It’s undeniable that recently, there has been an explosion in the knowledge available to companies relative to managing their manufacturing, shipping and workforce networks that helps to solve more complex programs.
Some facts like better data collection, mathematical innovation and huge computing power seem to create better models to improve efficiency in different areas and also, the possibility of cutting supply chain costs by up to 15%.
But the problem is politics taken by firms, because some companies are a little bit reluctant to apply these new methods.
In the article, we can find the example of a human planning a track route that will always avoid a “drive by” when a computer will sometimes find that a drive-by can be more efficient. This seems to be difficult to perceive by humans.
Other times there are problems such as conflicts of interests between different departments or between objectives and motivation and the solution often lies at having a big picture of efficiency; if we could look at the whole thing, we will optimize the performance of the entire corporation.
This battle between algorithms and humans will get sharper as analytics penetrate more aspects of organizational life.