Secondary Research, Inputs, and Drivers
Futures Research, Week 4
This week was, according to our instructor, “the big week”. It also lined up with some big non-school obligations for me1, so I feel like the past week has been a blur of squeezing my assignments into every available bit of empty space in my life. It was heartening to hear during the lecture that other students were confused about some of the topics from last week, like how to notice and correct for cognitive biases, and how to find weak signals when, by definition, they aren’t very prominent. To be clear, this isn’t schadenfreude; it’s more like a gentle reduction in the intensity of my imposter syndrome.
Secondary Research and Organization
Not surprising, after covering primary research last week, the natural topic for this week was secondary research. The primary vehicle for secondary research is scanning, which I covered two weeks ago and in Intro. One thing I didn’t cover in either of those was the ideal tool to use for storing scanning hits. The most popular tool at the University of Houston, and I think the most popular tool for futurists overall, is Diigo, which has been around since 2005 and has the web design and user experience to prove it. It has a browser extension to add hits directly, and it’s pretty easy to create a group to share hits, but it doesn’t really automate any of the process and it’s sometimes buggy. Raindrop is a more modern site that is pretty similar, but I’m told the tagging capabilities are bad. Newness.ai is custom-built for scanning and has lots of AI-based features that I’m confident will be a standard part of scanning in 5 years, but they’re behind a pretty serious paywall. Some of my classmates swear by Obsidian, mainly because it has tools to help you see the connections between your content using a graph - Tana seems similar. I and some others use and like Notion, because it is free, very flexible, and is generally great as a second brain; capacities.io seems like a slightly more opinionated version of the same thing.
The most interesting output from the scanning process can be organized into TIPPs: Trends, Issues, Plans, and Projections. Trends are some quantitative variable that has been increasing, decreasing, or holding steady over some period from the past to the present; there’s no guarantee that they will continue, but that’s the baseline. There are lots of kinds of issues, but the most useful are those with a clear bifurcation where there’s a controversy/decision/dilemma to be resolved in the future, and the particular resolution will have a big impact2. Plans are announced intentions of actors relevant to the issue - they aren’t certain to happen, but most organizations do make good-faith efforts to carry them out. Lastly, projections are the studies that have been released with forecasts of relevant variables into the future - most studies will have several useful variables at once. Here are my TIPPs for the future of religion in the US.
Drivers
Once research is organized, the various inputs can be assembled into drivers, which I’ve described before as “forces we can feel today that exert influence on the course of the future” of the topic being studied. They give conceptual shape to these inputs as a coherent story of one force pushing, pulling, or weighing down3 future trajectories. These drivers should be given names that are more than a category and less than a sentence - at least enough to make it clear what the influence is, and ideally with catchy names that make the concepts stickier4.
As two examples of what drivers might look like, here is my set for the semester project, and here’s a much more polished general-purpose set of 25 from ARUP, a sustainable development consulting firm. ARUP follows the advice I mentioned during Intro: one common way to package drivers is as a deck of cards, which makes them easier to remember and integrate into group discussions.
Bonus Content 1: Australian Futures
One aspect of the Futures Research class that I haven’t talked about yet: everyone is responsible for digesting and presenting one of the chapters in the Knowledge Base of Futures Studies. These are spread out through the semester, and I’ll mention them here if they connect interesting dots. This past week one of the students presented on Richard Slaughter’s chapter about futures as a quest for meaning. His journey growing up in the second half of the twentieth century gave him a perspective that the future of “progress” isn’t great, and we need to actively imagine alternatives. Futures work can be employed in a number of ways, such as a pragmatic approach seeking to “do today, better”, or a progressive approach looking to adopt and promote new practices, but Slaughter became increasingly convinced that what was needed was a practice focused on sowing the seeds of a new global civilizational pattern; that is, futurists have a deep moral obligation toward the futures they help create. The post-progress, transcendental, all-is-one view that underlies this new civilization is a form of the elevated consciousness I talked about in Intro when encountering Richard Slaughter’s work, and helps me understand why the Australian foresight community, largely emanating from Slaughter and the work he established at Swinburne University, so often takes on this normative, mystical tone.
Bonus Content 2: Selection of Methods
We’ve been spending the semester learning the canonical Framework Foresight method, but in the real-world professionals have a huge variety of methods to choose from at each stage of the process and have to choose based on familiarity or the circumstances of the project. What’s the best way to choose?
Rafael Popper worked with others to build up a big database of foresight projects, and then studied how the characteristics of the project related to which methods were used. Some methods were pretty ubiquitous (literature review, expert panels, and scenarios), and the average project brought together 5 or 6 methods. The domain/sector, geographic scope, and the sponsor/audience (government, business, NGO, etc) of the project don’t have much impact on what methods get used, though government projects tend to use fewer methods overall, and business projects are less likely to do lit review. Projects with a longer time horizon are less likely to use Delphi, SWOT, and bibliometrics (because of their weighting toward H1), and more likely to use scenarios. As the number of people involved grew toward more mass-participation engagements, there were fewer interviews and more group activities like brainstorming.
Daheim and Hirsch wrote an article surfacing some emerging methods that are making an impact on the field. Three worth drawing attention to: increasing automation in tools that do information extraction etc, the rise of crowdsourcing platforms that make it easier to collect information from a very wide group of stakeholders, and the rise of experiential futures methods like games or design exercises5.
Traveling and attending conferences all week for work, church conference on the weekend with lots of meetings. Good, important, and enjoyable things to do, but pretty inconvenient from an academic standpoint.
Issues are usually not the direct result of scan hits, but rather the result of spending enough time studying a subject that they tend to emerge as the shared concerns or uncertainties of stakeholders.
These are the corners of the Futures Triangle, and categorizing drivers by these corners can be a good way to impose a straightforward order if the collection is too unruly.
Point of pride, the professor called out my drivers to the whole class as great examples of pithy, creative names.
The Thing From the Future being a good example of both.