Big data can be an ideal ally to accompany the logistics sector in these vertiginous times, during which new business models also emerged, such as last-mile suppliers, dark stores (stores that only fulfill the function of warehouse and pick-up ) or the decentralization of demand.

The data sources available come from both the historical activity of the vehicle fleet and the transactions with customers, the manufacturing systems and operations of the goods to be transferred.

Preventive Maintenance

Sensors located in mobiles, in manufacturing facilities or in the warehouses that were automated, play a key role so that unscheduled stops become part of the past: a reality that extends throughout the entire logistics chain. Preventive maintenance saves costs and increases both the efficiency and the life cycle of the machinery that holds the company’s infrastructure.

It is also possible to even appeal to unstructured data sources, such as customer complaints about shortages made through social networks or weather issues that may affect the journey.

Optimal routes

New technologies make it possible to evaluate and reconsider the efficiency of a route in real time: an unscheduled traffic jam or an emerging street protest can be detected while they are still starting and serve as a starting point for the system to redefine the route.

By combining the data of the delivery points plus the reception points and the available routes, it is possible to draw optimal routes, with all the benefits that this involves: a decrease in fuel consumption, a greater use of vehicles (also extending their life cycle), a lower carbon footprint and less exposure to accidents.

Inventory accuracy

Stock control is, at the moment, one of the most used applications of big data applied to logistics, since continuous monitoring of how much merchandise is in each location can avoid shortages or surpluses.

It is not a minor issue: many industries, such as large supermarkets, handle catalogs with thousands of products. Ensuring the supply of each and every one of them is a first level challenge.

Even if it is combined with tools that allow forecasting demand, such as Intelligent Forecasting, Nubiral’s artificial intelligence solution that with exact data will make inventory savings, the precision in time and form of deliveries could reach unprecedented levels.

Perishables goods

Another key aspect is the management of perishable products, a key aspect in the food and health industries. With the correct application of big data and artificial intelligence tools that combine possible demand with supply, the amount of items wasted can be reduced to zero.

In this sense, vaccines against COVID-19 represented an extreme challenge for the world of logistics: a product with two doses, with an expiration date, with temperature requirements for its transport and with a potential demand equal to the number of people in the whole world. How much is it worth having made the right investments so that not a single dose was wasted?

Fleet management

From the point of view of fleet maintenance, the possibility of equipping vehicles with sensors is opened in order to anticipate damage and, thus, reduce maintenance and repair costs.

Looking to the future, big data is also the key for companies in the sector to experiment with new business models, develop more efficient delivery mechanisms and reach new milestones in terms of efficiency in distribution.

The optimization of logistics processes does not only have business benefits: it is also a key component for sustainability – the fewer vehicles circulating, the less carbon dioxide emissions – and, as it was demonstrated in 2020, it is also a key to the continuity of product delivery even in disruptive times.