Predicting the future is all about time
Predicting what is going to happen is easy. The hard part is predicting when it is going to happen.
There is a set of forces that are not immutable, but that are at the very least, slow to change. These forces drive us in particular directions. Some of these forces spring from human nature. Some from the fundamentals of our current economic system. If you understand properly where we are today, and how these forces drive us, then like a sailor plotting a course driven by the prevailing winds, you can make a pretty good shout about where we might end up.
This rather Newtonian approach to prediction doesn’t work for everything. It’s much better at the macro than the micro. But it is this approach that tells me that at some point, machines will replace humans in a lot of jobs. It underpins my long term optimism but also drives my short term pessimism. But it does very little to tell me when things will happen. Because time is beyond the control of these primary forces.
If you look back at the predictions of the past – ones at which we frequently laugh – I often find that what they got wrong was not the destination but the journey time. The paperless office? It’s coming, but slowly. Office paper sales are dropping about 2% a year, or they were the last time I spoke to someone in the industry about it. We probably won’t be totally paperless (or near enough so as not to count) for at least a decade or two yet.
What about flying cars? We’ll get there in one form or another over the next few years, though they won’t be mass market items for a good few years after that – if ever. They will exist, just not on the timescale any previous forecaster expected.
Could we have had flying cars before now? Or the paperless office? Both were plausible, if we had improved certain technologies more and adopted them faster. But the speed at which we make the relevant research leaps, development investments, policy shifts, and cultural adaptations to certain changes is deeply unpredictable. Because they exist in the realm of human collective behaviour with a multitude of conflicting forces. To come back to my ship analogy, we can see the start and end points and plot a rough path, but there is a storm along this path. How long it takes the ship to navigate that storm is deeply unpredictable.
When we cast out into the relatively far future, say 30 years and beyond, we can make some assumptions that whatever the scale of the storm, some ships will have navigated their way by this point. We’ll often be wrong though, which is why when looking to the far future we often imagine multiple scenarios.
Looking to the near future, we can see our ships emerging from the storm. We can see where they have already made port, to stretch my analogy even further. The industries and sectors and aspects of life that have already been touched by these new trends or technologies. Our challenge is to understand when they will reach our particular sector, the one for which we are trying to make predictions. This is why we look for pressure points, the issues that determine how great the impact of the incoming change might be on our target sector or organisation. The more disruptive a change is likely to be, the more attention we must pay it.