapted to individual circumstances.

If I'd known that from the beginning

In the face of complex challenges there aren't always clear-cut right or wrong answers. Sometimes you look back on a complex project and only see its true nature in retrospect. Cause and effect seem to happen in mysterious ways at the time, but later, when more facts are known, the pattern will often emerge.

Business growth and changing company culture are both examples of the ‘Complex’ domain in Cynefin. They are problems that can’t be broken down into clear steps so leaders should avoid thinking of complex problems in the same way as something that is complicated.

When faced with a Complex problem (unknown unknowns, in the unhelpful lingo), a leader should create an environment where experimentation and data lead the decision making process.

This can be difficult to achieve culturally. Leaders are sometimes reluctant to say that they don’t know what to do. Instead, there can be a menu of possible solutions and it is the job of leaders to explore these different options, and gather data in a way which is quick and ‘safe to fail’.

Agile software development sits nicely with the ‘probe-sense-respond’ nature of Complex problems. You can make small changes, monitor the results of user behaviour and use that data to make further improvements. These improvements might be small but over time they can add up to business changing success.

Analysis paralysis

Then there are 'Chaotic' situations, where rapid changes and unpredictability prevent a reasoned, data-driven approach. Examples of Chaotic scenarios include market crashes or major cyber attacks - these are the kinds of scenarios where time is decidedly not on your side.

Action, indeed any action, is better than analysis. Don’t look to gather data or consider which is the ideal response, just act.

Rapid, decisive action will help to bring order to the chaos, moving a chaotic situation into a more orderly (Complex or Complicated) one where data and experience can come into play.

How Cynefin helps to manage uncertainty

The Cynefin framework doesn't prescribe specific decisions but guides leaders on the type of decision-making suitable for each situation.

As understanding of a problem deepens, its classification may shift from Chaotic to Complex, then to Complicated and eventually Clear.

Organisations often face multiple issues simultaneously across different Cynefin domains. For instance, a company dealing with a major incident might have teams addressing immediate chaotic aspects, others analysing parts of the problem with more data and some maintaining regular operations.

Although in most occurrences situations move from Chaotic towards Clear as they are managed and understood, occasionally a situation can move the other way. An example of this in action could be in an industrial context where a system appears to be working fine until suddenly it’s not. Things can appear to be under control but reality can be different and it takes the resulting chaos to erupt before operators realise that things weren’t as steady as they once appeared.

The Three Mile Island incident is a prime example, where incomplete data led to a misunderstanding of the situation, exacerbating the crisis.

Even with a brief introduction like the one I’ve provided above, Cynefin can be a helpful tool for leaders to be aware of when they are faced with how to make decisions in an uncertain situation. For those looking to delve deeper, there is much more material on the subject to explore!