With decomposition, we can break down a problem or situation to smaller pieces and tackle them accordingly.

Pattern recognition is about finding the similarities or patterns among small, decomposed problems so that complex problems can be solved easily.

By finding the similarity in the causes of the problems, we are able to seek similar solutions that have been derived before.

Personally, it is my favourite stage of problem-solving. In fact, if you are a fan of biomimicry, this can be applied in your course of work.

Not only does pattern recognition help in product design, but it can also be applied to the process as well. For instance, the bees algorithm is a population-based search algorithm, which mimics the food foraging behaviour of honey bee colonies.

Here is a short documentary video that explains how the bees algorithm came about.

Pattern recognition encourages us to tap into our natural ability to look for similar patterns, which then helps us look at problems from a different perspective.

Because everything is a remix. Sound familiar?

The concept of abstraction guides us to keep what is relevant and discard what is not relevant to the program.

Abstraction is aligned with the Bauhaus Movement, ‘Less is more,’ which was the motto of Ludwig Mies van der Rohe, an advocate of minimalism in architecture. Or the concept of minimalism in Zen, which is to get rid of anything unnecessary and leave only the essential.

Abstraction is a perspective that goes beyond creating a simple and clean aesthetic when it comes to design. Rather, it is a way of being mindful and selective when deciding which element is necessary or redundant to the context of a situation.

Algorithmic thinking is a way of getting to a solution through clearly defining the steps needed. It is a sequence of step-by-step fulfilment of a task. It can be quite intimidating for creatives to adopt this way of thinking as the temptation to take a different route is always there.

Back when I was learning to code, I was inspired by Joshua Davis’ book, Flash to the Core, and how a few lines of AS2 code and parameters could generate digital artwork with just a couple of clicks.

At present, I have seen the popularity of using Photoshop Action (an algorithmic approach to running Photoshop tasks) to improve work productivity and creativity. As computation power improves, with generative design, using algorithms to design a product to fulfil a task efficiently will be inevitable as well.

But algorithmic thinking isn’t only limited to design. I have found it to be quite useful in running teams, especially when using it in the context of kanban, a system for managing work as it moves through a process. It is like putting parallelism and concurrency in a real-world context where you can incorporate an algorithmic way to design an efficient system.

I can’t speak for everyone, but learning the principles of coding has helped me to solve and view problems from a perspective that is structural and systematic. It allows me to plan the solution before I start to work on a project. Either with developing an application, designing a logo, or managing a work plan, I am able to visualise the solution in a systematic manner, with multiple possible configurations before I set out to work on it.

For those who have not tried coding, I urge you to give it a try. It can be as simple as Scratch, but the point is to get to experience the thinking process behind programming. If you eventually give it up and don’t want to stick with it, that is fine — but at least you will have gained a new set of tools that will help you solve problems.

For those who have tried coding, that is great! I hope this article brings you a perspective on how it can be applied in a different way.