As retailers with overstock and “a range of measures of shipping demand across the U.S. are sliding, freight rates are falling as a result,” according to an article in The Wall Street Journal and various other sources. This pattern has reduced capacity, making it more challenging for shippers to get the shipping capacity they need as they also deal with other challenges affecting the supply chain.
In response, logistics professionals seek innovative ways to improve operations efficiency. Analytics and business intelligence can help. Logistics analytics relies upon data relevant to supply chain management and the logistics operations of a company. It can help shippers optimize operations by enabling them to track shipments, consider trends, create better delivery processes, streamline costs, consider supplier performance, and create better customer service.
Data analytics in logistics can provide shippers with a host of important benefits. These include the following.
Quality data is the key to meaningful analysis. You can automate the collection of certain data like that from carrier invoices, order files, and tracking events. Automated data collection processes introduce benefits that include:
Automation also helps create optimal efficiency in event tracking throughout a given supply chain. By tracking events, you can see exactly where a slowdown happened. You can also use data to detect the carriers that best suit your existing freight infrastructure and identify patterns like the carriers with the highest exceptions and freight loss instances. This kind of information helps shippers create a more dependable carrier network, allowing them to adjust to fluctuations within the industry as they arise.
Gaining access to more relevant data creates more real-time visibility in logistics to help parcel shippers immensely. Increased data shares more information about the shipment process, and technology allows shippers to gain this information as it’s happening throughout the shipping process to stay on top of every step.
Improved visibility allows shippers to:
Parcel shippers can use analytics to improve supply chain efficiency. Through data analytics for logistics, shippers gain detailed insights into performance and cost. They can use the insights gained to create more efficient processes and better shipping strategies while they also continue to notice areas for improvement. Ultimately, making data-based changes like these can lead to significant benefits for supply chain efficiency, such as improved service levels, cost savings, and higher customer satisfaction.
Effective analytics can bolster performance related to various supply chain events:
Data analytics in logistics and supply chain management are helpful to shippers, and the business intelligence they can glean from analytics is invaluable to improving supply chains and operations. Yet, that doesn't mean it's easy to reach the goal of analyzing data. There are numerous challenges to implementing analytics and keeping up with the process from then on.
Shippers who want to implement analytics may find the cost of technology a major barrier to moving forward. Many shippers won’t have the budget for the necessary logistics analytics software and hardware needed to analyze big data, in addition to extra expenses for ongoing maintenance and upgrades. The running of this technology also requires expenditures on staff who can maintain it. The costs involved in adding this technology to a company can be prohibitive — an important factor that deters many shippers from taking full advantage of the opportunities analytics can provide.
Another challenge of doing it yourself with analytics is that aggregating raw data can be a complicated process. This requires the right tools and expertise, as well as the time and resources to go into the process. When your company cannot fully devote these factors to in-house aggregation, it’s easy to struggle with efficiently transforming large (sometimes massive) amounts of data into actionable analytics and insights that guide decisions. The process can become inefficient and even debilitating, defeating the purpose of trying to collect and use the data. This difficulty can prevent shippers from ultimately making decisions that can improve operations. In the end, the analytics efforts and the lack of strategic action cost valuable time and money.
It’s not so difficult to collect data, but data from different programs, purposes, and parts of the organization are not standardized. It doesn’t match up to allow you to quickly and adequately compare and use it. When the data is not standardized, it can be challenging to compare it accurately across different sources, which hampers shippers’ ability to identify trends and take corrective action.
This challenge shows why standardizing the data becomes another part of the logistics analytics process. But, what ends up happening for many shippers who try in-house analytics is that they struggle to make sense of their data and instead end up in a state of confusion and inefficiency. Overall, achieving standardized data is essential for allowing shippers to maximize the value of their data and make informed decisions from that data.
Shippers who are ready to move forward with using data to inform logistics decisions can follow best practices for doing so.
Logistics analytics can provide various benefits to shippers, including automated data collection, better real-time visibility, and improved supply chain efficiency. In addition, analytics can help companies perform better in response to various events in the supply chain, keeping up with changes as they occur, such as falling freight rates.
Intelligent Audit can provide the expertise shippers need to analyze logistics data effectively and gain business intelligence from it. Relevant services Intelligent Audit offers include:
Find out how Intelligent Audit can help your company implement data analytics for logistics and use that analysis to create better business decisions. Start a conversation with Intelligent Audit today.
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