{"id":33738,"date":"2022-01-18T14:55:36","date_gmt":"2022-01-18T03:55:36","guid":{"rendered":"https:\/\/www.institutedata.com\/?p=33738"},"modified":"2022-01-18T14:56:44","modified_gmt":"2022-01-18T03:56:44","slug":"how-data-science-helps-logistics-companies-make-smarter-moves","status":"publish","type":"post","link":"https:\/\/www.institutedata.com\/us\/blog\/how-data-science-helps-logistics-companies-make-smarter-moves\/","title":{"rendered":"How Data Science Helps Logistics Companies Make Smarter Moves"},"content":{"rendered":"

Logistics companies have experienced a spike in demand during the pandemic. Online shoppers and panic buyers across the country resulted in an increase in wholesale and retail operations. Couriers and vendors expedited goods to multiple locations across the country to cope with the influx of orders and home deliveries.<\/span><\/p>\n

But with every online purchase comes a trail of user data. The constant collection of data begs the question:\u00a0<\/span><\/p>\n

How can logistics companies leverage the pile of customer data collected?<\/span><\/h2>\n

Logistic giants such as DHL, UPS, Amazon, and FedEx have realized that investing in data science is a smart move in order to stay on top of consumer behaviors. Data science is emerging as the key to unlocking the potential of improving logistics companies to globalize operations.<\/span><\/p>\n

1. Big data improves logistics operations and the customer experience<\/span><\/h2>\n

We live in a consumer-first world where we want things now. As a result, we are constantly striving to improve ourselves and the way we work to adapt to market demands.<\/span><\/p>\n

Big data presents the opportunity to optimize performance across the board. Logistics companies are often challenged to automate and optimize their services. A 3PL survey reports that \u201c70% of logistics companies agreed big data would be best applied to route optimisation.\u201d<\/span><\/p>\n

Amazon credits the expansion of its business to investing in big data, which has helped it to better understand its operations and customer base. This, says Amazon, has increased its customer base.<\/span><\/p>\n

Route optimization assists logistics companies plan cost-effective strategies to improve operations and transport networks. It also helps to contend with unfavorable conditions such as high fuel costs, poor weather, and staff shortages.<\/span><\/p>\n

UPS conducted a study using big data and discovered that it was more cost-effective if its trucks avoided turning left. This caused delays and was potentially more hazardous to oncoming traffic.\u00a0<\/span><\/p>\n

Logistics companies use big data to analyze market intelligence to better understand their customers, to tailor their services to exceed customers\u2019 expectations and to improve customers\u2019 experience. Logistics factors that diminish the customer experience, such as late deliveries and restricted global coverage, can be avoided by advanced predictive techniques and real-time processing.<\/span><\/p>\n

2. Three examples of how data science provides a competitive advantage<\/span><\/h2>\n

Data science is an emerging field. The big logistics companies in APAC and worldwide, are only now starting to recognise the potential it has to transform global transport networks. Apart from route optimisation, data science provides a competitive advantage to other areas including:<\/span><\/p>\n