solution-axis

Looking At Solutions Spatially

I like to think of a solution to problem as occupying a three-way axis.

Magenta: The Economist

An economist’s view on solution is reflected by the magenta line: how many people can a solution solve the problem for, and for what cost? The result is thus gauged with a classic “cost per capita” equation, where you would divide the last value against the first and measure a solution’s relative effectiveness by the number of people it can reach versus the amount of money it spent on research and production.

The paperclip, a relatively low-cost/low-tech solution that can solve many people’s organization problem, would rank high on the economist’s measure. Conversely, the one-of-a-kind Maserati, a relatively high-cost/high-tech solution that solves the age-old problem of driving in much of the same way that we have solved it before, would rank low.

This does not mean that the solution on the right are more “correct” than the one on the left. Rather, it is more specialized and tailored to a niche (and thus may actually solves the problem more effectively, even though it costs more money) than the more be-all, end-all solution that happens on the left side.

Cyan: The Designer

The cyan line represents a designer’s view on solution: how elegant is it? If I’m writing a code, how “beautiful” is it? How “readable”? How many lines do I need? How many variables and strings? This is gauged against how many hacks I need to use and undocumented behavior I need to call.

jQuery, a JavaScript library that would allow someone who writes HTML to specify events, behaviors and AJAX-style interactions with relatively little code, would be ranked high on elegance. The Ruby language, thanks to its “cleanliness” and “readability,” is also one. On the contrary, using a software that was made for a blogging engine to serve a Content Management System role (ahem, like WordPress) would score low.

On a more tangible note, the cyan line also concerns time. How long does it take me to use a particular tool to solve a problem? Going up on the measure does not necessarily mean a good thing. Sure, most elegant solution takes less time to assemble, but hacks are done for the same reason, too: because it is faster to do something unfamiliar in a familiar context, rather than doing something familiar in an unfamiliar context.

Q: Should I Always Aim For The Top–Rightmost Solutions?

A: Generally, yes, but consider that fact that being closer to the center does not mean that your solution is necessarily less effective. Much like traveling, the further you drive, the more likely you’ll get to a destination more interesting than where you started, but the more resource it will take to get there.

Abstraction: The First Middle Ground

Between the red and cyan line lies the uneasy middle ground we call “abstraction” (not drawn in the diagram.) Abstraction is a system that distances ideas from object. It’s famously exhibited in the Recycle Bin/Trash Can feature of a computer, where the actual object of the feature is to “overwrite bits of 1’s with 0’s from a hard drive’s map,” but the idea that we thought about is “erasing files” like we would compare it to “putting garbage in the trash can.” Hence, the metaphor.

As mentioned before, abstraction has a link with both with both the economist (magenta) and designer’s (cyan) measures. This is because almost always require less mental and physical energy to utilize (arrows tend to move up on cyan), but carries the risk of little impact to the people (if one fails to learn to associate the metaphor with an object. Arrows tend to move left on magenta.)

Yellow: The Ecologist

Several weeks ago, I talked to Anselm during one of our Sunday Makerlab session, wherein a colleague was posing a gap she saw in the distribution of unwanted foods that are still in great shapes (ie. unsold baked goods from the morning) to people who need it the most.

The group brainstormed a solution. What I saw was a discussion between choosing an interface device that is going to:

  • Be most accessible (the magenta measure) to as many restaurant, café and bakery owners as possible
  • Simultaneously aggregate as many resources available as possible (“I have fifty loaves of wheat bread”), pickup availability (“I happen to live one mile from the bakery”) and community’s needs (“the shelter at Alberta St. is occupied with more people than they usually handle”)—all while keeping it as simple as possible (the cyan measure.)

Until the discussion veered towards Twitter (as it tends to happen) and Anselm mentioned the fact that, no, Twitter is neither a revolution (tumblelog and the concept of Microblogging was described by why the lucky stiff on April, 2005) nor it is one that a large percentage of society—young and old, privileged and poor—equally adopted.

But it is one that changes the way people interact online, forever.

This, Anselm then remarked, is the idea of Plasticity. Plasticity means that any environment occupies a space (virtual or physical) and therefore can be changed, shifted and molded.

The tricky thing about plasticity, of course, is that one really does not know that one is going to shift a particular space until, through intricate play between many factors, the space shifted itself. Note how determining how many people could a solution reach (magenta) is fairly easy to measure, and determining how elegant a solution is (cyan) is easier still. The Plasticity (yellow) measure, then, operates much like how an Ecologist would: always concerned about webs of relationships.

Rethinking How We Approach A Solution

I remarked this then, and still fully believe it until now:

What if we consider our solution not just in terms of elegance or affect to people, but rather to the potentiality that it has to change the environment around people?

And ultimately what if we base all of our decision on that? On executing solutions that move away from indulging ourselves (cyan) or our target audience (magenta,) but rather, the space between us?

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  1. [...] Looking At Solutions Spatially, I proposed the three dimensions that we can measure a solution by. The ultimate decision is always [...]

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