📈 #40 Can't solve every core decision-making business problem with technology? Here's why:

Theoretical computer science has the key to solve real-life business problems.

Two months ago we enjoyed the Oscars.

Those awards are the epitome of actresses and actors in their career. They highlight the best works they created.

But there are also other awards for computer scientists also recognizing their work over decades of effort.

This is the case of the Turing Award, an annual prize given by the Association for Computing Machinery for contributions of lasting and major technical importance to computer science.

Last year it was given to Avi Wigderson, a computer scientist and mathematician that has been working for decades on theoretical computer science, the branch of computer science that studies computational complexity, probabilistic computation, and algorithms, among others.

Since we already saw some initial concepts in the last post, today in Feasible we’ll see:

• 🏆 The challenge of complexity

• 🥙 The no free lunch theorem -and no, it’s not related to food-

• 🧲 The power of heuristic algorithms and how they help you find high-quality solutions in no time

Let’s go for it!

🏆 The challenge of complexity

Many of the business problems we encounter today are computationally complex.

This means that finding an optimal solution within reasonable time and resource constraints is an arduous task, if not impossible.

Supply chain optimization, scheduling, resource allocation, and routing are just a few examples of these puzzles that require advanced techniques to tackle.

And there is a field in computer science that studies it. It’s called computational complexity theory. This field helps in classifying problems based on their inherent difficulty, and predicting the efficiency of algorithms.

We’re not going into the details because, you know, it’s a complex topic 😅 but if we simplify it as much as possible, let’s say there are some problems that doesn’t have any efficient algorithm to solve them: