Category: Irregular ideas

Of all the rooms in our homes, the kitchen has been through the most change over the last hundred years. The introduction of running water, the electrification of domestic products, more consumer goods and the invention of the supermarket to make those goods available, and connecting of domestic goods to the internet. Driven by convenience for those using kitchens and competitive supply-and-demand market forces, the modern kitchen shows us what effective transformation could look like. Contrast this transformation with that we see taking place in our work environments and we can see that the way we think about digital transformation is all wrong.

Digital transformation in companies is driven by old thinking. It is usually approached like any other IT project; budget secured upfront, eighteen month project plan produced, new infrastructure procured, rolled-out to end-users who didn’t have a say. Products and systems are implemented to meet the needs of organisation, with little thought given to how easy it will be to use. Taking our lesson from the transformation of the kitchen we can see that one-sided approaches driven by business needs only will fail. Transformation means transforming the thinking and the technology.

The shift to digital thinking happens as the old-school IT managers step aside for digital managers with experience of consumer-focused digital products and treating the end user as the customer. The shift to digital products happens as B2B software providers recognise the shift in the market and focus on end-user needs and offering a great user experience.

These two interdependent changes will bring about the digital transformation companies have been looking for. The transformation of the kitchen taught us that it takes both sides of the supply and demand equation to balance in order for transformation to happen. The organisations have to want digital products that provide excellent user experience, and the providers have to develop them. When the CRM is as easy to use as Netflix, and the finance system as easy to use as a Stripe, then we can call digital transformation a success.

Pirsig, wrote in Zen and the Art of Motorcycle Maintenance, “If a factory is torn down but the rationality which produced it is left standing, then that rationality will simply produce another factory.” This quote has been used by many to illustrate the difference between our underlying systems of thought and the tangible results of that thinking, and to point out that merely changing the outputs without changing the process that produced the outputs is no change at all.

We see this in large change initiatives across organisations. Change is planned in the way all other work has always been planned. Outputs may be achieved but the usual ways of doing things continue. No change in thinking. More often than not we don’t want to change. If we did, we’d have done it already. Much easier to continue as we were and focus on the appearance of change through pre-planned outputs.

If we want to change we have to find ways to change the way we change. And it isn’t that difficult. We ask, “how do we do this now”, and then decide not to do it that way. Try something else. Experiment. Design the way forward as we go. Change shouldn’t have predictable outcomes, it should be uncertain and with results that emerge as it progresses.

The idea of the ‘meme’, introduced by Dawkins and derided by others as not scientific, attempts to offer some explanation about how ideas spread through a culture. Although the rules for transmission haven’t been fully understood yet, Deutsch says, “new ideas have to provide ‘good explanations’ for phenomena”, which means that for memes to spread the idea embodied by the meme has to make sense. It needs to be relevant, appropriate, acceptable, at least to some people, in order to spread. Random and nonsensical ideas don’t spread. Ideas that seem random and nonsensical to some people spread with others because they become part of a ‘memeplex’.

A memeplex occurs where a number of compatible memes join together in mutually supportive ways. New ideas piggy-back on well established ideas, memes come together to change each other, some memes replace others. Memes have a hard time on their own. Where we’ve seen new memes become well-established it is because they have had a strong association with a set of already well-established memes. Having an understanding of how ideas spread is a fundamental skill for the digital age. It helps us make choices about adopting ideas for ourselves based on the value of the idea rather than its association with other ideas we accept.

At the start of 2021 there were 5.5 million small businesses (with 0 to 49 employees) making up 99.2% of the total number of businesses in the UK. If you were to look at a graph of businesses by number of employees you’d see a power law distribution with a long tail of all those small businesses. Over the coming years, the creator economy will extend that tail much much farther.

As people look to diversify income, prompted by uncertainty in the labour market, and inspired by social media, or to justify their hobbies, or demonstrate their potential to employers, we’ll see the number of creators increase dramatically. The creator economy, ranging form influencers on YouTube and TikTok to solopreneur using no-code tools to build software products, has a current market size of around $104.2 Billion. If that isn’t sufficient for it to be taken seriously, then perhaps we can say that the creator economy will have jumped the curve when a one-person business disrupts an industry in the way we’ve become accustomed to startups doing.

Why does it matter? The trends that start with the creator economy will affect how large companies do business, how workers approach employment, and how people engage with brands. There’s a lot more to it than some guy riding around on a broomstick.

‘Post-truth’ is a political term used to describe the public burial of “objective facts” by an avalanche of media “appeals to emotion and personal belief” But philosophically, “post-truth” is not simply the opposite of truth, it is concerned with how we regard the nature of truth, fact, consensus, influence, trust, evidence and reason in the increasingly noisy infosphere.

The problem with the search for truth is that, more often than not, it is used as a means to create ‘one’ truth. The truth denies multiple points of view in favour of what the majority agree. It isn’t truth we seek, it’s consensus. When enough people believe the same as we do, we feel belonging, emotional connectedness, safety within our group. When enough people agree to the same narratives we have culture and society. Noah Yuval Harari says that, in a sense, humans have always been post-truth because we’ve always favoured narrative over empirical facts. Post-truth in the political realm, skewed and amplified by social media, is an extension of a culture of story-telling. And like all good stories there are heroes and villains, twists and turns, but, hardly ever it seems, a happy ending.

We like to push our opposing narratives. Insert whatever novel and contentious thing is the latest trend on Twitter and we’ll see opinion coalesce into group identities that attack alternative points of view. Even academics, who we might expect to be intellectually curious and rationally robust in how they approach things that are yet to reach the status of empirically verifiable facts, are still drawn into attacking alternative opinions in defense of their own.

