Future(s) as a networked pattern
In our live session this week (recording here), we discussed, briefly, the futures methodology that underlies the work we'll do in this course. The OECD document (pg 3-12) on futures thinking provides a good introduction to trends, scenarios, and methodologies. The model that Dave and I will present as we move through this course is somewhat based on the OECD document, but we take several key departures in our process of trend collection and analysis, our model of scenario generation, and the methodologies we employ in validating both trends/scenarios. We think (well, I do at least!) that our approach provides a model for making sense of numerous contradictory trend patterns and generates a sufficiently broad sequence of potential impacts to enable leaders/decision makers to effectively plan policies and set strategies.
Needless to say, futures thinking is a field of study that we won't be able to fully address in the eight weeks of this course. We will, however, engage with the 600+ participants in this course with our approach and encourage individuals to modify and adjust to reflect their context.
A futures methodology is largely field/discipline neutral. The process of making sense of trends (and from there, explore potential scenarios) in mobile devices is essentially the same as making sense of trends in medicine. Or technology. Or economics.
But what exactly is this process of sensmaking?
In our session this week, we discussed that trends do not live alone. Trends are networked. Which means that it is not enough to say that "x% of students have mobile phones". That means very little. But, when we take the trend of mobile phone adoption over a period of time, add increase in mobile applications, reduced costs of access, increased bandwidth allocation trends, growth of 3G networks, etc., we start to get a pattern. And this is key. Future(s) thinking requires bringing trends in relation to one another and exploring weight, impact, and influence
Look at the trends discussed in this forum. What a great list! Having identified these trends - ideally supported by stats, reports, and research - we can begin to plot a "change network" (or trend map). Mindmapping software will work (but we need the ability to comment on the nature of connections and their weight - we'll get into this in the next few weeks), as will concept mapping software like CMAP (a free download). In the process, we must be explicit about the type and quality of evidence for the trends we've listed. "My daughter/son plays a lot of xbox/PS3" does not count as evidence. Data from OECD, World Bank, UN, US Department of _____, and other recognized organizations do count as evidence. Peer reviewed research, reports from industry associations (with the necessary discounting of bias), trends through data visualization (Many Eyes), and so on. Qualitative data collection - panels of experts, "tension pairs", narratives - offer additional important sources of information.
The quality of data-driven trend analysis serves as the foundation for the entire futures process. Once data has been collected, the task of crafting a trend map begins...but we'll save the particulars for later in the course.
2 comments so far:
Najmeh says: Two Worlds
George, I'm kind of confused about the part where you say our resources/evidence are "Data from OECD, World Bank, UN, US Department of _____" I understand that to run a course like this for instance, valid statistics would be the best way to go as looking beyond them would drastically complicate our calculations. My question is regarding whether this approach is the best way to go in general (outside the course) when studying trends.
As a person involved in both educational technologies and comparative, international development education I can tell you that there's a slew of problems by relying on data alone with observing any phenomenon. Textures and contexts of relationships and metaphors get lost in the data, and to have a more comprehensive view of anything we always need a mixed studies method: analyzing both quantitative & qualitative results, looking at data AND at relationships, statistics & metaphors (whatever we choose to call it) is always really important. So is that something that is done with studying trends or do we mostly rely on data alone?
gsiemens says: 2 worlds?
Hi Najmeh,
I'm not exclusively focused on data - but too often, trends are extrapolated based on observation alone to provide an argument for a certain type of future.
For example, I've frequently heard the buzzword statements that "students have to power down when they go to class". The statement is used to support the notion that schools are outdated and out of touch. Outside of schools, students run merrily through digital fields skipping on new technology daisies.
But many things are wrong with this statement (even if we accept that students power down). Is "powering down" only technological? Perhaps students are mentally powering up. Is powering down a negative? Statements like this are very difficult to discuss because its a mushy statement - put pressure on one side (i.e. lack of data to support the assertion) and the statements squirts out the other side as "we still have blackboards in my school". Too many unsubstantiated claims and lack of opportunity for interrogating the statement make it meaningless for futures study. Now, there are ways to make this statement more palatable, and futurists use various methods to do so: environmental scans, expert reflections, tension pairs, trend analysis, etc.
The quality of futures thinking begins with the quality of data. The data available from organizations that have a long-term data collection experience (which provides history and reveals trends) is particularly valuable, which is why I highlighted it in particular. Too much soft and mushy analysis accompanies many futures thinking approaches in education.
You are absolutely right to note that data alone does not provide the complete picture - narratives, observations, detailed descriptions, etc. - are valuable too. (Latour suggests that writing "excellent description" is the key need in sociology).
Once we have collected our data, we need to place it in relation to other data. As stated in the original post - a single trend means nothing. We must compare, contrast, and relate trends to gain a better understanding of "the whole". So, even if we begin with good data (OECD, World Bank), we still need to contrast that with opinions of experts, our observations, participant comments, and so on.