If they have diverse experience, chances are, when confronted with new challenges, they can quickly call upon a rich database of potential solutions. On the other hand, a less experienced coder would need to invest more time to experiment with and explore the efficacy of new patterns, in order to find a solution.
Our memory is a database for such patterns. It stores patterns contextually, and is optimised for speed. This speed allows us to take the cognitive shortcuts that enable us to draw conclusions quickly. And the more experience we've had – the more patterns we have observed – the more cognitive shortcuts we have at hand.
But this speed comes at a cost – accuracy. Despite what we may think, our memory is often an inaccurate source of information, influenced as it is by myriad factors – such as our emotional (psychophysiological) state, time elapsed since we recognised the pattern and our current context.5 This means that many of the patterns we call upon to inform our default thinking may be inaccurate in any given context or moment – or even no longer valid or relevant in this new context. Thus, without challenging our own default thinking, we may be proceeding with flawed assumptions.
Default thinking is not the result of consideration or any form of reasoned, intuitive or active thought. It takes effort to draw awareness to the potential inaccuracies or inherent biases within our thinking. Such effort is confronting, and slows down the cognitive process and decision-making, running counter to the efficiency and productivity we need for most of our work.6
Of course, it would simply be infeasible to engage in slow, deep and thorough thinking for every facet of business – we'd get nothing done. It'd be silly to go back to the drawing board when attempting any new task.
And so systems are created to help us to manage increasingly complex patterns of work.
SYSTEMS
Most organisations today simply would not function without clever systems. Systems keep entropy at bay.7
Whenever we've got multiple, interconnected patterns happening, we have the opportunity to create systems to increase our efficiency and avoid wasted effort.
I use, and love, a heap of systems – one being the software I'm writing this book with, and the operating system that nests it. These complex systems were developed by very intelligent teams. Short of an ecosystem or the human body, few systems are quite as complex.
But not all systems are of such a high order.
Take the typical sales sequence, for example. I've chosen ‘sales' because it is a fairly universal function within any business or organisation – even if your organisation or business unit doesn't sell products or services for money, value is still generated and a currency of exchange is still at play.
The typical sequence looks like this:
1. First, a business needs to generate leads (‘leads' being code for ‘potential opportunities'). Assuming you are doing something of value, generating leads could look like advertising, marketing, public relations or networking. In my world, leads are generated as a consequence of doing great work with clients (which generates referrals), sharing fresh research and insights (via my ‘making clever happen' museletter), speaking at conferences, running our own events, and publishing research and books like this. Each of these activities is also a collection of patterns – but they form part of this bigger sales sequence.
2. Once leads are generated, they need to be qualified. If your organisation trades entirely online, your situation may be that the customer is self-qualifying, and your focus is on enhancing conversion. But if your organisation is service-based, or you engage in business-to-business sales, you likely need to qualify your leads. This means sorting out the valuable opportunities from the dead ends. In my world, we scare the tyre kickers away with our fee guide.
3. Next comes the nurturing. Some sales cycles are incredibly short, and as such, minimal client nurturing is required. A sales rep might know the typical questions that prospects have about a product, and be able to easily call upon the right answers for these questions. Other sales cycles are incredibly long, and require a lot of client nurturing. An example might be a large organisation adopting a new piece of software for tens of thousands of their employees – it's a big decision. Eventually, with enough nurturing prompts and the right frequency of positive interactions, clients are ready to consider investing in the work.
4. Then comes the pretty proposal. Once prospective clients are primed and ready to buy, some sort of proposal or agreement is required. This may be something automatically generated, like a software license agreement, with pricing structures that scale in proportion to the number of users. Or it could be manually generated. I used to spend a heap of time on these (mainly on design and layout), but over time we had developed enough confidence and experience to be able to recognise patterns and present proposals that frame our methodology and value (without getting bogged down in detail).
5. Then comes doing the work. And providing the value (although of course, you'd want to be providing value before any proposal is submitted). This nests a whole heap of systems and patterns too. Patterns, patterns everywhere! But sometimes we have good systems to corral them into something manageable.
And that's kind of how we make sales happen. Each step nests its own level of complexity but, not to worry – we have a system to manage this complexity. If you're a small business, your system might look like a spreadsheet that lists the current status of particular opportunities. If you're a bit more advanced, you might be using customer relationship management and/or sales pipeline software as your sales system. Thanks to these systems, we can track where various opportunities are at, and can ensure we are investing the right effort in the right folks at the right time.
But this is an incredibly simple example of a very small and agile thought-leadership practice. As things scale up, things get much more complex. Multinational corporations live on the other side of this spectrum, and need to embrace a broader mix of systems in order to coordinate efforts on a global scale. These may include systems for performance reviews and compliance, inductions and on-boarding, communications, professional development, succession, distribution, legal considerations and disputes, and so on.
And these systems work too – 80 per cent of the time. Until the world changes and they become irrelevant.8 In these cases, fortune favours those who are able to adapt to new systems. But this only happens if we have viable alternative options beyond the default.
Hey, here's another element of default thinking – and something found within many systems – templates.9
TEMPLATES
‘I'm glad you love Jason's doodle'. This statement came from a virtual assistant I once employed, in response to a senior HR director's email.
The response created a mighty awkward situation, but let me explain the details.
The HR director had just written to express their gratitude for a closing keynote I had recently delivered at their annual conference. In this keynote, I shared some of my visual notes from the event – ‘doodles', one might call them. The plural is important.
Around the same time, I had developed some systems to guide my virtual assistant through the complexity of my business. Virtual assistants were all the rage back then, and my business hadn't matured to the wonderful point it is at now where I have a closer and more experienced local team (in real life, not just virtually).
But
Not to mention a swag of cognitive biases (see chapter 14).
You may have already suspected this, but I'm setting up ‘default thinking' to take a fall. Don't get me wrong – it is utterly brilliant for 80 per cent of our work.* If you're looking to replicate existing work more efficiently, to simply tick boxes, be productive, get shit done and progress formulaic processes with predictable outcomes, your ability to recognise patterns, take cognitive shortcuts, leverage past experience and run with default thinking is an absolute asset. But – and it's a big but – if you're looking to venture beyond the default, to truly innovate and pioneer into uncharted territory, you need to 'ware the perils of our default thinking, lest we meet the Inevitable Kraken of Doom.
* Where did I get this figure from? Not research. It just seems ‘about right' – I essentially defaulted to the Praeto principle, which states that (for most events) roughly 80 per cent of the effects come from 20 per cent of the causes. And why did I do this? Because it serves as a good reference point. And that's what default thinking can be, if we can heighten ourselves to see it: a reference point for decision-making. But not the only reference point.
Or, at least, they attempt to – but entropy relates to increasing disorder (the higher the entropy, the greater the disorder) and disorder will always win, in the end.
Or, in some cases, organisations and their leaders grip onto systems that no longer serve the business model – which is akin to gripping the railings of a sinking ship.
Let's just pause and reflect on how bad that segue was.
