Supply chains had an unusually challenging year in 2020, one that will likely result in considerable changes. After the Covid-19 pandemic caused massive disruptions around the globe, logistics companies are taking new steps to prevent similar situations in the future. Data analytics is taking center stage amid all this change.
Experts predict that the world will generate 463 exabytes of data every day by 2025. As markets grow increasingly crowded and competitive, harnessing this wealth of information could be what determines if supply chains fail or succeed. Competition aside, the growing amount of available data provides organizations with the tools they need to create more agile, resilient supply chains.
Here’s a closer look at how data analytics is transforming the supply chain this year.
Shipping speed optimization
Few trends have impacted modern supply chains as much as e-commerce. As online shopping continues to grow, consumers have become accustomed to the quick delivery speeds of companies like Amazon. In response, more supply chains this year will use data analytics to optimize their shipping speeds.
Unsurprisingly, Amazon was an early leader in this area, offering one-day shipping in 2019. The e-commerce giant uses data analytics to track its inventory and enable rapid deliveries by finding the warehouse closest to the vendor and customer. It then sends the order to that specific facility, allowing the fastest shipping possible.
Low-volume high-mix (catalog) electronics distributors also provide overnight delivery options. These distributors cater to designers and engineers that need a wide variety of components readily available.
E-commerce has only grown since then, along with consumer expectations. As more customers expect faster shipping speeds, analytics will become increasingly crucial. More companies will analyze warehouse distances, routes and potential obstacles to enable faster deliveries.
Supply chains have adapted to incoming demand changes for years, but analytics takes this a step further. With more data at their fingertips, companies can predict shifts in demand on a far more granular level. While traditional demand forecasting uses historical demand levels, machine learning can predict new changes.
Supply chains now have access to more real-time data, revealing trends as they develop in the moment. Predictive analytics then use this information to tweak estimations using past demand shifts. Supply chains can adjust inventory levels appropriately to minimize waste and disruption amid changing trends with these insights.
Today’s digital-native consumers adopt and discard trends quickly. As a result, in-depth demand forecasting is becoming a more critical part of supply chain operations. Now that the analytics tools necessary for this process are more accessible, even smaller companies will embrace demand forecasting.
One of the most painful lessons supply chains learned in the past year is the need for emergency preparedness. After the widespread disruption of Covid-19, it’s clear that the logistics industry needs to be more flexible and resilient. Data analytics plays a crucial role in this effort.
Disasters like the Covid-19 pandemic provide unusual, outlying data that companies would typically disregard. This year, supply chains will use it to model and prepare for future emergencies. Walmart has engaged in disaster preparedness like this for some time and was able to withstand the pandemic better than most because of it.
Data from the pandemic can reveal where supply chains’ weak points lie. Organizations can then take steps to correct them, becoming more resilient in case of future disasters. Supply chains can either remodel their standard practices or create contingency plans with this data.
Supply chains have major shifts ahead of them
After a period as disruptive as the past year, supply chains have little choice but to innovate. Data analytics are at the heart of this transformation, guiding logistics companies to a faster, more resilient and profitable future.
As the world produces more information, analytics will continue to unlock new opportunities. Before long, the global supply chain could look entirely different, and data will drive that change.