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Alternative Futures Forecast: Methodology Note

How to prepare for the futures that conventional thinking fails to forecast

Methods for forecasting global futures are commonly found within the field of economics, but have been applied to national and international security as well. There are several proven methodologies aimed at predicting different potential outcomes based on current trends and possible changes.

These methods, unfortunately, inherit flaws from both embedded assumptions in their approaches and the substantial gaps in the data upon which they rely. At Girl Security, our unique research method begins with the experiences of participants in our programming to understand the issues and trends that they consider important. Our communities of participants, mentors, staff, and sponsors represent marginalized populations – most often at the intersection of gender and race, ethnicity, economic wellbeing, educational opportunity, and culture, among others. Their priorities and insights are typically overlooked or undervalued by conventional study. This is why our method begins with their input.

Additionally, the method we have chosen for forecasting alternative futures is inspired by disruptive thinkers and innovative researchers, such as:

These authors underscore the simple fact that “the conventional” – whether referring to beliefs, research, thinking, information, or theories, and so on, – by definition excludes experiences, observations, knowledge, and approaches of those other than the subset of people who created it. Given the male-domination for millennia of all domains other than domestic life, today’s “conventions” were inequitably informed. Moreover, more modern sensibilities to the omission of women led to the adoption of a notion of gender neutrality without modern introduction and rather perpetuate the deceptive notion of gender neutrality.

Forecasting alternatives that matter to the future’s majority

To challenge these flaws, Girl Security has chosen a method of forecasting alternative futures based on drivers whose intersections fail to receive mainstream attention. The drivers themselves are derived from trends that Girl Security’s communities identify as being of special concern to them, rather than from trends based on traditional economic and societal indicators. The steps are explained below:

  1. Identify trends of concern to marginalized communities and those historically excluded from informing conventional thinking. The number of trends chosen will determine the number of alternative future scenarios created. The ideal approach is to intersect every possible set of two trends.
  2. Turn a trend into a driver by describing it mathematically in its positive and negative extremes. For example, imagine there is a report that shows Americans are increasingly choosing dogs over other animals as pets. To turn this into a driver, it would be stated in both positive and negative directions: Americans are increasingly choosing dogs as pets over other animals AND Americans are decreasingly choosing dogs as pets over other animals.
  3. Plot your two drivers intersected on an X and Y axis, as in Figure A, which will then create four distinct scenarios.
  4. Figure A demonstrates how two trends turn into two drivers, and when intersected, create four distinct scenarios – or alternative futures.
  5. To complete the alternative future forecast, Girl Security will title each of the four scenarios and provide a brief description of each of the four futures created by the intersection of the drivers.
A graph with four quadrants is pictured. The left side of the x-axis is labeled "X decreasing, reducing, becoming less" and the right side of the x-axis is labeled "X growing, increasing." The upper y-axis is labeled "y growing, increasing" and the lower y-axis is labeled "y decreasing, reducing, becoming less." Each of the four quadrants are predicted results of two combined drivers either trending negatively or positively. The upper right quadrant is labeled "scenario A: positive x and positive y." The lower right quadrant is labeled "scenario B: positive x and negative y." The lower left quadrant is labeled "scenario c: negative x and negative y." The upper left quadrant is labeled "scenario D: negative x and positive y." 

There is a note at the bottom left of the figure that reads as follows: "Positive does not necessarily mean 'good.' It is positive in the mathematical sense of increasing or growing. Likewise, negative does not have to mean 'bad.'"