I spend the day at Northwestern, giving a paper to the Marketing department. I was talking about reading trends. I have worked up a new model for doing this, borrowing heavily from Complexity theory and the work of Stuart Kauffman at the Santa Fe Institute.
I blew by one opening slide called “trends trending upward.” The point of this slide is to note in passing, and much too summarily, that the dynamism of consumer taste and preference appears to be growing.
Here’s the slide as I presented it.
1. trend sensitivity is up: Russian glasses
2. more trends at work: end of big slow breakers
3. producing stations more numerous (NY, LA, London, Paris to Atlanta & Iceland)
4. end of mass society: fragmentation of taste
5. trends penetrating new sectors: paint at the hardware store
6. trends peak faster
7. so far the corporation plays catch up
8. what happens when corporations become fully engaged?
Most of these are pretty transparent. The “Russian glasses” notion come from the experience of a friend of mine who examined the possibility of selling prescription glasses in the 2nd and 3rd world, only to discover that Russian visitors are really quite well informed about that fashions in glasses. We used to be able to take advantage of a “back water” effect. That’s gone.
Point two was about the old days when we had plenty of time to spot new trends and to watch them roll through the marketplace. Now it is closer to a perfect storm, with several trends colliding with sometimes unpredictable results.
Point three noted the problem of how many centers can now participate in cultural innovation. At one time it was enough to keep an eye on NY, LA, London and Paris because innovators else would find themselves shut out by the gatekeepers. Now we know that innovators can happen even in Iceland. This means we must monitor more widely and the changes that we will miss something (and suffer the blind side hit) have gone up.
Point four is clear enough, as is point five. A good way to make point five, I find, is to note that trends have penetrating even that bastion of function and pragmatism, the hardware store. Our great grandfathers would be astonished to find that paint colors in hardware stores now change routinely.
Point six says simply that trends move more quickly. And this is just about the only reason I think to feel good about the amount of money we pay our cultural icons. Their moment upon the stage of celebrity can be very brief indeed.
Points seven and eight suggests that as it stands the corporate world is usually playing a game of catch up, often hanging onto trends by their fingernails. This won’t last long. In the next decade we will see corporations solve the trend watch as they have solved every other problem. And once this happens, our dynamism will be redoubled. Once corporations are full participants in the trend game, we will set off in a cultural adventure that will be pretty darn astonishing.
This is another way of saying that as people like me create models to track and predict change, the corporation will get better at creating this change. And then the model building will have to begin again.
McCracken, Grant. In Press: 2006. Flock and Flow: tracking consumer taste and preference in a dynamic marketplace. Bloomington: Indiana University Press.
I’d really like to know how the Kellogg marketing folk reacted to your presentation. It can be hard for academics to refocus their attention from the scholarly literature to the outside world. If they were able to do it, it’s praiseworthy.
Your point about how widespread knowledge about a theory of trends would destroy the patterns the theory tries to explain suggests that such theories may not be constructible. Or perhaps that we may find some local or mesocopic rules, but not a grand, overarching Theory that can predict trends before they happen.
Actually, it might be interesting for you to outline your “fantasy” theory of trends: What data would it take as input, what general kinds of procedures would it apply to those data, and what kind of output would it produce? Outlining the input/output ideal “fantasy” might enable you to rule out a lot of avenues and rule in some others.
Wow, I’d subscribe to Steve’s idea, and pay for it!
Very nice post, Mr Popcorn.
(Wait, that popcorn thing was meant as praise, not insult. Very nice post, Mr. McCracken, I mean.)
As usual, a fascinating post, Grant.
It is not at all obvious to me that widespread awareness by trend-watchers of trends (and even of trends in trend-watching) should make it harder to track trends. After all, the theory of rational expectations in neo-classical economics tackles a very similar problem. This is the theory which attempts to account for the fact that the success or otherwise of a Government’s macro-economic policies can depend upon the expectations of knowledgeable and rational (in the strictly limited sense of economics) participants in the economy about those same policies and their intended effects on the participants.
In other words, the Government might lower our taxes to encourage us to spend more, but if we know that is why the Government is lowering taxes, we may decide not to spend more (or we may over-spend).
I’m working on similar stuff in Computer Science — designing computational systems comprising intelligent software agents aware of the system states (perhaps only imperfectly), using this awareness to predict future states, and also discussing their predictions with one another — intelligent, reflective, anticipatory complex adaptive systems.
The ratex stuff in macro (to the extent one accepts the assumption) works because there is no supernormal profit in equilibrium. In other words, we can all have an accurate model of the economy, base our actions on that model, and collectively make that model true (i.e. find a fixed point in the beliefs/actions correspondence)–but the equilibrium cannot allow anyone to get rich from knowing the true model. So a trend forecasting system that everyone knows about that makes trends come true will not be one that earns a profit.
Personally, I’m skeptical of the assumptions in most ratex models that a homogeneous representative agent is a good way to think about expectations. It seems to me that heterogeneous beliefs are pretty important in understanding the economy.
Steve, agreed. One of the hardest things for Computer Scientists to accept — used as we are to designing and buildng systems ourselves — is that agents in multi-agents systems will be diverse, and that the diffusion of beliefs and expectations in such systems generates much of the dynamism which these systems exhibit.