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Hey team,
We’ve looked at the resource-based view of an organization, dominant designs and complementary assets. Last time we also thought about how complementary assets can layer on top of each other. I had said we were going to talk about s-curves, but I wanted to cover two quick concepts first. Today, I want to look at the “Fallacy of Obviousness.” We’ll look at s-curves towards the end of this week, sorry for the bait-and-switch.
Gorillas in the missed
There are numerous resources for this concept, this is a good recent one. A wonderful and oft-cited introduction to this concept is an interesting psychological experiment with basketballs and gorillas. In essence, a group of individuals were shown a video and asked to count the number of basketball passes they saw a group of people performing: an engaging task, the viewers had to pay close attention. After watching the video, they were asked for the number of passes, and then they were asked whether they saw the gorilla: a person in a gorilla suit had wandered into the frame and waved at the camera. Most people had completely missed the gorilla. There are a few conclusions we can draw from this interesting vingette. We can think about the nature of concentration, we can consider being misdirected. But also consider, if the individuals had been prompted, even gently about gorillas up front, would they have missed it? Indeed, in any future experiments will the participants be looking out for unexpected appreances? Of course they will. Prior knowledge is fundamental to how we understand our world. It both broadens and constricts our interpretations of an observation.
For the purposes of our story, the conclusion is straight forward: before you know to look for something, it is exceedingly easy to miss seemingly obvious patterns, but once you know to look it’s hard to imagine what it’s like to not know that thing. New knowledge becomes part of our context, and when we consider from that point on, those considerations are made with that new knowledge in mind. It is hard to unknow things.
Within the context of strategic geospatial, we can extrapolate at least two important points:
Geospatial people know what is possible with maps, location, and sensor data but may assume too much of others’ knowledge in this area.
Geospatial people tend to assume that maps, location, and sensor data can answer questions clearly better answered by other means.
Just because we feel something is well understood does not mean others agree, understand, or even know what we are talking about.
Reactions to the fallacy of obviousness
In our community the question of “is spatial special?” becomes particularly interesting because, in essence, this is the fallacy of obviousness. As a community we know something: that location is a good way of organizing our world, and we struggle with determining if this should make a difference. Within the context of the above discussion, spatial is absolutely special. I resevere the right, however, to also suggest that spatial is less special when we consider technical deployments or ramifications. But yes, in terms of organizing information, the concept of spatial is special, because it shapes the lens through which we see our world. We know that geography is a good way of organizing our world view, but our problem is, can we abstract ourselves from that view long enough to make objective assessments of other ways of organizing? Can we challengae ourselves to unknow geospatial?
Nomenclature - simple words for hard concepts
Just because you know something, does not mean others do. But once they do, they they will have a hard time unknowing it too. So, as strategists in a new unsettled market, our job is to tell stories to help non-experts or newcomers understand the possible. However, the trick here is to use words which make sense. One of the best skills we can learn is the ability to explain deep, technical concepts using non-technical language. If you want to cement a concept in the head of a newcomer, don’t use words which are unfamiliar, instead build a bridge of language and try to use familiar words. Dazzling newcomers with technicalities only serves to bore, and create disinterest.
Beyond words, consider what concepts will actually resonate. Arguably, what is exciting, interesting, or fun for a cartographically minded person, might not be the same for the rest of society. There may a reason the individual you are communicating with is not interested in mapping technology…
Echochambers
As alluded to above:
geospatial people are wonderful and building geospatial products for other geospatial people.
We love talking about maps: sharing our experiences with bad data or making witty comments about null island. We love talking with our people. That’s fine, most individuals like sharing common experiences. But, I would argue that those who work in digital geography revel in our niche more that others; perhaps more than is healthy. As an extension to the above statements about nomenclature, generally our industry should step out of the echochamber we have created for ourselves.
Our communications are enormously self-focused. I would argue that most of the dominant technology solutions around geospatial are deeply map-centric, which has limited the discussion to those who care about maps. Increasingly, I now come across examples of geospatial technologies which are not map-centric. These include insurance companies who want to see changes through time, noting that remotely sensed images are nice but arn’t helpful in-and-of-themselves. On the assumption we are quantitatively approaching the problem, monitoring is an activity not conveniently visualized in a map, but more usefully with a histogram. Gifs are fun, but not scalable or quantitative.
Have we, ourselves fallen into our own fallacy of obviousness by assuming the only way we can understand geography is with a map? With the smorgasbord board of complementary assets now available to our community, have we assumed that the best way to visualize change is with the same tools we have always used for GIS and situational awareness? By knowing about and fixating on one method, have we ignored better methods?
Next time, we will talk about demand.