Why Logistics Companies Need Data Analytics to Survive

It’s hard not to generate too much hype when discussing the importance of data. What was once just a buzzword has come to dominate nearly every aspect of how a company does business – and for good reason: it has proven time and again to be an invaluable asset for companies both large and small.

For logistics companies in particular, data is proving to be increasingly powerful. In fact, industry experts continue to sound the alarm, warning logistics companies that unless they begin capitalizing on their data, they will likely be overrun by data-driven global giants. Perhaps the most significant threat comes from Amazon, whose growing success is largely driven by its effective use of data.

So why is data so important for logistics companies? And how can they utilize data for their success? We’ve outlined three key benefits below.

  1. Operational Efficiency

The core business of logistics boils down to operations, from planning routes, verifying delivery addresses, shift planning and more. Logistics companies can utilize data analytics to streamline these operations. For instance, the ability to analyze route preferences, traffic densities, weather conditions, etc. can provide insight on how to improve driving performance, save on fuel, and deliver products on time.

For proof, consider this: UPS drivers (almost) never turn left. Why? By utilizing data from their routes, delivery time and other statistics, they found that turning left reduces the chances of an accident and cuts delays caused by waiting for a traffic break, thereby wasting fuel. Accordingly, they have saved over 39 million gallons of fuel and avoided 364 million miles since they started route optimization in 2001.

  1. Risk Analysis

Minimizing risk is important for any businesses, especially logistics companies who can’t afford to chance late deliveries or unhappy customers. One of the ways big data helps eliminate risk for logistics companies is through the use of predictive analytics, which helps anticipate maintenance requirements of delivery vehicles in order to avoid unplanned breakdowns. With predictive analytics, logistics companies can ensure customer satisfaction and on-time delivery, while simultaneously saving time and money. As a white paper from the World Economic Forum notes, “through optimized maintenance scheduling, it can cut maintenance costs by up to 30% and reduce the incidence of breakdowns by 75%.”

  1. Customer Experience

In today’s world, where people are used to getting anything they want with the click of a button, customer expectations are extremely high. Logistics companies can utilize customer data to better understand customer requirements, perform targeted marketing and enhance customer interaction. For instance, UPS’ ‘My Choice’ service enables customers to manage delivery location and timing via their mobile devices, so they don’t have to worry about not being home for a package delivery. Such flexibility is of increasing importance to customers, as noted in a 2016 study by Deloitte.

The Conclusion

Data analytics plays a powerful role in helping logistics companies improve operations, minimize risk and meet growing customer expectations. Logistics companies that have yet to implement data analytic solutions are at a significant disadvantage, particularly when faced with growing competition from Amazon. As a Logistics Management study notes, unless logistics companies utilize their data effectively, “Based on volume, scale and buying power, Amazon will command more attractive pricing than other freight forwarders, enabling them to secure capacity at a lower cost and ensure profitability as they fill that space more easily than competitors.” 

To ensure your logistics company is handling its data effectively, contact Treehouse Technology Group for a free consultation.

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