This time, we’re moving into the third territory: the ecologist’s. We’re going to look at solutions that change the shape of the space they’re in. True to its name, I’m going to use the natural web of life, adaptation and evolution as analogies.

The ecologist, I think, will propose two things that problem solver could do:

Up until the end of the Cretaceous Period 65 million years ago, dinosaurs, large-sized, cold-blooded reptiles (or so they speak of them) became the dominant Phylum in the ecosystem. But notice how the game changed gradually afterwards. Small-sized, warm-blooded mammals, originally of relatively weak physique and small population, survived, thrived and changed the game until today
What does the mammalians do to change the space they’re in?

This is the first way: they did nothing. They let nature takes its course, kept themselves small, then wait for the impending disaster to arrive, survive thanks to their relative size and thrive that way.

Applied to problem solving, idea that at first doesn’t seem like much (whether by elegance or economy), but is able to withstand time by laying low until all the other idea (company, product, etc.) withers away, wins.

In a decidedly ethnocentric move, I’ll take our own race as a second example:

For at least most of the world’s history, no other species had changed the environment around it as much as we, humans, do (mostly negatively, but that’s beside the point.) I’m going to go into a classic argument here and say that we are weaker and less agile than many other creatures out there (cheetahs, shark and dinosaurs come to mind) yet we are able to change the space around us like no other species could.

What, then, made us different?

This is the second way: we became flexible. What we lacked in strength, dexterity or agility, we make up in our ability to adapt to any situation. In fact, you may even say that, thanks to our physical inability, we then are forced to rely on our flexibility to adapt. A shark, for instance, is perfectly suited for the underwater environment. A hawk for the sky. A tiger for land, and so on. It turned out that survival isn’t just about being the best at dominating any one environment. It’s being good at one and adaptable at many.

In the same sense, a solution that has more potentiality to change the plasticity of the the shape around it tends to not be:

• The most specialized (shark == water, hawk == air)
• Full-featured (shark and hawk == fully equipped for hunting)
• Or novel (a shark can sense a drop of blood amongst a million parts of water, a hawk can see from afar)

Rather, it tends to be the most barebone but flexible. This kind of solution may not have enough elegance or economy to do much, but it’s also one which principle can be applied to many other areas.

An example: MySpace. Does it do every one of its function well? No. Is it exclusively targeted to a niche at its inception (for example, towards artists or musicians?) No. Is it fast, full featured or standard-compliant? No.

But does it provide an interface that’s malleable to the user’s heart’s content? Yes. In fact, customizing is one of its key strength that allowed it to became one of the key players. Does it have enough flexibility to adopt most of the user’s area of life? Absolutely.

Another example: Twitter. Can it play music, display elaborate profile, or even be customizable to a good extent? No. Can it display more than 140 characters at a time? Mostly, no. But does its service have enough flexibility that the user can utilize in almost every area of her life? Absolutely.

Take WordPress. Is it a proper content management system? No. Does it have all the power needed to do stuff specialized for blogging? No. But does it have enough flexibility to allow any user of fairly low web development level to write her own plugin and customize the look and feel and behavior to her heart’s content? Yes.

The empty frame, the blank box and the universal interface is all you need. The rest could be good enough. MySpace, Twitter and WordPress aren’t products with killer features, they’re good enough products with flexibility and accessibility.

In the word of my friend and fellow tweeple, Rodney Rumford (@Rumford):

Twitter vs. FB they are very dissimilar ecosytems. twitter is really quite astonishing in many ways. it is whatever you want it to B

Source.

I happen to believe that there are certain mistake that will allow you to not only make mistake, but get you further from where you started and give you new perspectives on things that will allow you to better solve the initial problem you encounter.

These are great mistakes.

First issue: how can you spot a mistake if you don’t know that it’s the one you’re currently in?

Easy. A mistake will not happen without a prior action on your part. This means that if you can spot the type of action and its failure potentiality, you can probably predict how likely it is to be a mistake.

For example, if I’m building a house, doing things that are related to cooking (ie. bake a lasagna, brine a turkey) or programming (ie. GitHubbing, Ruby coding) are more likely to cause failure and result in a mistake than doing things related to architecture (ie. drawing a blueprint, divvying up rooms) or engineering (ie. putting up bricks, measuring woods.)

To put it simply, the rule to spotting a mistake is to ask yourself how far-fetched does the action that I am currently taking stray from the problem I am trying to solve? The further it is, the more likely you’ll make a mistake.

Second issue: could I identify and make great mistakes more often?

