Time passed, we overcame pandemic, and things apparently reached a state of unreal calm because the only thing that was obtained was a new level of demand that came to stay with a consumer who is not willing to pay more, but to keep the benefits added to a global inflation that prints a challenge that we can only face with technology based on data and the famous artificial intelligence (AI).
This is where the planning department becomes more important in the supply chain. I invite you to think of it as an orchestra conductor that, under the midday sun, must guarantee service to this new demanding market and at the lowest possible cost. As already mentioned, it is necessary to have tools that enhance this area and AI combined with organized data is the new crystal ball that this director has to make everything sound like Beethoven's fifth symphony.
Today, data science is not optional, it is an obligation in order to generate forecasts that allow us to anticipate with the least possible error, and in this new market, intuition is dangerous if it does not have solid numerical support. To go deeper into this new world, data science must be understood as a compendium of three professions: the data engineer, who manages the ERP to maintain the compilation of data in each of the transactions; the data scientist, in charge of generating new algorithms (in Python, R, SQL, among others) that allow analyzing the data according to the answers we need; and finally the data analyst, who shapes all these results (Power BI, tableau) and keep generating more interactions for more answers, compiling them to have visual or summarized forms that allow making the most accurate decisions. It is easy to confuse these three moments in which each specialist takes part but without a doubt, a supply chain without this group of thinkers and not having an S&OP in place is like flying a plane at night without instruments.
We conclude that it is vital to have dynamic dashboards, filled only with vital online information, with a complete mass of data and operated by AI, otherwise, you are only analyzing the surface of the information as it was done ten years ago.
In an evolved model, the goal would be to define a roadmap from operations that is more precise than the intuition or the directors' sense of smell, since this new generation will be able to analyze astronomical amounts of information, not only about the company, but also to establish connections with external variables such as weather conditions or the behavior of currencies, and this is only the tip of the iceberg.
Just as AI provides fast and innovative improvements, it also has several limitations and despite generating accelerated changes, it is still important the human interaction that with its criteria can validate or not an AI suggestion, as well as the construction of new algorithms to improve the current developments (NLP, ANN, FL, and ABS/MAS).
Nowadays, supply chain professionals must align themselves with these new forecasting models, which are and will be the main tool to efficiently plan our resources and satisfy a market with ever-increasing demands.
