Computational Thinking: moving fast, in the right direction-EN

“More and more traditional companies are realizing that, to compete and grow in a digital world, they must look, think and act like software companies.” – McKinsey

An organization is a group of people who think; as a group and individually. We think to achieve personal, professional and organizational objectives. We do so to solve, at each of these three levels, numerous types of problems; simple, complex, recurring, unique, high impact, low impact… We need to choose every day which direction to follow; where to invest our limited time.

The challenge of constant decision-making

Can we think about and consider every action we take?

Impossible. We know that our brain consumes energy when facing new challenges, so it is somehow programmed to go into saving mode when faced with known and familiar situations. And in organizations, we create structures with well-defined roles to optimize our decision-making. There are numerous tools to distribute these responsibilities in an efficient and well-defined way. This allows us to focus only on a certain number of challenges to be solved on a daily basis. But it has its risks.

Feeling too comfortable in our field of action and not asking questions that go beyond our scope will result in missed opportunities, personally, professionally and organizationally.

For example, if you are thinking about using the RACI matrix to delimit your team’s decision making, you may find the following McKinsey article interesting, which proposes to give a voice, and therefore encourage everyone on the team to think and ask questions before a decision is made, even if the final word or vote rests with just a few or a single individual.

Let’s look at an illustrative example of this; legionary ants.

Legionary ants are known for their mass hunting behavior, which is very efficient and usually guarantees success. Their modus operandi is to form large columns of ants that move in search of prey. During these hunting expeditions, the ants follow a path determined by pheromones left by the previous ants, forming a kind of ant “highway”.

The problem arises when these ant columns encounter an insurmountable obstacle, such as a body of water or a vertical obstacle. In such cases, the ants continue to blindly follow the previous ones, without questioning the viability of the path, even when this behavior can lead to large numbers of ants advancing without finding a solution and reaching a horrible end; against the survival of the organization.

Letting be carried away by the inertia of a solution that has worked before is a real risk in a complex and changing environment such as the one organizations live in today. The ability of each of the gears that make up your machinery to think is an intangible that cannot be outsourced.

Our disruptive partner

Realistically, not all of us have the skills, or even the information, to make the right decisions. But it is indisputable, we all add up and it is important that we learn to distinguish when it is necessary to use critical and logical thinking, to break the loop of <<it has always been done this way>>.

Undeniably, technology, and specifically, computers along with software solutions, are becoming the protagonists of the most challenging and challenging business of existing business models, at an ever increasing speed. Code allows us to create worlds and products accessible from different devices with a couple of clicks. Networks of people, machines or a synergy of both are generated across the length and breadth of our globe thanks to internet connectivity and software. Now even with new artificial intelligences emerging every day.

The feeling of vertigo is inevitable. We do not like what we do not know or control. Arthur C. Clarke once said that “any sufficiently advanced technology is indistinguishable from magic”. But we must not forget that all this has been created by man, there is nothing more human than the ability to design tools that help us to be better to achieve the goals we set. And also, the transfer of knowledge of how to use them. This is because we are better at moving forward together, collaboratively.

And now we have created a traveling companion, which frees us from repetitive tasks, is capable of performing large calculations in milliseconds, can process huge volumes of data, and also store all the information needed. We need to learn to communicate in the new ecosystem that has been created by their arrival.

Code is the new universal language. Computational Thinking goes further.

Marc Andreessen, creator of Nestcape – or what was for many of us, our first web browser – already warned us with his sentence “software is eating the world”. Now “software is the world and data is the most valuable energy”.

It is time for us to learn to communicate in this new ecosystem in which information is growing exponentially and for that we need new skills and tools. And no, it is not necessary to learn to program to get them. Although it can be a useful way to understand how to create business and solutions in the new digital world, it is not trivial and the cost-benefit does not make sense in many cases. There are more forms of communication than just language. And we can understand the environment, without learning to code with programming languages.

Computational Thinking is a conglomerate of all the learning and best practices that computational science has managed to acquire until today, allowing us to understand and create new solutions that respond to the complex challenges in this new world.

What is Computational Thinking?

Let’s recover the idea that it is a set of several learning processes and let’s see what they are;

1. It is a mindset that allows us to have perspectives and express ideas in a structured way favoring their understanding.
2. It is a macro-skill composed of four pillars; abstraction, decomposition, pattern recognition and algorithm design. Essential to understand complex problems and design efficient and reproducible solutions in the new digital world.
3. It is a group of tools and concepts that provide a homogeneous vocabulary and way of working that fosters collaboration and cooperation.

1. Computational Thinking: mindset

The most remarkable feature of computers is that they can store, manage and analyze large amounts of data, in addition to their computational capacity, which is very useful for making informed decisions, analyzing the vast amount of information we generate and collect today.

Does this mean that we have to start thinking like machines? It has nothing to do with this idea. Computers are nothing more than a tool that replicates very well part of our cognitive abilities. They even surpass us in performing the tasks we have just discussed.

But they need us to tell them exactly what to do, unambiguously and unambiguously. And that means that in order to take advantage of them, we have had to learn to design solutions following some standards, principles and best practices to maximize their usefulness. To such an extent that we have created communities of people who have studied how best to express and represent the solutions so that they are maintainable both by different people, improving their readability, and over time, looking for forward-looking solutions and allowing their adaptability and continuous improvement.

2. Computational thinking: macrocapacity

Jeannetter M. Wing coined the term Computational Thinking and wanted to highlight in his paper of the same name, that it is an attitude and a set of skills that everyone, programmer or not, should have. What skills are they? And how do they help us?

1. Abstraction: it helps us to have a complete picture of the complex problem, filtering only the information that is really relevant, to avoid noise. This allows us to have a global vision to be able to face the challenge by prioritizing the tasks while helping us to understand which are the elements that make up the system and their relationships.
2. Decomposition: is the process by which we break down a complex problem into smaller, more manageable challenges. This helps to avoid paralysis while allowing us to focus our effort and resources on an achievable task.
3. Pattern Recognition: we will identify if there is any pattern among the different subproblems we have, that is, if there are any that are the same or similar where an already implemented solution can be reused. This allows us to optimize resources.
4. Algorithm Design: this skill facilitates the design of a step-by-step that tells us how to solve the problem efficiently, helping us to plan to be clear about the actions to be performed and their order.

3. Computational Thinking: tools and concepts

When facing complex problems, we need to have a strategy that avoids paralysis and helps us to trigger a solution. And to be able to transfer the skills described above, we need tools and concepts that help us to apply the skills and a common vocabulary that allows us to understand each other. Throughout the years of development, computational sciences and all the people involved in its evolution, have generated a very extensive toolkit and depending on the nature of the complex problem, it will be more useful to decide to use some or others.

Knowing and using all these skills, tools and concepts helps us to communicate and collaborate in the new digital world. Computational Thinking provides us with a way to face all the new complex and changing challenges of the ecosystem in which computers and software are great allies. And you don’t need to know how to program to add value and understand the solutions.