Success in a highly dynamic business environment requires the ability to make informed decisions faster than the competition.
Businesses can no longer afford to dwell on vast amounts of data to “train” human intuition.
In the transportation industry, tomorrow’s successful companies will not be those that do only one thing really well, but those that can optimize and harvest value out of a multitude of activities.
The more algorithms can improve, accelerate decision making and support human experts, the more time and resources those experts and their enterprises will have for innovation.
We already see increasing volumes of data being captured and processed to facilitate a better understanding of everyday life.
In fact, we see it in a variety of everyday applications, from the development of movie recommendations based on viewing habits to the use of fitness trackers to encourage healthy behaviors.
The information to be found in data is critical to the transportation industry as well.
Integration of diverse data sources is not only allowing real-time prediction of goods movement from source to consumption to recycling, but the data itself will explode in volume with increasing automation within the supply chain.
But while the volume of data will continue to grow, the speed at which this data will lose value will also increase. Industry experts already struggle with leveraging vast amounts of data to gain an edge over the competition.
Nor will humans and Artificial Intelligence (AI) be sufficient, especially when it comes to training AI to respond to unprecedented situations.
In this paper, we present empirical evidence to support the hypothesis that freight supply chains (FSC) of the future will be governed by Intelligence Amplification (IA), or human intelligence complemented by AI.