Data Science Applications in Logistics and Transportation
Each year billions of packages are shipped to customers across the world. Do you have any idea of the amount of data that is collected at every supply chain touchpoint? Think of it this way- from a customer initiating an order to the final delivery of that order, data is generated in the form of customer information, GPS data, the number and types of items, delivery partner information, etc. Apart from this. Logistics and Supply Chain Management industry also deals with innumerous variables and uncertainties. Uncertainties like inadequate area mapping, the imbalance between demand and resource availability, vehicle breakdown or even bad weather conditions affect the logistics and SCM at a larger level. The complex and dynamic nature of this sector, as well as the intricate structure of the supply chain, make logistics a perfect use case for data science.
The applicability of data science to most, if not all, industries is evident. Logistics centers on the design and implementation of the interaction between people, products, and processes.
Highlighted by various researches in recent years, Big Data and logistics are made for each other. Companies are often sitting on masses of under-utilised data that could aid them in a number of ways.
Some of the current applications of Data Science by data-driven businesses within the industry include:
Reducing freight costs through delivery path optimization
Dynamic price matching of supply to demand
Warehouse optimization
Forecasting demand
Estimating total delivery times
Extending the life of assets through finding patterns in usage data — identifying the need for maintenance
Today, Predictive Analytics and Route Optimization are two major ways through which AI and Data Science can help the Logistics Industry. Let’s have a look at how Rubikon Labs is doing it for you.
At Rubikon Labs, we study and analyze behavioural patterns of machines which in turn account for detecting anomalies. Companies can then use predictive analysis to detect instances such as weather patterns and deal with them better. In our previous blog, we explained how predictive analytics can help forecast the correct demand and in turn optimize supply.
Rubikon Labs also helps you in Route Optimization- finding the best possible path from point A to point B. This helps improve the efficiency of the system and reduces the time taken to deliver a package. Our model gathers information from all sources- GPS, weather forecasts, delivery schedules, and uses the data to predict the best route for delivery.
Data Science and Data Analytics are the tools to unleash the power of Logistics! Do Not Wait, Contact Us Now.