Design Thinking: How to critically assess a solution in relation to the problem

There exists a problem. We need a specific geometric shape to fulfill a given set of requirements. Let’s apply some design thinking principles to find a suitable solution.


  • must have 4 flat sides
  • must have 4 sides of equal length
  • must have 4 corners
  • must have 4 right angles

Solution Candidate 1: Square

A standard Square A standard blue square


  • has 4 flat sides
  • sides are equal length
  • all 4 corners have right angles
  • area happens to be simple to calculate

The square meets all of the given requirements and is a suitable solution to the problem. We normally do not find the perfect solution straight away. This post isn’t so much about the process itself as it is about the pitfalls.

Solution Candidate 2: Rectangle

A standard rectangle A standard blue rectangle


  • has 4 corners
  • has 4 right angles
  • orientation is easier to identify


  • Does not have 4 sides of equal length, does not fulfil a requirement.

Yes, but its orientation is easier to identify!

The rectangle excels at something that was not a requirement for the square. The reason it excels at this new requirement is not because it is inherently better than the square. It excels because it was not constrained by one of the original requirements (which was imposed on the square). With regard to the original problem, the square still fulfills the requirements better even though the rectangle brings additional advantages.

If we care about the rectangle’s benefits then we are changing the requirements and nature of the problem. (This is ok, some might call it agile.) In doing so, the rectangle becomes superior to the square and should be adopted as a solution. This is important. It is not about the square or the rectangle, its about which one works best in the target environment.

But Sometimes

But sometimes, the square is black!

(When its dark and the lights are out.) As soon as an argument starts with “But sometimes” you know that it probabaly does not carry much weight and is ultimately dismissed after a heated and stressful discussion.

Case and point

Energy-saving LED traffic light bulbs do not emit enough heat in winter to melt snow off their lenses, causing traffic accidents.

LED traffic lights are so energy efficient that they do not produce enough excess heat to dissipate any snow that covers them. It turns out, perhaps in an homage to bad engineering everywhere, that the inefficiency of incandescent light bulbs was previously relied upon to keep traffic signals unimpeded. The new LEDs do not achieve the same effect, which has resulted in a few accidents and even a death being blamed on obstructed traffic lights. Source Engadget

All year round they present these advantages compared to incandescent bulbs:

  • 75% reduction in power consumption and related costs
  • Increased brightness and visibility in all weather conditions
  • LED bulbs last twice as long as incandescent bulbs
  • Saving on maintenance costs

For a few weeks in winter, they may have this disadvantage: snow does not melt

And it requires: A one-time retrofit of lens heaters that use electricity for a few weeks in winter

LED light bulbs now require lens heaters that use whatever energy saving is achieved.

No, that is another stupid “But sometimes” argument. The energy saved greatly exceeds the energy used to heat the fucking lenses (for a few weeks) in winter.

We have a solution that brings with it all the advantages we could hope for, a solution that is cross-dimensionally better than anything that came before, that fulfils our wildest dreams and deepest desires and solves problems of humanity–both known and unknown–for generations to come…but sometimes God forbid, our perfect solution creates a small new problem for which we must now cater, even though it is astoundingly simple to mitigate and only happens <1% of the time. The only reason the original solution did not exhibit this particular problem is because of a flaw in its design or a limitation of the chosen technology.

Back to shapes…

Solution Candidate 3: Cloverleaf

A Just a cloverleaf type shape


  • Rounded shape is less spiky and “cornery”
  • symmetric in 4 axis (like the square)
  • it is a lucky charm


  • area is difficult to calculate
  • crevices collect dust
  • top collects rain water
  • bottom looks like a butt

The cloverleaf has a completely different set of advantages and disadvantages, it meets new requirements and creates new problems, all the while completely neglecting the original requirements we identified to be important.

People draw parallels, (as they did with the number of axis of symmetry), in an attempt to make the cloverleaf solution seem like it actually fulfills some profound requirement. By comparing it in such a way, it’s easy to assume it automatically inherits any benefits presented by the square. In actual fact, it does none of those things because its a separate shape.

False Equivalency This phenomenon is called false equivalency.

False equivalence is a common result when an anecdotal similarity is pointed out as equal, but the claim of equivalence doesn’t bear because the similarity is based on oversimplification or ignorance of additional factors. Source Wikipedia

That does not mean the cloverleaf is inherently bad in its own account. It’s advantages are clear and if you are not concerned about its dust collection properties and area calculation then a cloverleaf is certainly a pretty shape to have! It solves a different problem.

However, it is a bad solution for the proposed problem because none of the requirements are satisfied. Sure, it’s a nice shape and a lucky charm but it makes no sense to compare it to the square. It excels at some aspects with which the square cannot possibly compete because it was designed to do and be something else.

What is even worse is when people misunderstand and think their solution does one thing or works a certain way when–and telling them is never advisable–, it does not do what they claim and their string of arguments is based entirely on wrong assumptions.