Trends, Visions, Signals and Assessing Potential Futures
In a recent futures studies lecture our group was asked to define a couple of seemingly simple terms, like “trend”, “megatrend”, “wildcard”, “signal”, “cultural shift”, “acceleration” and so on. I already knew that people use them differently depending on their background, but I was surprised how many viewports actually existed — even in our small group. Having diverse backgrounds, our group engaged in long discussions, trying to understand each others viewpoints and experience in approaching and applying these terms and the concepts they represent.
So as an attempt to broaden the discussion, I thought I might share how I see a couple of these terms and how I apply them in my daily work myself.
Trends as directional indicators
Let’s start with the easy one. Trend is a relatively well known and established term, so I usually point to the official definition. Merriam Webster for example has a couple of definitions for the word “Trend”, and they all roughly describe a measurable change in something. So in terms of cultural trends, these would be changes in behavior among a population of individuals.
Trends are not self-fulfilling. Every trend needs a driver, some kind of reason that causes the change in the first place. These might be based on human factors, on technology, the environment and so on. I find it useful to understand the drivers to understand the potential scale and impact of a trend.
For example I believe that the trend to create the Internet of Things is not driven by convenience or better user experiences, but by the rule of scale. Based on this assumption I can apply different lenses to the trend and assess the impact.
Signals from potential futures
I see them as “Signals from potential futures”, that don’t necessarily belong in our present (yet). So usually I look for “Something real, that didn’t reach critical mass”. Real means that there is an actual product or service or procedure that is (or was) used commercially and that could scale if needed. Not reaching critical mass means that although it could scale, it is not widely adopted outside a specific circle of users.
An example for this could be the Apple Newton. It was a real product that sold commercially, however it was only popular in a small number of specialized industries as it was too limited and expensive for mass market adoption. That said, it was a great signal that would lead to the Palm Pilot, Nokia Communicator and later the iPhone.
Visions about potential futures
A vision is “Something fictional, but shared and understood by a critical mass”. So in contrast to signals, there never was a real product, however the concept or principle is known and understood on a society level.
Pop culture artifacts (books, movies, TV series and so on) are usually a large driver of visions. Sometimes they even feed themselves when one movie introduces a concept, which is then picked up by other pop culture media formats. These might be fictional products that protagonists use or just concepts that these products are based on.
An example of this could be Dick Tracey’s 2-way wrist radio, which led to generations of children talking to their wrist watches during play. These visions can influence how we think about products and services to a point where the industry sees potential to create them for real. When Tim Cook announced the Apple Watch, he said “I have been wanting to do this since I was 5 years old”.
How I use signals and visions to assess products and trends
When I see new product announcements I then look for relevant signals and visions.
Signals: Can I trace this product back to a past product that didn’t scale? Did the new product fix what was wrong with the previous product? Is there something fundamentally new about this iteration?
Visions: Did this product evolve based on or is similar to something seen in popular culture? Will it be recognized as a similar product by people that know the vision?
If the product holds up in both dimensions, then the product will most likely be a success. As a simple example: The Apple Newton and its influence on following technology products combined with the vision for tablet like slates for business and leisure made it pretty obvious that the iPad / form factor would be a success.
The same can be done for trends. I studied information sciences in the late 90s. Real, conscious artificial intelligence turned out way harder than originally thought and research and industry was just recovering from the second AI winter. During my time at university new approaches were tested, like agent based systems, optimized semantic networks, context based systems and so on. I even wrote my thesis on why context based information systems were not working at the time and what would be needed to allow them to. Looking at these signals around AI that are interesting to look at.
At the same time pop culture has been playing around with the concept of artificial intelligence pretty much since people were telling each other stories. You had historic non-human artificial beings like Golems, Mary Shelley’s 1818 Frankenstein and looking at Wikipedia, the first mention of computer based AI might have been 1872 with Samuel Butler and his novel Erewhon.
These strong visions explain the massive hype around AI whenever some kind of progress has been made to make machines seem a little bit smarter. The popular understanding of what a trend “should be” will drive, but often also obfuscate its progress. Understanding the vision helps me getting clarity when assessing the real trajectory and impact of the trend.
And as mentioned earlier, with trends especially I look for the underlying drivers that cause the change in the first place. Why were the visions created in the first place? How did the visions evolve over time? Who drove the development of the earlier signals? What was the relationship between both?
I apply this to emerging products, services or trends to assess their validity and impact (for example going through Kickstarter or through announcements at big trade shows). I also use it in fictional scenarios to make sure they are believable and consistent (and practice this for example via writing short stories). So far it works for me and my purposes.
Let’s have discussions
I would be curious if you find these definitions relevant and their application helpful. I’d also be curious if you have different interpretations and how you put them to use. Drop me a note here @DirkSonguer or on Twitter. I’d be grateful to hear from you!