I think so; and I think that getting there involves asking yourself if I were…

For example: suppose that I asked you to cook dinner. There are three possible actions you cold take:

1. Do it right: follow a recipe book, consult a friend, get a caterer to deliver.
2. Make a good mistake: combine cooking methods, fuse Peruvian and Swahili cuisine, try exotic ingredients.
3. Make a great mistake by asking yourself: if I were the first human being who discovered fire, if I live in zero gravity, if I had a vacuum chamber, what would I cook for dinner?

Another example. Let’s say that I want to built a house. Again, I could do three things:

1. Do it right: commission an architect.
2. Make a good mistake: seek as much inspiration from outside your field of study, then blueprint it yourself.
3. Make a great mistake by asking yourself: if I were a horse, or a human who could live for 200 years, what kind of house would I make?

Note how, while both types of mistake—good and great—may lead to failure that you can learn from, asking if I were… allow you to see it from different points of view and recontextualize its content.

After you solved this question, you should then return to your original problem and incorporate the things you learn while you were reframing it. Doing this will help you think of singular solutions.

A good parallel to making a great mistake can be found in the Kōan, “a story, dialogue, question, or statement [...] generally containing aspects that are inaccessible to rational understanding, yet may be accessible to intuition.” A Kōan is designed to “confound the habit of discursive thought or shock the mind into awareness” rather than be answered.

In the same manner, a great mistake is designed to reimagine a problem rather than necessarily solve them. From reimagining, then naturally comes the solving.

And if I were you, I would start making great mistakes that produces more elegant, economic and game-changing solutions.

On Looking At Solutions Spatially, I proposed the three dimensions that we can measure a solution by. The ultimate decision is always up to you, but the metric is there to help you qualify it.

To sum up, there are three points of view. These are represented by three colors and analogized by three occupations, respectively:

• Magenta – The Economist: Looks at the financial and quantitative impact of the solution by asking “how many people can we reach with this solution, and at what cost?”
• Cyan – The Designer: Looks at the elegance of the solution itself by asking “how much time will it take for me to develop, and can my user save by this solution?”
• Yellow – The Ecologist: Looks at the potentiality of the solution to change the shape of the space around it by asking “how ‘plastic’ is my environment, and how far could I shift it by using the solution?”

Today, we’re going to look at the first two axis: the Designer (cyan) and Economist (magenta) – the challenge that faces them and the connections they share.

The Designer

This is how the Designer look at solutions:

• Elegant solution takes less time to use, yet more time to develop
• Hacked-together solution takes more time to use, yet less time to develop

Here’s the problem: these statements somewhat wrongly imply that the more time the designer spends on a solution, the more elegant it will become. Many designers I’ve met, through anecdotal evidences, say that they could only work on a solution for a set period of time before the quality of work and elegance of solution declines.

This notion is strongly supported by a technique that many uses, defined by James Webb Young in A Technique for Producing Ideas and reinterpreted as thus:

1. Define the problem
2. Research it extensively
3. Try out some solutions
4. Forget about it (while “constantly thinking about it” or “letting the ideas marinate”)
5. Eureka!

Webb then stated that, after trying some solutions out, one must stop the working of her conscious mind to let the unconscious “background process” do the work.

This means that there indeed is a certain time limit, a point in the equation when spending more time does not necessarily equal to creating more elegant solutions.

The Economist

The Economist also posits two things in connection to the Designer’s point of view:

• Elegant solution that is friendly to the user’s mental model may impact more people, but cost more money to research
• Hacked-together solution that is less-friendly to the user may impacts less people, but cost less money to research

But, much like time, there is a limit to how much money and resource (number of people) you can throw at a problem.

This quote from Stacey Higginbotham of GigaOM summed it up:

As anyone who’s ever hosted a demolition party well knows, you can only throw so many workers at a problem before people start to linger at the edges, swill your alcohol and generally stop helping.

Implication

It turns out, then, that putting more money and resource into a project can only work so far. There is a certain point in the equation when spending more does not necessarily equal to creating more elegant solutions.

This, then, begs the questions:

• Where in the process is this point located?
• Is it possible to predict it or achieve a workable approximation?
• If so, is it possible to stop the process right at this moment so we can avoid wasting unnecessary time and energy?

Caveats

• Money and time tend to encourage most, but not all developments to be more far-reaching and elegant. A great solution does not have to cost a lot of be done over a long period
• These two factors, in most cases, are thought of as two very strong factors that impacts problem-solving. But there are other factors that should also be taken into consideration, like experience, risk-taking tendency, political power and cultural considerations

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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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