In Futures Thinking: The Basics, I offered up an overview of how to engage in a foresight exercise. In Futures Thinking: Asking the Question, I explored in more detail the process of setting up a futures exercise, and how to figure out what you’re trying to figure out. In Futures Thinking: Scanning the World, I took a look at gathering useful data. This time, we dive into the heart of the process: creating alternative scenarios.
Note the plural. Foresight exercises that result in a single future story are rarely as useful as they appear, because we can’t predict the future. The goal of futures thinking isn’t to make predictions; the goal is to look for surprising implications. By crafting multiple futures (each focused on your core dilemma), you can look at your issues from differing perspectives, and try to dig out what happens when critical drivers collide in various ways.
Whatever you come up with, you’ll be wrong. The future that does eventually emerge will almost certainly not look like the scenarios you construct. However, it’s possible to be wrong in useful ways–good scenarios will trigger minor epiphanies (what more traditional consultants usually call “aha!” moments), giving you clues about what to keep an eye out for that you otherwise would have missed.
As a clarifying example, I once worked with a business services company to craft different scenarios of its future competitive environment. All of the scenarios included some level of economic upheaval and technological disruption, with one suggesting that a technology company offering business services could be a real threat–a story arising from tentative signs that some of their clients were starting to use more open source software. A few of the strategists realized that a company they had thought of as a minor nuisance at worst could actually be their most serious rival, and pushed their CEO to pay more attention to that threat.
(He didn’t, and the business services company eventually went under, with the tech company gaining many of its former clients–and employees.)
So how do you actually do this?
In the aftermath of your “scanning the world” work, you will have come up with at least dozens and probably hundreds of interesting and potentially relevant data points and potential drivers. It’s hard to work with hundreds, though; more useful would be about five or six. Time to call in some friends.
You’re going to want to spend an afternoon with a group of no more than a dozen colleagues talking about the “distant early warnings” you’ve dug up. You’ll probably find it easiest to put each one on a separate index card or sticky note (in this, low-tech still beats high-tech). What you’ll then do is look for patterns and bigger picture categories that would encompass multiple topics. Try to focus the categories on subjects that are clearly important and hold a great deal of uncertainty.
Pile up the clusters of related subjects; you might find that a single topic might belong in multiple clusters, but resist the urge to duplicate it–you want to put it with the group where it seems most important. Feel free to brainstorm along the way–you might find that your colleagues are inspired by the scanning results, and offer more than a few additional suggestions. This is fine.
You will eventually have a smallish group of categories with lots of members, and a largish group of categories with just a few. The big categories will be your key scenario drivers, and should appear in all of your scenarios in some form. The smaller piles will be minor drivers, and should be included in at least one.
For example, a scenario project about whether and how to expand a business might end up with major drivers such as “the economy,” “China,” “aging baby boom market,” “oil prices,” and “computer tech.” All of your scenarios will at least touch on each of these subjects. Minor drivers might include “labor relations,” “advertising markets,” “new manufacturing technologies,” and so forth. These don’t necessarily need to appear in every scenario, but should appear in at least one. Yes, these are all very high-level categories, but remember that they’re clusters of individual data points and issues; these individual bits are what you’ll eventually weave into the scenarios you construct.
So you now have your key drivers, and have been thinking about the ways in which they’re both important and uncertain. It’s time to start building your scenario worlds.