According to a survey published by Dresner Advisory Services, over 50% of companies are using big-data analytics. A closer look reveals that the adoption rate varies significantly by industry, with financial services and telecommunications leading the way, followed by education and healthcare. But the top five includes no mention of logistics.
When one thinks about big data, logistics is rarely the first industry that comes to mind. Ironically, however, it’s likely to be the one that stands to benefit most from its adoption.
The use of predictive analysis to estimate and prevent bottlenecks in the supply chain is crucial, especially in an industry where punctuality, transparency, and privacy play key roles. And with more and more consumers opting for e-commerce, pretending to stay relevant without relying on big data is naive.
The last mile of a package’s journey to the buyer is the most painful step for logistics companies. It’s also the most expensive, acocunting for over half of total shipping costs. Delays due to traffic jams, parking difficulties, bad weather, force majeure, and even more trivial challenges such as apartments without elevators, all contribute to adding up costs and negatively impacting customers’ experience.
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