Forming the Baseline Future
Futures Research, Week 5
Refining Drivers
Once the research is done and the drivers have been assembled, it’s time to start building futures! Chapter 3 of Thinking About the Future is a 92-page monster about how to do this1. In class we largely assembled the drivers intuitively from the TIPPs inputs, but a more formal approach might be to cross inputs from different STEEP categories and imagine how they might intersect.
Another approach is to excavate the inputs by using Causal Layered Analysis, which I discussed in Intro in the context of building a vision, but which can be used here in the same way: take what people are saying on the surface of an issue, and dig down to understand the underlying systems, the worldview driving those systems, and the myths that lead to that worldview. Deeper layers are more consequential but change much more slowly (centuries), and so this approach can help distinguish what can change within the horizon of the project and how impactful it might be.
Once you have a decent, smallish set of drivers identified, one way to start to imagine them interacting is by using a cross-impact matrix, which is a simple technique going back to the 1960s where the impact of each (row) driver on each other (column) driver is estimated; this could be via conditional probability in support of simulation modeling, or just some qualitative judgement on how much one reinforces or contradicts another. The rows then give information on which drivers are the most consequential (usually as accelerants to the others, but sometimes as brakes), and looking down the columns can tell you which drivers are the most dependent on the outcome of others.
Forecasting
Once the drivers are ready, they can be used to start generating potential futures. This is often called forecasting, but because that term sometimes carries an inappropriate connotation of certainty, futuring is sometimes used instead to suggest something different than predicting the weather2. There are lots of methods to choose from, and TATF has two main pieces of advice for selection. The first is to pick one or more formal methods based on the expectations of the client and the needs of the engagement; this formality creates transparency, as the output will have a logical relationship to what came before, and not seem like just the invention of the futurist. The second is to mix and match methods that complement each other, such as a qualitative and a quantitative method, or something collaborative and something more expert-based.
Once the method is selected, the goal becomes the creation of multiple futures that are plausible but as different from one another as possible (to stretch the client’s imagination). A few methods to do this: have the client group brainstorm about possible future outcomes to get all their existing ideas out, then throw all those ideas away and force the creation of new thoughts; find the most hard-set assumptions or uncertainties in the organization and reverse them; surface the surprises that could mean that all the data were right, but the forecasts/conclusions were wrong; or search out what ideas and topics make the organization a little uncomfortable. Most of all, resist the urge to start converging your ideas too early; TATF explicitly makes the recommendation of using sleep as a strategy when you get stuck.
Houston Forecasting
Within the Houston Method, the primary method of generating futures is through scenarios, via a collection of archetypal scenarios that are borrowed and modified from the four generic futures developed by Jim Dator for the Manoa School.
The first scenario is the Baseline, where the drivers keep moving in the direction they are currently going (the rules stay the same); this is often but not always the “official future”3.
The second is the Collapse archetype, where the baseline falls into deep dysfunction (there are no rules).
The third is New Equilibrium, where the underlying system stays the same but there’s a meaningful shift that creates a new balance (the rules are changing).
The fourth is the Transformation archetype, where the entire underlying system is changed (there is a new set of rules).
The program has started aligning these archetypes with the Three Horizons framework. Baseline corresponds to Horizon 1, since it’s emerging from trends that are already fully underway. Transformation belongs to Horizon 3; by definition, the change is so dramatic that we can only see small pockets of it today. Horizon 2 is the stage for the conflict between the old and new realities, and that conflict can play out in either incremental shifts (New Equilibrium) or in the current system breaking (Collapse). Whether it makes sense to draw a trajectory between these futures as plausible paths is a matter of ongoing debate.
So far this week, we covered the creation of the parameters for the Baseline scenario, which is pretty straightforward: just extrapolate out all the current drivers individually, work out how they would interact (the cross-impact matrix is great for this), and give the whole thing a memorable/clever name4.
Systems, Stories, Scenarios
A totally different approach to generating scenarios is given by Schultz, Crew, and Lum in their paper “Scenarios: A Hero’s Journey across Turbulent Systems”. The basic idea is to make scenarios compelling by incorporating classic insights from storytelling. Broadly, this can be mapped to the Three Horizons: the hero’s journey is what takes place in Horizon 2, as the hero struggles to get from the status quo of Horizon 1 to the transformation implicit in Horizon 3. The approach to build these futures is to start by taking the changes in question and mapping the implications out using a futures wheel enhanced by the categories in the Verge framework, then array these in chronological order along the three horizons. Interactions between elements can be added as arrows, and different causal loops can be isolated as the driving logic behind different scenarios. These scenarios can be populated using the structure of the hero’s journey and with characters that take the role of Jungian archetypes. The paper suggests three possible products for this work: long-form high level stories with a pop-history tone; shorter on-the-ground stories that are more vivid, and short videos that pair the scenario details with visuals.
Bonus Content 1: Ryan Burge Interview
This week as part of my primary research for my project, I had the opportunity to speak with Dr Ryan Burge, a pastor, researcher, author (both books and the excellent Graphs About Religion newsletter), and frequent source of media quotes on stories about religion (here’s a recent example). Much of what he shared with me aligned with what I’ve been gathering through my secondary research, but there were lots of fresh insights too: the critical but under-reported role of mainline Protestants and center/left Catholics in America’s religious makeup; how the Evangelical movement seems like a permanent fixture of American society, but 100 years ago the Social Gospel was the biggest Christian movement; and how we could be heading for a significant re-evaluation of the importance of religion (ancient or not) in building a functioning society. It was a great conversation and I’m deeply grateful that he was so generous with his time.
Bonus Content 2: More Australian Futures
There was another great student presentation about the development of futures in Australia, following up on last week’s discussion of the personal journey of Richard Slaughter. This week was the discussion of the rise and fall of the futures program at Swinburne University of Technology. It had a difficult history from 2001 to 2016, under the leadership of Slaughter, then Peter Hayward5 and Joseph Voros, and finally Rowena Morrow, as Australian higher education, in general, experienced a shift toward “business-ification” and a need for quantifiable value. At present the extent of futures education in Australia is a collection of issues-specific single courses (design futures, business futures, etc) scattered throughout their universities, which is a sad fall from the lofty heights of the last two decades.
Part of the length is because it starts with several methods for identifying drivers and areas of uncertainty, which was the main subject of last week.
In case you haven’t been tracking this, weather forecasting really is getting better.
For example, with climate change, the baseline is pretty grim, but the official future is that any day now we’ll transform the economy to meet emissions targets.
I may have made mine too clever by half: since I’m doing my project on the future of religion in the US, I decided to get all my scenario names from WB Yeats’s poem “The Second Coming”, which I’ve heard described as the second-most-quoted piece of English literature. So far, in my limited sample, it doesn’t ring a bell for people.