In recent years, AI has become such a hyped-up concept that all and their housecats want to use artificial intelligence. Moreover, it has become the silver bullet answer at the bottom bullet point of the slide deck. I get it. ChatGPT showed the amazing capabilities of large language models, and I am astonished almost daily by the capabilities and use cases. However, I want to discuss how we approach problems in business and how we can work smarter and use machine learning as a highly efficient tool when it is needed and not as a Swiss Army silver knife bullet.

Scrum is a popular agile methodology that is used in project management. It emphasizes teamwork, accountability, and iterative progress toward well-defined goals. Scrum is widely used in software development, but it can also be applied to any project that requires a flexible and collaborative approach to problem-solving.

In finance and economics, the Pareto principle has been used as a rule of thumb for a long time.

• The Pareto principle states that in many situations, roughly 80% of the effects come from 20% of the causes. This might mean:
  • 80% of a company's profits come from 20% of its customers.
  • 80% of software bugs stem from 20% of the code. However, what the underlying data says is that the phenomenon a Pareto law applies to means that the data likely is power-law distributed.
    A power-law distribution is a mathematical relationship where the probability of a certain value is inversely proportional to some power of that value. Most of the phenomena in the real world can be modeled by either normal or Gaussian distributions or power law distributions (This will probably follow some sort of Pareto principle). Just doing some sort of heuristic on the Pareto principle can tell you a lot about the distributions and how they behave.