Leveraging Predictive Analytics In E-Commerce Logistics

Source: Found here

David Barberá Costarrosa has been dedicated to e-commerce and its ecosystem since 2017. Entrepreneur, Cofounder of Beeping , among others.

The whirlwind of e-commerce and its constant evolution poses a very challenging scenario for companies when it comes to optimizing logistics processes. Over time, consumers have become increasingly demanding when it comes to the optimization and delivery time of their packages.

In this context, predictive analytics takes a leading role and also establishes a paradigm shift. Why? Because by analyzing large volumes of data, it's possible to forecast future demand and anticipate possible supply chain disruptions to meet customer expectations.

In addition to the above, predictive analytics makes it possible to identify shopping trends and predict demand peaks through the use of mathematical models, machine learning and big data analysis. From an e-commerce perspective, this information becomes essential at specific times such as holidays, when companies need to rely on it to determine which products and how many of them will have the best sales during those periods. Without this data, stockouts would likely affect not only the supply chain but also the business's profitability.

Predictive analytics, thanks to its use of data, becomes a fundamental resource to improve business dynamics in the following ways:

As one example, Amazon uses predictive analytics to understand which products will be most in demand in specific geographic sectors. Based on that data, it distributes merchandise strategically to meet demand, thus reducing and optimizing logistics resources.

This same technology can be used for smaller retailers to identify more basic patterns and adjust inventory accordingly.

Reducing the likelihood of supply chain disruption is a vital function offered by predictive analytics. Among other features, it allows real-time detection of vulnerabilities and delays in transporting goods, whether due to inclement weather or other holdups. Taking predictive analytics into account will enable the adjustment of delivery routes to reduce delays.