By James Northway, Global Head of Data Strategy, Wavemaker
After a large amount of research, my family and I have just bought our first electric car – and that got me thinking about change. For a long time, EVs were only for very early adopters, and then in 2021 we seemed to reach a tipping point, and global sales accelerated rapidly. Share prices jumped, stocks ran low, and delivery times were measured in months and years rather than weeks.
Lots of change. And now things have changed again. While global sales are still growing, the rate of growth seems linear rather than exponential.
The decision to buy an EV at this moment in time says something about us as consumers (we’re clearly not first movers). As a data professional, I have also found myself thinking about what the EV market can teach us about the stages of ‘change’. Clearly understanding the forces that impact change – and being able to predict it – is fundamental for any marketer.
According to the Canadian Prime Minister, Justin Trudeau, “The pace of change has never been this fast, yet it will never be this slow again”. It would be fair to say that change is a well-trodden word. However, while vague rhetoric is powerful at signalling the need for rapid adaption, we really need to understand different types of change. Alongside the specific implications to effectively plan ahead and unlock the benefits. When it comes to marketing some key examples come to mind:
Linear change – yesterday, today, tomorrow: Although change can be uncomfortable, linear change is normally where we are in our ‘change comfort zone’ as humans and marketers. For example, the growth in smartphone adoption over the last 10 years has been close to linear, according to Statista from a billion units in 2014 to close to five billion today.
This linear change is why there never was a ‘year of the mobile’. Similarly, the Ofcom Media Nations 2023 report highlights a decline in linear TV with weekly viewing minutes in the UK falling for 25–34-year-olds from 200 in 2012 to under 70 in 2023 in a predictable linear way.
These are still hugely significant changes, driving more and different types of data and connection opportunities into our advertising ecosystems. But it is relatively easy to build strategies to adapt and take advantage of these changes, and we have more time to do it and get it right.
Exponential change – the 8th wonder of the world: Unless you were under a rock during COVID, you will have heard scientists trying to explain the significance of exponential growth, and how we as humans constantly underestimate it. Einstein of course called compound interest the 8th wonder of the world, “He who understands it, earns it … he who doesn’t … pays it”.
Exponential change is hard to manage because at first, it is tough to detect and therefore difficult to gain first mover advantage. How do you know which will take off and grow fastest, TikTok or BeReal? Equally, once it’s finally clear a trend is growing exponentially, it’s hard to catch up.
First-order phase transition – this changes everything: This type of change is where it gets interesting, or terrifying, depending on your point of view. Here, while the system itself is changing linearly, the output of the system doesn’t move at all until suddenly there is a complete phase change. It would be like Tesla selling no cars for 10 years, then suddenly in a single year, every new car sold is a Tesla. This sounds impossible, but it does happen (and maybe explains Tesla’s PE ratio!).
Generative AI is a great example of a first-order phase transition: Years of research with effectively no usable output, and now suddenly everyone can create stunning photo-realistic images in seconds. With AI we now must guess if the phase change is complete, and we can move on to adapting and benefiting from the new paradigm, or if further change is still to come.
Finding your growth in change: For marketers, linear change represents less an opportunity to get ahead, and more a risk of slipping back by getting it wrong.
Exponential change is where an advantage can be gained. But while network effects enable the opportunity for exponential growth, they can be hard to harness. An alternative (and complementary) approach is what the American marketeer Jim Collins calls the ‘data flywheel effect’. Put simply this is when the data and information created by a business are leveraged to find more opportunities to grow, and this growth in turn delivers more data. In business, the most obvious example of this has been retailers such as Alibaba, Amazon, and Tesco. In marketing, we are seeing the data wheel spin-off retail media products that in turn are returning valuable advertising and insight data.
Understanding how change works and can create growth, should be an important part of any business plan. For me and my family as consumers, this meant waiting till the EV market changes had created more affordable vehicles with better charging infrastructure. For a brand marketer, understanding the different types of change means you can make informed decisions and calculated risks – to the benefit of your brand.
It’s complicated, yes, but understanding how change can move very differently is a powerful first step to take.
