This article was originally published on CFO.com

Forecasting the future is a tough act, but there are strategies and signals available that create a useful framework.

Around this time of year, I’m often asked what the next year will bring by way of new things, emerging trends, and surprises. Forecasting the future is a tough act — the obvious sometimes never shows up and a surprise wouldn’t be a surprise if you knew it was coming. So this year I’m going to lay out the approach I have used for more than two decades to get a handle on what’s likely to be ahead. The approach is called “weak signals.” It’s generally worked well for me and the clients I advise.

The theory is that most of what we need to know about the future is around somewhere in the present, but not always easy to see or understand. The signs may not look like signs; may not be easy to interpret (or may be easy to misinterpret or disregard); may be in places we don’t usually (or ever) look; may not seem important; or may be in direct conflict with other, stronger, seemingly more relevant signals we’re already paying attention to.

What we want to do is create a framework where we can watch for and track these weak signals and create a series of “hypotheses” about how the future will be influenced if a weak signal becomes significant. That way we can have a manageable set of things to watch for (“watchpoints”) that can help direct our attention to things we might otherwise miss.

So, what does this framework look like? Mine has six elements:

  • Devices (and the software that enables them) and their capabilities, plus what these capabilities make possible. I look for novel devices or novel uses of existing devices because the device is usually easier to see than the software.
  • Locus: I look for new places where we can do new or existing things or where we can make new connections between things, activities, and places.
  • Algorithms: I look for algorithms that allow us to do new kinds of things, solve new or existing problems, find new patterns, or make new connections
  • Process: What ways will the first three elements, individually or in combination, change what we can do?
  • Society: How might the first four elements might change how we work and live our lives?
  • Expectations: What issues and ideas illuminate, illustrate, motivate, or constrain our aspirations as individuals, groups and societies? How might these expectations be met by the first five elements I am watching?

All these elements interact with each other to provide the “weak signals,” the emergent issues and trends to track. The stronger the interactions, the clearer the signals tend to be, but we’re still generally looking for a few useful pointers amid a lot of noise.

Even when you get the signals right, the timing is very tough to predict. As the late (and already sadly missed) Seymour Papert (Professor emeritus at MIT) once insightfully observed “We generally overestimate what we can get done in two years and underestimate what we can do in ten.” However, timing is important, so, in response, I divide the future up into a series of “horizons,” which I call H1 to H(n). I’ve experimented with several different values for “n” and tend to end up with n=5, each resulting “H” defined as follows:

  • H1: The next 12 months. We should be able to forecast this horizon accurately. It will be based on elements that are already here, somewhere, morphing from weak to stronger signals.
  • H2: 12 to 36 months. This horizon is harder. We’ll see some H1 elements that were slower to develop, mixed in with newly present signals and evolving trends.
  • H3: 36 to 60 months. Harder still, because the H1 changes will start to spawn their own set of evolutions, generating new weak signals that could not have existed earlier.
  • H4: more than five years. At this point we are guessing, but the whole point of the process is collecting relevant data on what to watch for, so it’s not much of a surprise when the unexpected happens.
  • H5: more than ten years. Anything this far out is essentially science fiction. We can imagine it, but we need significant breakthroughs in theory and major innovations in practice to make what we imagine real.

These horizons are guidelines only. I allocate the weak signals I track to a horizon (I generally use some combination of Delphi methods, crowd-sourcing, and scenario modeling) and allocate resources based on how soon I think the signal will tell me something. Some things will take root early, but be slow to develop. Others will stay somewhat hidden and then grow explosively when they finally appear. Much of what we watch for will never happen. The whole approach is less about being precisely right and more about being generally prepared — and I guarantee things will still be missed, in part because there is simply too much to watch.

But better to be as prepared as possible!

Now that you know how I go about it, I’ll be offering some thoughts about 2017 in the next few weeks.

About the Author
John Parkinson

John Parkinson is an Affiliate Partner at Waterstone. John brings extensive experience to the topics of technology strategy, architecture and execution having served in both senior operating and advisory roles.