Different ways of looking at something are a good thing. They help us question our thoughts and balance our opinions and reach a better understanding… if we let them.

Humans have organised themselves for as long as there have been humans. Tribes, hunting parties, religions, clubs, gangs, businesses, social media audiences. We have relied on our ability to organise ourselves and others to get the species to where it is today, for better or worse. Without it we could not grow enough food, build a cathedral, or launch rockets into space.

In Game Theory the coordination problem tells us that if we all work together for a shared goal then we all benefit. Coordination, then, means agreement about the goal, and about how to achieve it; that it is a goal worth working towards, and who is going to do which piece of work. The bigger the goal, the more people it takes to achieve it. The more people who work towards the same goal, the more coordination is required.

Frederick Brooks showed us in The Mythical Man Month that complex work cannot be perfectly partitioned into discrete tasks that can be worked on without communication between the workers, and that adding more people to do the work increases the need for coordination to the point where people spend all their time communicating about the work instead of doing to work.

Despite the obvious ridiculousness that this way of approaching work leads too, it isn’t a lesson the majority of organisations have learned. We still hold onto the mindset that in order to accomplish something we need to be coordinated with others, and to accomplish bigger things requires more coordination.

But what if, instead of action being coordinated along with the goal, individuals could choose their own way of contributing towards the goal. What if we could do our own thing in pursuit of a shared goal without requiring our efforts to be coordinated. Maybe we could achieve more, and achieve it more quickly, if we didn’t rely on quite so much coordination. Maybe we can switch off multiplayer mode in the game of life and still accomplish our goals.

‘Islands of coherence’ is a phrase the physicist Ilya Prigogine used to describe ways of approaching change in complex systems. He said, “When a system is far from equilibrium, small islands of coherence have the capacity to shift the entire system”.

Mistakenly, we often apply reduced, mechanistic, cause-and-effect thinking to creating change in complex systems. And we tend to expect that we can predict and control the outcome of something we do within a complex system. We’re always wrong.

We are part of multiple complex systems that interact in unpredictable ways. Our aim for change shouldn’t be to develop some grand plan but instead to create our own islands of coherence in our own situations and systems. And perhaps islands can connect with other islands, not in an attempt to bring order to the complexity as that would be flawed goal, but to shift the system in ways that that benefit those affected by it.

Human Centred Design was coined in 1958 with the convergence of trends from engineering, art and psychology, and over more recent decades became popularised as ‘design thinking’. HCD takes a humanist perspective in assuming that humans are autonomous, conscious, intentional.

So, why has it had it’s day? Because we’re beginning to understand the negative consequences that worldview has created. Humanism, individualism and human centred designed place the human as separate from nature, and make action and interaction a point-in-time event with linear consequences only occurring for the person being designed for. Push that button, buy that thing, you’ll feel better for it.

Posthumanism critiques this perspective and says that the systems around us have far more influence and control over us than we realise or would like to admit. Systems-shifting design is an emerging practice that is aligned with posthuman perspectives and that places greater emphasis on understanding and designing for the systems we interact with.

Rather than seeing design as being about driving a user to perform an action, it can be about shaping relationships and interactions with everything in the system. Rather than designing the solution for an isolated individual end-user, systems-shifting designers will look for points to intervene in systems and create alternative spaces where solutions can emerge.

Symbolically associating a colour with a direction may be one of the oldest ideas in the world. Ten thousand years old. That makes the symbolism of direction one of the most deeply embedded ideas across all of human civilization and culture. For the Mayans, and other Native Americans the colour white was associated with north, red was associated with east, black with west, and yellow with south. For the Hopi, north west was yellow, south west was associated with blue/green, red for south east and white for north east. In ancient China, north was associated with the colour black, east with green, south red, and east with white. Similar colours, similar directions, sometimes with different associations, but always an association between a direction and a colour.

Why should these ancient symbolic associations matter to us today? Because the symbolism of direction is very much with us in modern society. In the northern hemisphere at least, north is associated with moving forward, with progression and advancement towards an intended destination or goal. We use the metaphor of the north star as a guide for setting a preferred direction. On computer game controllers, up is forward. Our sense of direction, and the symbolic meaning we associate with them gets embodied into our technologies and the virtual and conceptual worlds they create.

As talk of creating metaverses and virtual reality environments increases, we would do well to consider how physical direction gets represented in these spaces. Does it help to orientate, or disorientate us? Will these immersive online worlds lack the symbolism we’ve relied on for so long? And what might that do to our sense of the real world?

How often we are surprised by new and unexpected information can give us a good sense of how much uncertainty there is in our work, our lives and our world in general. This sense of surprise is different from simply learning new things that fit within our worldview and don’t appear unexpected to us. For something to surprise us it has to be both new and unexpected. And how often we feel surprised, that is, how many times over a given length of time, gives us a sense of the rate of surprise. A high rate of surprise might suggest impending futureshock; the phenomenon of experiencing too much change in too short a period of time.

Why might we want an indicator of uncertainty? In most organisations, uncertainty is regarded as a bad thing. For the purposes of discussing this idea, ‘organisation’ means any group of people coordinating themselves to achieve a shared goal. A group of mates getting together for a game of football falls under this definition. If they experience too much uncertainty because they don’t know who is coming, where they’re meeting, who’s bringing the ball, etc., etc., then they’ll be unable to achieve the shared goal of playing a game of football. Continuing with this example, which applies equally to any means of organising and coordinating people, if all of those mates agree where they’re meeting, who’s bringing the ball, etc., but then some of those expectations don’t happen as planned, then there is surprise. Organising reduces uncertainty. Surprise indicates unexpected uncertainty.